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Solution draft log for https://github.com/link-assistant/market-research/pull/10
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| # Solve.mjs Log - 2025-12-28T03:03:30.599Z | |
| [2025-12-28T03:03:30.600Z] [INFO] π Log file: /home/hive/solve-2025-12-28T03-03-30-599Z.log | |
| [2025-12-28T03:03:30.601Z] [INFO] (All output will be logged here) | |
| [2025-12-28T03:03:31.464Z] [INFO] | |
| [2025-12-28T03:03:31.465Z] [INFO] π solve v0.38.1 | |
| [2025-12-28T03:03:31.465Z] [INFO] π§ Raw command executed: | |
| [2025-12-28T03:03:31.466Z] [INFO] /home/hive/.nvm/versions/node/v20.19.6/bin/node /home/hive/.bun/bin/solve https://github.com/link-assistant/market-research/issues/9 --model opus --attach-logs --verbose --no-tool-check | |
| [2025-12-28T03:03:31.466Z] [INFO] | |
| [2025-12-28T03:03:31.479Z] [INFO] | |
| [2025-12-28T03:03:31.480Z] [WARNING] β οΈ SECURITY WARNING: --attach-logs is ENABLED | |
| [2025-12-28T03:03:31.480Z] [INFO] | |
| [2025-12-28T03:03:31.481Z] [INFO] This option will upload the complete solution draft log file to the Pull Request. | |
| [2025-12-28T03:03:31.481Z] [INFO] The log may contain sensitive information such as: | |
| [2025-12-28T03:03:31.481Z] [INFO] β’ API keys, tokens, or secrets | |
| [2025-12-28T03:03:31.481Z] [INFO] β’ File paths and directory structures | |
| [2025-12-28T03:03:31.482Z] [INFO] β’ Command outputs and error messages | |
| [2025-12-28T03:03:31.482Z] [INFO] β’ Internal system information | |
| [2025-12-28T03:03:31.482Z] [INFO] | |
| [2025-12-28T03:03:31.482Z] [INFO] β οΈ DO NOT use this option with public repositories or if the log | |
| [2025-12-28T03:03:31.482Z] [INFO] might contain sensitive data that should not be shared publicly. | |
| [2025-12-28T03:03:31.483Z] [INFO] | |
| [2025-12-28T03:03:31.483Z] [INFO] Continuing in 5 seconds... (Press Ctrl+C to abort) | |
| [2025-12-28T03:03:31.483Z] [INFO] | |
| [2025-12-28T03:03:36.489Z] [INFO] | |
| [2025-12-28T03:03:36.511Z] [INFO] πΎ Disk space check: 8705MB available (500MB required) β | |
| [2025-12-28T03:03:36.512Z] [INFO] π§ Memory check: 8783MB available, swap: 2047MB (138MB used), total: 10692MB (256MB required) β | |
| [2025-12-28T03:03:36.513Z] [INFO] β© Skipping tool connection validation (dry-run mode or skip-tool-connection-check enabled) | |
| [2025-12-28T03:03:36.513Z] [INFO] β© Skipping GitHub authentication check (dry-run mode or skip-tool-connection-check enabled) | |
| [2025-12-28T03:03:36.513Z] [INFO] π URL validation: | |
| [2025-12-28T03:03:36.513Z] [INFO] Input URL: https://github.com/link-assistant/market-research/issues/9 | |
| [2025-12-28T03:03:36.513Z] [INFO] Is Issue URL: true | |
| [2025-12-28T03:03:36.513Z] [INFO] Is PR URL: false | |
| [2025-12-28T03:03:36.514Z] [INFO] π Checking repository access for auto-fork... | |
| [2025-12-28T03:03:37.218Z] [INFO] Repository visibility: public | |
| [2025-12-28T03:03:37.219Z] [INFO] β Auto-fork: Write access detected to public repository, working directly on repository | |
| [2025-12-28T03:03:37.219Z] [INFO] π Checking repository write permissions... | |
| [2025-12-28T03:03:37.586Z] [INFO] β Repository write access: Confirmed | |
| [2025-12-28T03:03:37.897Z] [INFO] Repository visibility: public | |
| [2025-12-28T03:03:37.898Z] [INFO] Auto-cleanup default: false (repository is public) | |
| [2025-12-28T03:03:37.899Z] [INFO] π Auto-continue enabled: Checking for existing PRs for issue #9... | |
| [2025-12-28T03:03:37.899Z] [INFO] π Checking for existing branches in link-assistant/market-research... | |
| [2025-12-28T03:03:38.914Z] [INFO] π Found 1 existing PR(s) linked to issue #9 | |
| [2025-12-28T03:03:38.914Z] [INFO] PR #8: created 0h ago (OPEN, draft) | |
| [2025-12-28T03:03:38.915Z] [INFO] PR #8: Branch 'issue-7-aaba35ea06a7' doesn't match expected pattern 'issue-9-*' - skipping | |
| [2025-12-28T03:03:38.915Z] [INFO] βοΈ No suitable PRs found (missing CLAUDE.md or older than 24h) - creating new PR as usual | |
| [2025-12-28T03:03:38.915Z] [INFO] π Issue mode: Working with issue #9 | |
| [2025-12-28T03:03:38.916Z] [INFO] | |
| Creating temporary directory: /tmp/gh-issue-solver-1766891018916 | |
| [2025-12-28T03:03:38.919Z] [INFO] | |
| π₯ Cloning repository: link-assistant/market-research | |
| [2025-12-28T03:03:39.649Z] [INFO] β Cloned to: /tmp/gh-issue-solver-1766891018916 | |
| [2025-12-28T03:03:39.733Z] [INFO] | |
| π Default branch: main | |
| [2025-12-28T03:03:39.746Z] [INFO] | |
| πΏ Creating branch: issue-9-fcb0cba15ea8 from main | |
| [2025-12-28T03:03:39.756Z] [INFO] π Verifying: Branch creation... | |
| [2025-12-28T03:03:39.767Z] [INFO] β Branch created: issue-9-fcb0cba15ea8 | |
| [2025-12-28T03:03:39.768Z] [INFO] β Current branch: issue-9-fcb0cba15ea8 | |
| [2025-12-28T03:03:39.768Z] [INFO] Branch operation: Create new branch | |
| [2025-12-28T03:03:39.768Z] [INFO] Branch verification: Matches expected | |
| [2025-12-28T03:03:39.771Z] [INFO] | |
| π Auto PR creation: ENABLED | |
| [2025-12-28T03:03:39.771Z] [INFO] Creating: Initial commit and draft PR... | |
| [2025-12-28T03:03:39.771Z] [INFO] | |
| [2025-12-28T03:03:39.771Z] [INFO] π Creating: CLAUDE.md with task details | |
| [2025-12-28T03:03:39.771Z] [INFO] Issue URL from argv['issue-url']: https://github.com/link-assistant/market-research/issues/9 | |
| [2025-12-28T03:03:39.772Z] [INFO] Issue URL from argv._[0]: undefined | |
| [2025-12-28T03:03:39.772Z] [INFO] Final issue URL: https://github.com/link-assistant/market-research/issues/9 | |
| [2025-12-28T03:03:39.772Z] [INFO] β File created: CLAUDE.md | |
| [2025-12-28T03:03:39.772Z] [INFO] π¦ Adding file: To git staging | |
| [2025-12-28T03:03:39.797Z] [INFO] Git status after add: A CLAUDE.md | |
| [2025-12-28T03:03:39.797Z] [INFO] π Creating commit: With CLAUDE.md file | |
| [2025-12-28T03:03:39.812Z] [INFO] β Commit created: Successfully with CLAUDE.md | |
| [2025-12-28T03:03:39.813Z] [INFO] Commit output: [issue-9-fcb0cba15ea8 6968d2f] Initial commit with task details | |
| 1 file changed, 5 insertions(+) | |
| create mode 100644 CLAUDE.md | |
| [2025-12-28T03:03:39.825Z] [INFO] Commit hash: 6968d2f... | |
| [2025-12-28T03:03:39.837Z] [INFO] Latest commit: 6968d2f Initial commit with task details | |
| [2025-12-28T03:03:39.849Z] [INFO] Git status: clean | |
| [2025-12-28T03:03:39.861Z] [INFO] Remotes: origin https://github.com/link-assistant/market-research.git (fetch) | |
| [2025-12-28T03:03:39.873Z] [INFO] Branch info: * issue-9-fcb0cba15ea8 6968d2f Initial commit with task details | |
| main d6f6a66 [origin/main] Merge pull request #5 from link-assistant/issue-3-3509ef45146c | |
| [2025-12-28T03:03:39.873Z] [INFO] π€ Pushing branch: To remote repository... | |
| [2025-12-28T03:03:39.873Z] [INFO] Push command: git push -u origin issue-9-fcb0cba15ea8 | |
| [2025-12-28T03:03:40.674Z] [INFO] Push exit code: 0 | |
| [2025-12-28T03:03:40.674Z] [INFO] Push output: remote: | |
| remote: Create a pull request for 'issue-9-fcb0cba15ea8' on GitHub by visiting: | |
| remote: https://github.com/link-assistant/market-research/pull/new/issue-9-fcb0cba15ea8 | |
| remote: | |
| To https://github.com/link-assistant/market-research.git | |
| * [new branch] issue-9-fcb0cba15ea8 -> issue-9-fcb0cba15ea8 | |
| branch 'issue-9-fcb0cba15ea8' set up to track 'origin/issue-9-fcb0cba15ea8'. | |
| [2025-12-28T03:03:40.674Z] [INFO] β Branch pushed: Successfully to remote | |
| [2025-12-28T03:03:40.675Z] [INFO] Push output: remote: | |
| remote: Create a pull request for 'issue-9-fcb0cba15ea8' on GitHub by visiting: | |
| remote: https://github.com/link-assistant/market-research/pull/new/issue-9-fcb0cba15ea8 | |
| remote: | |
| To https://github.com/link-assistant/market-research.git | |
| * [new branch] issue-9-fcb0cba15ea8 -> issue-9-fcb0cba15ea8 | |
| branch 'issue-9-fcb0cba15ea8' set up to track 'origin/issue-9-fcb0cba15ea8'. | |
| [2025-12-28T03:03:40.675Z] [INFO] Waiting for GitHub to sync... | |
| [2025-12-28T03:03:43.080Z] [INFO] Compare API check: 1 commit(s) ahead of main | |
| [2025-12-28T03:03:43.080Z] [INFO] GitHub compare API ready: 1 commit(s) found | |
| [2025-12-28T03:03:43.404Z] [INFO] Branch verified on GitHub: issue-9-fcb0cba15ea8 | |
| [2025-12-28T03:03:43.680Z] [INFO] Remote commit SHA: 6968d2f... | |
| [2025-12-28T03:03:43.681Z] [INFO] π Getting issue: Title from GitHub... | |
| [2025-12-28T03:03:44.003Z] [INFO] Issue title: "Similar to other research documents we also need AI aggregator API gateways" | |
| [2025-12-28T03:03:44.004Z] [INFO] π€ Getting user: Current GitHub account... | |
| [2025-12-28T03:03:44.260Z] [INFO] Current user: konard | |
| [2025-12-28T03:03:44.511Z] [INFO] User has collaborator access | |
| [2025-12-28T03:03:44.511Z] [INFO] User has collaborator access | |
| [2025-12-28T03:03:44.512Z] [INFO] π Fetching: Latest main branch... | |
| [2025-12-28T03:03:44.795Z] [INFO] β Base updated: Fetched latest main | |
| [2025-12-28T03:03:44.795Z] [INFO] π Checking: Commits between branches... | |
| [2025-12-28T03:03:44.807Z] [INFO] Commits ahead of origin/main: 1 | |
| [2025-12-28T03:03:44.807Z] [INFO] β Commits found: 1 commit(s) ahead | |
| [2025-12-28T03:03:44.808Z] [INFO] π Creating PR: Draft pull request... | |
| [2025-12-28T03:03:44.808Z] [INFO] π― Target branch: main (default) | |
| [2025-12-28T03:03:44.808Z] [INFO] PR Title: [WIP] Similar to other research documents we also need AI aggregator API gateways | |
| [2025-12-28T03:03:44.808Z] [INFO] Base branch: main | |
| [2025-12-28T03:03:44.808Z] [INFO] Head branch: issue-9-fcb0cba15ea8 | |
| [2025-12-28T03:03:44.808Z] [INFO] Assignee: konard | |
| [2025-12-28T03:03:44.808Z] [INFO] PR Body: | |
| ## π€ AI-Powered Solution Draft | |
| This pull request is being automatically generated to solve issue #9. | |
| ### π Issue Reference | |
| Fixes #9 | |
| ### π§ Status | |
| **Work in Progress** - The AI assistant is currently analyzing and implementing the solution draft. | |
| ### π Implementation Details | |
| _Details will be added as the solution draft is developed..._ | |
| --- | |
| *This PR was created automatically by the AI issue solver* | |
| [2025-12-28T03:03:44.809Z] [INFO] Command: cd "/tmp/gh-issue-solver-1766891018916" && gh pr create --draft --title "$(cat '/tmp/pr-title-1766891024809.txt')" --body-file "/tmp/pr-body-1766891024809.md" --base main --head issue-9-fcb0cba15ea8 --assignee konard | |
| [2025-12-28T03:03:47.548Z] [INFO] π Verifying: PR creation... | |
| [2025-12-28T03:03:47.888Z] [INFO] β Verification: PR exists on GitHub | |
| [2025-12-28T03:03:47.889Z] [INFO] β PR created: #10 | |
| [2025-12-28T03:03:47.890Z] [INFO] π PR URL: https://github.com/link-assistant/market-research/pull/10 | |
| [2025-12-28T03:03:47.890Z] [INFO] π€ Assigned to: konard | |
| [2025-12-28T03:03:47.890Z] [INFO] π Linking: Issue #9 to PR #10... | |
| [2025-12-28T03:03:48.209Z] [INFO] Issue node ID: I_kwDOPLdrWM7gbYoV | |
| [2025-12-28T03:03:48.673Z] [INFO] PR node ID: PR_kwDOPLdrWM66uIEL | |
| [2025-12-28T03:03:49.012Z] [INFO] β Link verified: Issue #9 β PR #10 | |
| [2025-12-28T03:03:49.324Z] [INFO] π€ Current user: konard | |
| [2025-12-28T03:03:49.325Z] [INFO] | |
| π Comment counting conditions: | |
| [2025-12-28T03:03:49.325Z] [INFO] prNumber: 10 | |
| [2025-12-28T03:03:49.325Z] [INFO] branchName: issue-9-fcb0cba15ea8 | |
| [2025-12-28T03:03:49.325Z] [INFO] isContinueMode: false | |
| [2025-12-28T03:03:49.326Z] [INFO] Will count comments: true | |
| [2025-12-28T03:03:49.326Z] [INFO] π¬ Counting comments: Checking for new comments since last commit... | |
| [2025-12-28T03:03:49.326Z] [INFO] PR #10 on branch: issue-9-fcb0cba15ea8 | |
| [2025-12-28T03:03:49.326Z] [INFO] Owner/Repo: link-assistant/market-research | |
| [2025-12-28T03:03:49.678Z] [INFO] π Last commit time (from API): 2025-12-28T03:03:39.000Z | |
| [2025-12-28T03:03:50.699Z] [INFO] π¬ New PR comments: 0 | |
| [2025-12-28T03:03:50.700Z] [INFO] π¬ New issue comments: 0 | |
| [2025-12-28T03:03:50.700Z] [INFO] Total new comments: 0 | |
| [2025-12-28T03:03:50.701Z] [INFO] Comment lines to add: No (saving tokens) | |
| [2025-12-28T03:03:50.701Z] [INFO] PR review comments fetched: 0 | |
| [2025-12-28T03:03:50.701Z] [INFO] PR conversation comments fetched: 0 | |
| [2025-12-28T03:03:50.701Z] [INFO] Total PR comments checked: 0 | |
| [2025-12-28T03:03:53.080Z] [INFO] Feedback info will be added to prompt: | |
| [2025-12-28T03:03:53.081Z] [INFO] - Pull request description was edited after last commit | |
| [2025-12-28T03:03:53.081Z] [INFO] π Getting timestamps: From GitHub servers... | |
| [2025-12-28T03:03:53.373Z] [INFO] π Issue updated: 2025-12-28T03:03:15.000Z | |
| [2025-12-28T03:03:53.641Z] [INFO] π¬ Comments: None found | |
| [2025-12-28T03:03:53.946Z] [INFO] π Recent PR: 2025-12-28T03:03:46.000Z | |
| [2025-12-28T03:03:53.946Z] [INFO] | |
| β Reference time: 2025-12-28T03:03:46.000Z | |
| [2025-12-28T03:03:53.947Z] [INFO] | |
| π Checking for uncommitted changes to include as feedback... | |
| [2025-12-28T03:03:53.961Z] [INFO] β No uncommitted changes found | |
| [2025-12-28T03:03:53.965Z] [INFO] | |
| π Final prompt structure: | |
| [2025-12-28T03:03:53.966Z] [INFO] Characters: 281 | |
| [2025-12-28T03:03:53.966Z] [INFO] System prompt characters: 8495 | |
| [2025-12-28T03:03:53.966Z] [INFO] Feedback info: Included | |
| [2025-12-28T03:03:53.968Z] [INFO] | |
| π€ Executing Claude: OPUS | |
| [2025-12-28T03:03:53.969Z] [INFO] Model: opus | |
| [2025-12-28T03:03:53.969Z] [INFO] Working directory: /tmp/gh-issue-solver-1766891018916 | |
| [2025-12-28T03:03:53.969Z] [INFO] Branch: issue-9-fcb0cba15ea8 | |
| [2025-12-28T03:03:53.969Z] [INFO] Prompt length: 281 chars | |
| [2025-12-28T03:03:53.969Z] [INFO] System prompt length: 8495 chars | |
| [2025-12-28T03:03:53.969Z] [INFO] Feedback info included: Yes (1 lines) | |
| [2025-12-28T03:03:53.993Z] [INFO] π System resources before execution: | |
| [2025-12-28T03:03:53.993Z] [INFO] Memory: MemFree: 5449912 kB | |
| [2025-12-28T03:03:53.993Z] [INFO] Load: 0.49 0.25 0.21 1/771 1127750 | |
| [2025-12-28T03:03:53.994Z] [INFO] | |
| π Raw command: | |
| [2025-12-28T03:03:53.994Z] [INFO] (cd "/tmp/gh-issue-solver-1766891018916" && claude --output-format stream-json --verbose --dangerously-skip-permissions --model claude-opus-4-5-20251101 -p "Issue to solve: https://github.com/link-assistant/market-research/issues/9 | |
| Your prepared branch: issue-9-fcb0cba15ea8 | |
| Your prepared working directory: /tmp/gh-issue-solver-1766891018916 | |
| Your prepared Pull Request: https://github.com/link-assistant/market-research/pull/10 | |
| Proceed." --append-system-prompt "You are an AI issue solver. You prefer to find the root cause of each and every issue. When you talk, you prefer to speak with facts which you have double-checked yourself or cite sources that provide evidence, like quote actual code or give references to documents or pages found on the internet. You are polite and patient, and prefer to assume good intent, trying your best to be helpful. If you are unsure or have assumptions, you prefer to test them yourself or ask questions to clarify requirements. | |
| General guidelines. | |
| - When you execute commands, always save their logs to files for easier reading if the output becomes large. | |
| - When running commands, do not set a timeout yourself β let them run as long as needed (default timeout - 2 minutes is more than enough), and once they finish, review the logs in the file. | |
| - When running sudo commands (especially package installations like apt-get, yum, npm install, etc.), always run them in the background to avoid timeout issues and permission errors when the process needs to be killed. Use the run_in_background parameter or append & to the command. | |
| - When CI is failing or user reports failures, consider adding a detailed investigation protocol to your todo list with these steps: | |
| Step 1: List recent runs with timestamps using: gh run list --repo link-assistant/market-research --branch issue-9-fcb0cba15ea8 --limit 5 --json databaseId,conclusion,createdAt,headSha | |
| Step 2: Verify runs are after the latest commit by checking timestamps and SHA | |
| Step 3: For each non-passing run, download logs to preserve them: gh run view {run-id} --repo link-assistant/market-research --log > ci-logs/{workflow}-{run-id}.log | |
| Step 4: Read each downloaded log file using Read tool to understand the actual failures | |
| Step 5: Report findings with specific errors and line numbers from logs | |
| This detailed investigation is especially helpful when user mentions CI failures, asks to investigate logs, you see non-passing status, or when finalizing a PR. | |
| Note: If user says \"failing\" but tools show \"passing\", this might indicate stale data - consider downloading fresh logs and checking timestamps to resolve the discrepancy. | |
| - When a code or log file has more than 1500 lines, read it in chunks of 1500 lines. | |
| - When facing a complex problem, do as much tracing as possible and turn on all verbose modes. | |
| - When you create debug, test, or example/experiment scripts for fixing, always keep them in an examples and/or experiments folders so you can reuse them later. | |
| - When testing your assumptions, use the experiment scripts, and add it to experiments folder. | |
| - When your experiments can show real world use case of the software, add it to examples folder. | |
| - When you face something extremely hard, use divide and conquer β it always helps. | |
| Initial research. | |
| - When you start, make sure you create detailed plan for yourself and follow your todo list step by step, make sure that as many points from these guidelines are added to your todo list to keep track of everything that can help you solve the issue with highest possible quality. | |
| - When user mentions CI failures or asks to investigate logs, consider adding these todos to track the investigation: (1) List recent CI runs with timestamps, (2) Download logs from failed runs to ci-logs/ directory, (3) Analyze error messages and identify root cause, (4) Implement fix, (5) Verify fix resolves the specific errors found in logs. | |
| - When you read issue, read all details and comments thoroughly. | |
| - When you see screenshots or images in issue descriptions, pull request descriptions, comments, or discussions, use WebFetch tool (or fetch tool) to download the image first, then use Read tool to view and analyze it. | |
| - When you need issue details, use gh issue view https://github.com/link-assistant/market-research/issues/9. | |
| - When you need related code, use gh search code --owner link-assistant [keywords]. | |
| - When you need repo context, read files in your working directory. | |
| - When you study related work, study the most recent related pull requests. | |
| - When issue is not defined enough, write a comment to ask clarifying questions. | |
| - When accessing GitHub Gists (especially private ones), use gh gist view command instead of direct URL fetching to ensure proper authentication. | |
| - When you are fixing a bug, please make sure you first find the actual root cause, do as many experiments as needed. | |
| - When you are fixing a bug and code does not have enough tracing/logs, add them and make sure they stay in the code, but are switched off by default. | |
| - When you need latest comments on pull request (sorted newest first), use appropriate GitHub API commands. | |
| - When you need latest comments on issue (sorted newest first), use appropriate GitHub API commands. | |
| Solution development and testing. | |
| - When issue is solvable, implement code with tests. | |
| - When coding, each atomic step that can be useful by itself should be commited to the pull request's branch, meaning if work will be interrupted by any reason parts of solution will still be kept intact and safe in pull request. | |
| - When you test: | |
| start from testing of small functions using separate scripts; | |
| write unit tests with mocks for easy and quick start. | |
| - When you test integrations, use existing framework. | |
| - When you test solution draft, include automated checks in pr. | |
| - When issue is unclear, write comment on issue asking questions. | |
| - When you encounter any problems that you unable to solve yourself (any human feedback or help), write a comment to the pull request asking for help. | |
| - When you need human help, use gh pr comment 10 --body \"your message\" to comment on existing PR. | |
| Preparing pull request. | |
| - When you code, follow contributing guidelines. | |
| - When you commit, write clear message. | |
| - When you need examples of style, use gh pr list --repo link-assistant/market-research --state merged --search [keywords]. | |
| - When you open pr, describe solution draft and include tests. | |
| - When there is a package with version and GitHub Actions workflows for automatic release, update the version (or other necessary release trigger) in your pull request to prepare for next release. | |
| - When you update existing pr 10, use gh pr edit to modify title and description. | |
| - When you are about to commit or push code, ALWAYS run local CI checks first if they are available in contributing guidelines (like ruff check, mypy, eslint, etc.) to catch errors before pushing. | |
| - When you finalize the pull request: | |
| follow style from merged prs for code, title, and description, | |
| make sure no uncommitted changes corresponding to the original requirements are left behind, | |
| make sure the default branch is merged to the pull request's branch, | |
| make sure all CI checks passing if they exist before you finish, | |
| double-check that all changes in the pull request answer to original requirements of the issue, | |
| make sure no new new bugs are introduced in pull request by carefully reading gh pr diff, | |
| make sure no previously existing features were removed without an explicit request from users via the issue description, issue comments, and/or pull request comments. | |
| - When you finish implementation, use gh pr ready 10. | |
| Workflow and collaboration. | |
| - When you check branch, verify with git branch --show-current. | |
| - When you push, push only to branch issue-9-fcb0cba15ea8. | |
| - When you finish, create a pull request from branch issue-9-fcb0cba15ea8. (Note: PR 10 already exists, update it instead) | |
| - When you organize workflow, use pull requests instead of direct merges to default branch (main or master). | |
| - When you manage commits, preserve commit history for later analysis. | |
| - When you contribute, keep repository history forward-moving with regular commits, pushes, and reverts if needed. | |
| - When you face conflict that you cannot resolve yourself, ask for help. | |
| - When you collaborate, respect branch protections by working only on issue-9-fcb0cba15ea8. | |
| - When you mention result, include pull request url or comment url. | |
| - When you need to create pr, remember pr 10 already exists for this branch. | |
| Self review. | |
| - When you check your solution draft, run all tests locally. | |
| - When you compare with repo style, use gh pr diff [number]. | |
| - When you finalize, confirm code, tests, and description are consistent." | jq -c .) | |
| [2025-12-28T03:03:53.994Z] [INFO] | |
| [2025-12-28T03:03:53.994Z] [INFO] π User prompt: | |
| [2025-12-28T03:03:53.994Z] [INFO] ---BEGIN USER PROMPT--- | |
| [2025-12-28T03:03:53.994Z] [INFO] Issue to solve: https://github.com/link-assistant/market-research/issues/9 | |
| Your prepared branch: issue-9-fcb0cba15ea8 | |
| Your prepared working directory: /tmp/gh-issue-solver-1766891018916 | |
| Your prepared Pull Request: https://github.com/link-assistant/market-research/pull/10 | |
| Proceed. | |
| [2025-12-28T03:03:53.994Z] [INFO] ---END USER PROMPT--- | |
| [2025-12-28T03:03:53.995Z] [INFO] | |
| [2025-12-28T03:03:53.995Z] [INFO] π System prompt: | |
| [2025-12-28T03:03:53.995Z] [INFO] ---BEGIN SYSTEM PROMPT--- | |
| [2025-12-28T03:03:53.995Z] [INFO] You are an AI issue solver. You prefer to find the root cause of each and every issue. When you talk, you prefer to speak with facts which you have double-checked yourself or cite sources that provide evidence, like quote actual code or give references to documents or pages found on the internet. You are polite and patient, and prefer to assume good intent, trying your best to be helpful. If you are unsure or have assumptions, you prefer to test them yourself or ask questions to clarify requirements. | |
| General guidelines. | |
| - When you execute commands, always save their logs to files for easier reading if the output becomes large. | |
| - When running commands, do not set a timeout yourself β let them run as long as needed (default timeout - 2 minutes is more than enough), and once they finish, review the logs in the file. | |
| - When running sudo commands (especially package installations like apt-get, yum, npm install, etc.), always run them in the background to avoid timeout issues and permission errors when the process needs to be killed. Use the run_in_background parameter or append & to the command. | |
| - When CI is failing or user reports failures, consider adding a detailed investigation protocol to your todo list with these steps: | |
| Step 1: List recent runs with timestamps using: gh run list --repo link-assistant/market-research --branch issue-9-fcb0cba15ea8 --limit 5 --json databaseId,conclusion,createdAt,headSha | |
| Step 2: Verify runs are after the latest commit by checking timestamps and SHA | |
| Step 3: For each non-passing run, download logs to preserve them: gh run view {run-id} --repo link-assistant/market-research --log > ci-logs/{workflow}-{run-id}.log | |
| Step 4: Read each downloaded log file using Read tool to understand the actual failures | |
| Step 5: Report findings with specific errors and line numbers from logs | |
| This detailed investigation is especially helpful when user mentions CI failures, asks to investigate logs, you see non-passing status, or when finalizing a PR. | |
| Note: If user says "failing" but tools show "passing", this might indicate stale data - consider downloading fresh logs and checking timestamps to resolve the discrepancy. | |
| - When a code or log file has more than 1500 lines, read it in chunks of 1500 lines. | |
| - When facing a complex problem, do as much tracing as possible and turn on all verbose modes. | |
| - When you create debug, test, or example/experiment scripts for fixing, always keep them in an examples and/or experiments folders so you can reuse them later. | |
| - When testing your assumptions, use the experiment scripts, and add it to experiments folder. | |
| - When your experiments can show real world use case of the software, add it to examples folder. | |
| - When you face something extremely hard, use divide and conquer β it always helps. | |
| Initial research. | |
| - When you start, make sure you create detailed plan for yourself and follow your todo list step by step, make sure that as many points from these guidelines are added to your todo list to keep track of everything that can help you solve the issue with highest possible quality. | |
| - When user mentions CI failures or asks to investigate logs, consider adding these todos to track the investigation: (1) List recent CI runs with timestamps, (2) Download logs from failed runs to ci-logs/ directory, (3) Analyze error messages and identify root cause, (4) Implement fix, (5) Verify fix resolves the specific errors found in logs. | |
| - When you read issue, read all details and comments thoroughly. | |
| - When you see screenshots or images in issue descriptions, pull request descriptions, comments, or discussions, use WebFetch tool (or fetch tool) to download the image first, then use Read tool to view and analyze it. | |
| - When you need issue details, use gh issue view https://github.com/link-assistant/market-research/issues/9. | |
| - When you need related code, use gh search code --owner link-assistant [keywords]. | |
| - When you need repo context, read files in your working directory. | |
| - When you study related work, study the most recent related pull requests. | |
| - When issue is not defined enough, write a comment to ask clarifying questions. | |
| - When accessing GitHub Gists (especially private ones), use gh gist view command instead of direct URL fetching to ensure proper authentication. | |
| - When you are fixing a bug, please make sure you first find the actual root cause, do as many experiments as needed. | |
| - When you are fixing a bug and code does not have enough tracing/logs, add them and make sure they stay in the code, but are switched off by default. | |
| - When you need latest comments on pull request (sorted newest first), use appropriate GitHub API commands. | |
| - When you need latest comments on issue (sorted newest first), use appropriate GitHub API commands. | |
| Solution development and testing. | |
| - When issue is solvable, implement code with tests. | |
| - When coding, each atomic step that can be useful by itself should be commited to the pull request's branch, meaning if work will be interrupted by any reason parts of solution will still be kept intact and safe in pull request. | |
| - When you test: | |
| start from testing of small functions using separate scripts; | |
| write unit tests with mocks for easy and quick start. | |
| - When you test integrations, use existing framework. | |
| - When you test solution draft, include automated checks in pr. | |
| - When issue is unclear, write comment on issue asking questions. | |
| - When you encounter any problems that you unable to solve yourself (any human feedback or help), write a comment to the pull request asking for help. | |
| - When you need human help, use gh pr comment 10 --body "your message" to comment on existing PR. | |
| Preparing pull request. | |
| - When you code, follow contributing guidelines. | |
| - When you commit, write clear message. | |
| - When you need examples of style, use gh pr list --repo link-assistant/market-research --state merged --search [keywords]. | |
| - When you open pr, describe solution draft and include tests. | |
| - When there is a package with version and GitHub Actions workflows for automatic release, update the version (or other necessary release trigger) in your pull request to prepare for next release. | |
| - When you update existing pr 10, use gh pr edit to modify title and description. | |
| - When you are about to commit or push code, ALWAYS run local CI checks first if they are available in contributing guidelines (like ruff check, mypy, eslint, etc.) to catch errors before pushing. | |
| - When you finalize the pull request: | |
| follow style from merged prs for code, title, and description, | |
| make sure no uncommitted changes corresponding to the original requirements are left behind, | |
| make sure the default branch is merged to the pull request's branch, | |
| make sure all CI checks passing if they exist before you finish, | |
| double-check that all changes in the pull request answer to original requirements of the issue, | |
| make sure no new new bugs are introduced in pull request by carefully reading gh pr diff, | |
| make sure no previously existing features were removed without an explicit request from users via the issue description, issue comments, and/or pull request comments. | |
| - When you finish implementation, use gh pr ready 10. | |
| Workflow and collaboration. | |
| - When you check branch, verify with git branch --show-current. | |
| - When you push, push only to branch issue-9-fcb0cba15ea8. | |
| - When you finish, create a pull request from branch issue-9-fcb0cba15ea8. (Note: PR 10 already exists, update it instead) | |
| - When you organize workflow, use pull requests instead of direct merges to default branch (main or master). | |
| - When you manage commits, preserve commit history for later analysis. | |
| - When you contribute, keep repository history forward-moving with regular commits, pushes, and reverts if needed. | |
| - When you face conflict that you cannot resolve yourself, ask for help. | |
| - When you collaborate, respect branch protections by working only on issue-9-fcb0cba15ea8. | |
| - When you mention result, include pull request url or comment url. | |
| - When you need to create pr, remember pr 10 already exists for this branch. | |
| Self review. | |
| - When you check your solution draft, run all tests locally. | |
| - When you compare with repo style, use gh pr diff [number]. | |
| - When you finalize, confirm code, tests, and description are consistent. | |
| [2025-12-28T03:03:53.995Z] [INFO] ---END SYSTEM PROMPT--- | |
| [2025-12-28T03:03:53.995Z] [INFO] | |
| [2025-12-28T03:03:53.995Z] [INFO] π Command details: | |
| [2025-12-28T03:03:53.996Z] [INFO] π Working directory: /tmp/gh-issue-solver-1766891018916 | |
| [2025-12-28T03:03:53.996Z] [INFO] πΏ Branch: issue-9-fcb0cba15ea8 | |
| [2025-12-28T03:03:53.996Z] [INFO] π€ Model: Claude OPUS | |
| [2025-12-28T03:03:53.996Z] [INFO] | |
| βΆοΈ Streaming output: | |
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| [2025-12-28T03:04:14.763Z] [INFO] {"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01QAYTTBbq3yQZpPoc6hy8kz","type":"tool_result","content":" 1β# Agentic CLI Tools for Coding: A Comprehensive Guide\n 2β\n 3βThis guide provides a clear and concise comparison of agentic CLI tools for coding, tailored to help you choose the best tool for your needs. These tools allow you to write, edit, and manage code directly from the terminal using AI-powered assistance. Below, we evaluate leading toolsβClaude Code, Gemini CLI, OpenAI Codex CLI, Cline, Aider, Goose, OpenCode, Warp, Kiro CLI, Amazon Q Developer CLI, Qwen Code, Droid, Roo Code, and OpenHandsβfocusing on their support for advanced AI models, pricing, and key features. The analysis prioritizes fair pricing and open-source options where possible, ensuring you have the information needed to make an informed decision.\n 4β\n 5β### Key Points (Updated December 2025)\n 6β- **Claude Code** is Anthropic's terminal-based agentic coding tool with 49K GitHub stars, excelling in complex multi-file projects with deep codebase understanding, available via Pro ($20/month) and Max ($100-$200/month) plans.\n 7β- **Gemini CLI** from Google is the most starred CLI tool (88.5K stars) with an industry-leading free tier (1,000 requests/day) and access to Gemini 3 Flash with 1M token context.\n 8β- **OpenAI Codex CLI** is open-source (54.7K stars) with GPT-5.2-Codex as the default model, featuring new agent skills and GitHub/Linear integrations.\n 9β- **Cline** is GitHub's fastest-growing AI open source project (50K+ stars), offering Plan/Act modes and IDE integration.\n 10β- **Aider** is the pioneer open-source AI pair programmer with Git integration and support for virtually any LLM.\n 11β- **Goose** from Block (24.8K stars) is now part of the Linux Foundation's Agentic AI Foundation, offering fully local execution with any LLM.\n 12β- **OpenCode** (41K stars) is a truly open-source alternative to Claude Code with multi-session support and LSP-enabled architecture.\n 13β- **Warp** is an AI-native terminal with new Build plan ($20/month) and bring-your-own-key support.\n 14β- **Kiro CLI** from AWS reached general availability in November 2025 with spec-driven development and team features.\n 15β- **Amazon Q Developer CLI** integrates well with AWS, offering a free tier and a $19/month Pro plan.\n 16β- **Qwen Code** is Alibaba's open-source CLI optimized for Qwen3-Coder with 2,000 free requests/day via OAuth.\n 17β- **Droid by Factory** is #1 on Terminal-Bench with 58.75% score, offering multi-model orchestration.\n 18β- **Roo Code** (21.4K stars) provides multiple AI modes (Code, Architect, Debug, Ask) in VS Code.\n 19β- **OpenHands** is an open-source platform for autonomous AI software development with SDK, CLI, and GUI interfaces.\n 20β\n 21β### Why Choose an Agentic CLI Tool?\n 22βAgentic CLI tools are designed for developers who prefer working in the terminal, offering AI-driven assistance to generate code, fix bugs, and automate tasks. These tools understand your codebase, execute commands, and integrate with version control, making them ideal for efficient, hands-on coding workflows. Unlike passive autocomplete tools, an agentic CLI actively plans and executes multi-step tasks: reading your repository, generating or editing files, running tests, resolving Git history, and orchestrating shell commands through natural-language prompts.\n 23β\n 24β### Top Tools at a Glance\n 25β- **Claude Code**: Ideal for complex, multi-file projects requiring deep codebase understanding. Best terminal UX for rapid prototyping.\n 26β- **Gemini CLI**: Excellent for developers wanting generous free usage with massive context window (1M tokens) and Google Search integration. Best for large-context refactors.\n 27β- **OpenAI Codex CLI**: Great for cost-conscious users with GPT-5.2-Codex, agent skills, and deep GitHub/Linear integration.\n 28β- **Cline**: Suited for autonomous coding with IDE integration, Plan/Act modes, and strong community (fastest-growing on GitHub).\n 29β- **Aider**: Perfect for open-source enthusiasts who value Git integration and model flexibility.\n 30β- **Goose**: Ideal for developers wanting local execution with extensible agent capabilities and enterprise privacy.\n 31β- **OpenCode**: Best open-source alternative to Claude Code with multi-session support.\n 32β- **Warp**: Best for developers wanting an AI-native terminal experience with BYOK support.\n 33β- **Kiro CLI**: Great for teams using AWS services with spec-driven development and structured workflows.\n 34β- **Amazon Q Developer CLI**: Optimal for AWS users needing cloud-integrated tools.\n 35β- **Qwen Code**: Excellent for users wanting a free, open-source CLI with Qwen3-Coder's 256K context.\n 36β- **Droid**: Best for enterprise users needing top benchmark performance and multi-model orchestration.\n 37β\n 38β### How to Choose\n 39β- **If you're working on large projects**: Claude Code's robust features make it a strong choice.\n 40β- **If you want maximum free usage**: Gemini CLI offers 1,000 requests/day free with 1M token context.\n 41β- **If you need deep GitHub integration**: OpenAI Codex CLI with @codex mentions and agent skills.\n 42β- **If budget is a concern**: Gemini CLI, OpenAI Codex CLI, Aider, Cline, Goose, OpenCode, or Qwen Code offer free usage with API costs.\n 43β- **If you prefer local execution**: Goose runs entirely locally with any LLM.\n 44β- **If you want an AI-native terminal**: Warp provides a reimagined terminal experience with built-in agents.\n 45β- **If you use AWS**: Amazon Q Developer CLI or Kiro CLI provide seamless cloud integration.\n 46β- **If you need top benchmark performance**: Droid by Factory leads on Terminal-Bench.\n 47β\n 48β---\n 49β\n 50β# Comprehensive Analysis of Agentic CLI Tools (Updated December 2025)\n 51β\n 52βThis comprehensive analysis evaluates agentic CLI tools for coding, focusing on the most popular and capable tools available as of December 2025. These tools enable developers to generate, edit, and refactor code directly in the terminal using advanced AI models. The report assesses their support for the latest AI models, pricing, usage limits, and suitability for autonomous coding tasks. It emphasizes fair pricing and open-source options, providing a detailed guide for developers.\n 53β\n 54β## Background and Context\n 55βAgentic CLI tools are conversational, AI-driven tools that operate in the terminal, allowing developers to perform coding tasks such as code generation, debugging, and multi-file refactoring without leaving the command line. These tools leverage advanced AI models to understand codebases, execute commands, and integrate with version control systems like Git. The analysis prioritizes fair pricing and open-source options, ensuring alignment with the latest data as of December 2025.\n 56β\n 57β### Model Availability Summary (December 2025)\n 58β- **GPT-5 Series**: GPT-5 released August 7, 2025; GPT-5.1 released November 2025; GPT-5.2-Codex released December 2025. [Source](https://openai.com/index/introducing-gpt-5-2-codex/)\n 59β- **Claude 4 Series**: Claude Opus 4/Sonnet 4 released May 22, 2025; Opus 4.1 released August 2025; Sonnet 4.5 released September 2025; Opus 4.5 released November 24, 2025. [Source](https://www.anthropic.com/news/claude-opus-4-5)\n 60β- **Gemini 3 Series**: Gemini 3 Flash available in Gemini CLI since December 17, 2025, with 78% SWE-bench score. [Source](https://developers.googleblog.com/gemini-3-flash-is-now-available-in-gemini-cli/)\n 61β- **Grok 4**: Released July 9, 2025 via xAI API. [Source](https://x.ai/news/grok-4/)\n 62β- **Qwen3-Coder**: Alibaba's 480B parameter open-source coding model with 256K native context. [Source](https://qwenlm.github.io/blog/qwen3-coder/)\n 63β\n 64β## Methodology\n 65βThe research involved extensive web searches to verify the features, supported models, pricing, and usage limits of each agentic CLI tool. Official documentation, blogs, GitHub repositories, and community discussions were cross-referenced to ensure accuracy. GitHub star counts and recent releases were verified directly from source repositories.\n 66β\n 67β## Detailed Analysis of Agentic CLI Tools\n 68β\n 69β### Claude Code\n 70β- **Description**: Claude Code is Anthropic's terminal-based agentic coding tool with 49K GitHub stars, designed for complex software engineering tasks like code generation, debugging, and multi-file refactoring. It understands your entire codebase and helps you code faster by executing routine tasks, explaining complex code, and handling git workflows. [Source](https://github.com/anthropics/claude-code)\n 71β- **Agent Mode**: Maps entire codebases for deep understanding, executes tests, and integrates with GitHub Actions for automated workflows.\n 72β- **AI Model Support**: Directly supports Claude Sonnet 4, Sonnet 4.5, Opus 4, Opus 4.5, and older Claude models. Supports other providers via API configuration.\n 73β- **Key Features**:\n 74β - Automatic codebase context gathering for precise edits.\n 75β - Multi-file edits and test execution with high accuracy.\n 76β - CLAUDE.md files for project-specific instructions.\n 77β - WebSearch, WebFetch, and MultiEdit tools for enhanced functionality.\n 78β - LSP (Language Server Protocol) tool for code intelligence (v2.0.74+).\n 79β - Available in terminal, VS Code, JetBrains, and Slack.\n 80β- **Pricing**: Pro plan at $20/month (light usage, shared limits with Claude web/desktop); Max plans at $100/month (5x more than Pro) or $200/month (20x more than Pro) with access to Opus 4.5; API pricing at $3/$15 per million tokens (input/output) for Sonnet 4.5, $5/$25 for Opus 4.5 (67% reduction from Opus 4.1). [Source](https://www.anthropic.com/pricing)\n 81β- **Usage Limits**: Usage limits reset every five hours and are shared across Claude (web, desktop, mobile) and Claude Code. Weekly rate limits added August 2025 for heavy users.\n 82β- **Why It Fits**: Excels in complex, multi-file projects with deep codebase comprehension. Best for rapid prototypes and productive terminal UX.\n 83β\n 84β### Gemini CLI\n 85β- **Description**: Gemini CLI is Google's open-source (Apache 2.0) AI agent with 88.5K GitHub stars that brings the power of Gemini directly into your terminal. It uses a Reason and Act (ReAct) loop to complete complex use cases like fixing bugs, creating new features, and improving test coverage. [Source](https://github.com/google-gemini/gemini-cli)\n 86β- **Agent Mode**: Uses ReAct loop with built-in tools and MCP server support to complete complex tasks autonomously.\n 87β- **AI Model Support**: Uses Gemini 2.5 Pro by default; Gemini 3 Flash available since December 17, 2025 (78% SWE-bench Verified score). Gemini 3 Pro available for AI Ultra subscribers. [Source](https://developers.googleblog.com/gemini-3-flash-is-now-available-in-gemini-cli/)\n 88β- **Key Features**:\n 89β - Industry-leading free tier: 60 requests/minute, 1,000 requests/day.\n 90β - 1 million token context window for large codebase analysis.\n 91β - Built-in tools: Google Search grounding, file operations, shell commands, web fetching.\n 92β - Model Context Protocol (MCP) support for custom integrations.\n 93β - Multimodal: supports PDFs, images, and sketches.\n 94β - GitHub Actions integration for CI/CD workflows.\n 95β - Fully open-source (Apache 2.0).\n 96β- **Pricing**: Free tier with 1,000 requests/day. Google AI Pro at $19.99/month (5x limits). Google AI Ultra for intensive, multi-agent workflows (20x limits). Pay-as-you-go via Gemini API. Gemini 3 Flash at $0.50/$3 per million input/output tokens. [Source](https://geminicli.com/docs/quota-and-pricing/)\n 97β- **Usage Limits**: Free tier: 60 requests/minute, 1,000 requests/day. Paid tiers offer higher limits.\n 98β- **Why It Fits**: Best for large-context refactors with generous free tier and Google Search integration.\n 99β\n 100β### OpenAI Codex CLI\n 101β- **Description**: An open-source (Apache 2.0) command-line tool from OpenAI with 54.7K GitHub stars that brings reasoning models to the terminal, enabling local code reading, modification, and execution. Latest version 0.78.0. [Source](https://github.com/openai/codex)\n 102β- **Agent Mode**: Offers Suggest, Auto Edit, and Full Auto modes for task automation, including code generation, bug fixing, and test execution with sandboxed execution and approval workflows.\n 103β- **AI Model Support**: Default model is GPT-5.2-Codex (December 2025), the most advanced agentic coding model. Also supports GPT-5, GPT-5.1, o3, o4-mini. [Source](https://openai.com/index/introducing-gpt-5-2-codex/)\n 104β- **Key Features**:\n 105β - Agent Skills: reusable bundles of instructions ($skill-installer, $create-plan, etc.).\n 106β - Slash commands (/review, /plan) for specialized workflows.\n 107β - Multimodal inputs (text, screenshots, diagrams).\n 108β - AGENTS.md files for codebase navigation and standards.\n 109β - Sandboxed execution with approval workflows.\n 110β - GitHub integration: @codex mentions in PRs and Issues.\n 111β - Linear integration for task management.\n 112β - Model Context Protocol (MCP) support.\n 113β - Open-source (Apache 2.0 license) for customization.\n 114β- **Pricing**: Free to use; pay-as-you-go API pricing. [Source](https://openai.com/api/pricing/)\n 115β- **Usage Limits**: API usage-based.\n 116β- **Why It Fits**: Best for developers needing deep GitHub/Linear integration with GPT-5.2-Codex capabilities.\n 117β\n 118β### Cline\n 119β- **Description**: An open-source AI coding assistant with 50K+ GitHub stars, recognized as GitHub's fastest-growing AI open source project (4,704% YoY growth). Acts as an autonomous coding agent with Plan/Act modes. [Source](https://cline.bot/)\n 120β- **Agent Mode**: Supports planning and executing complex tasks, including multi-file edits and command execution with human-in-the-loop approval.\n 121β- **AI Model Support**: Model-agnostic, supporting Claude Sonnet 4/4.5, Opus 4/4.5, GPT-5, o3, o4-mini, Grok 4, and any API-compatible model. [Source](https://github.com/cline/cline)\n 122β- **Key Features**:\n 123β - Deep context understanding for accurate code changes.\n 124β - Permission-based file edits and command execution.\n 125β - Model Context Protocol (MCP) support for tool integration.\n 126β - Plan/Act modes for structured task execution.\n 127β - Browser capabilities for debugging and UI fixes.\n 128β - CLI extension (Beta) for scripts, cron jobs, and CI pipelines.\n 129β - Available for VS Code, JetBrains, and Cursor.\n 130β - Enterprise features: SSO, audit trails, private networking, self-hosted deployments.\n 131β- **Pricing**: Free to use; pay-as-you-go API pricing for chosen model. [Source](https://cline.bot/)\n 132β- **Usage Limits**: API usage-based.\n 133β- **Why It Fits**: Fastest-growing community with Plan/Act modes and enterprise-ready features.\n 134β\n 135β### Aider\n 136β- **Description**: An open-source CLI tool for AI pair programming in your terminal, supporting conversational prompting, multi-file edits, and Git-integrated workflows. One of the first open-source AI coding assistants. [Source](https://aider.chat/)\n 137β- **Agent Mode**: Features inline editing, multi-turn refinement, and task automation for collaborative coding. Architect/Editor mode for SOTA benchmark results.\n 138β- **AI Model Support**: Works best with Claude 4.1 Opus, DeepSeek V3, OpenAI GPT-5 and -4.1. Supports Grok-4, Gemini models. Can connect to almost any LLM, including local models. [Source](https://github.com/Aider-AI/aider)\n 139β- **Key Features**:\n 140β - Multi-file and multi-language support (Python, JavaScript, C++, etc.).\n 141β - Git-based code tracking with automatic commits and sensible messages.\n 142β - Conversational prompting for iterative refinements.\n 143β - Repository map for better context understanding.\n 144β - Image and web page support for visual context.\n 145β - Voice input support for hands-free coding.\n 146β - Automatic lint and test execution after changes.\n 147β - Shell completions for bash, zsh, etc.\n 148β - Optional web UI and VS Code extensions.\n 149β- **Pricing**: Free to use; pay-as-you-go API pricing for chosen model. [Source](https://aider.chat/)\n 150β- **Usage Limits**: API usage-based.\n 151β- **Why It Fits**: Best value CLI tool with optimized context fetching and pioneering Git integration.\n 152β\n 153β### Goose\n 154β- **Description**: An open-source (Apache 2.0), extensible AI agent from Block with 24.8K GitHub stars, now part of the Linux Foundation's Agentic AI Foundation (AAIF). Goes beyond code suggestionsβcan install, execute, edit, and test with any LLM. Runs entirely locally. [Source](https://github.com/block/goose)\n 155β- **Agent Mode**: Full autonomous agent capable of building entire projects from scratch, writing and executing code, debugging failures, orchestrating workflows, and interacting with external APIs.\n 156β- **AI Model Support**: Works with any language model that has tool calling capabilities, including DeepSeek, OpenAI models (GPT-5), Anthropic models (Claude Opus 4, Sonnet 4), Google models, and XAI models. [Source](https://block.github.io/goose/)\n 157β- **Key Features**:\n 158β - Fully local execution for privacy and control.\n 159β - Modular design with Model Context Protocol (MCP) support.\n 160β - Desktop app and CLI interfaces available.\n 161β - Extensible with custom tools and integrations (Jira, GitHub, etc.).\n 162β - Transparent operationβsee exactly what the agent is doing.\n 163β - Permission modes: Autonomous or Manual Approval.\n 164β - Agent Client Protocol (ACP) support for editor integration.\n 165β - Slash commands: /prompts, /prompt, /compact, /clear (December 2025).\n 166β - OpenRouter & XAI streaming support.\n 167β- **Pricing**: Free and open-source (Apache 2.0). API costs depend on chosen model provider. [Source](https://github.com/block/goose)\n 168β- **Usage Limits**: API usage-based depending on chosen model.\n 169β- **Why It Fits**: Ideal for developers wanting local execution, privacy, and extensible agent capabilities. Part of Linux Foundation AAIF.\n 170β\n 171β### OpenCode\n 172β- **Description**: An open-source AI coding agent with 41K GitHub stars, truly open-source alternative to Claude Code. Built by neovim users and creators of terminal.shop. [Source](https://github.com/sst/opencode)\n 173β- **Agent Mode**: Full agentic capabilities for multi-file editing, refactoring, and complex development tasks.\n 174β- **AI Model Support**: Supports any model via OpenAI, Anthropic, or local models like Ollama. [Source](https://opencode.ai/)\n 175β- **Key Features**:\n 176β - Multi-session support: multiple AI agents on same project without conflict.\n 177β - LSP-enabled architecture: auto-detects best tools for each language.\n 178β - Shareable sessions for debugging and collaboration.\n 179β - Deep project context: scans project files for dependencies.\n 180β - GitHub integration: /opencode or /oc mentions in comments.\n 181β - Desktop app and CLI interfaces.\n 182β - Haskell LSP support (December 2025).\n 183β- **Pricing**: Free and open-source. API costs depend on chosen model provider. [Source](https://opencode.ai/)\n 184β- **Usage Limits**: API usage-based.\n 185β- **Why It Fits**: Best open-source alternative to Claude Code with unique multi-session and LSP features.\n 186β\n 187β### Warp\n 188β- **Description**: Warp is an agentic development environmentβa reimagined terminal with AI agents built-in. Features Agent Mode, Warp Pair, and Dispatch Mode for different levels of autonomy. [Source](https://www.warp.dev/)\n 189β- **Agent Mode**: Agent Mode tackles multi-step tasks by executing commands with permission. Dispatch Mode operates fully autonomously. Warp Pair enables collaborative AI coding.\n 190β- **AI Model Support**: Access to Claude 3.5 Sonnet (default), Claude 3.5 Haiku, and GPT-4o. Enterprise controls for custom models. BYOK support for OpenAI, Anthropic, or Google models on Build plan. [Source](https://www.warp.dev/warp-ai)\n 191β- **Key Features**:\n 192β - Native terminal with AI agents built-in.\n 193β - Agent steering with code review and file editing support.\n 194β - WARP.md files (compatible with AGENTS.md, CLAUDE.md, cursor rules).\n 195β - MCP support and codebase embeddings.\n 196β - Privacy: No data used for model training, Zero Data Retention policies.\n 197β - Available on macOS, Linux, and Windows.\n 198β - Works with Zsh, Bash, fish, PowerShell, WSL, Git Bash.\n 199β- **Pricing**: Free tier with 75-150 credits/month. Build plan at $20/month with 1,500 credits and BYOK support. Business at $50/month with SSO and SOC 2 compliance. [Source](https://www.warp.dev/pricing)\n 200β- **Usage Limits**: Free: 75-150 credits/month. Build: 1,500 credits/month with rollover.\n 201β- **Why It Fits**: Best for developers wanting an AI-native terminal experience with BYOK flexibility.\n 202β\n 203β### Kiro CLI\n 204β- **Description**: Kiro CLI from AWS brings AI-powered development tools directly to the terminal. Generally available since November 2025 with 250,000+ developers. [Source](https://kiro.dev/cli/)\n 205β- **Agent Mode**: Full agentic capabilities for building features, automating workflows, analyzing errors, and suggesting fixes in an interactive loop. Spec-driven development framework.\n 206β- **AI M | |
| [2025-12-28T03:04:14.770Z] [INFO] odel Support**: Uses Claude Haiku 4.5, and Auto mode which balances performance, efficiency, and output quality. [Source](https://kiro.dev/blog/introducing-kiro-cli/)\n 207β- **Key Features**:\n 208β - Spec-driven development: plan, generate, and validate code through AI agents.\n 209β - Property-Based Testing (PBT) and Checkpointing.\n 210β - Custom agents for specialized tasks with pre-approved tool permissions.\n 211β - Seamless transfer of IDE configurations (MCP servers, steering rules).\n 212β - Native MCP support.\n 213β - Multi-root workspace support.\n 214β - Works with macOS and Linux.\n 215β - Available in US East (N. Virginia) and Europe (Frankfurt) regions.\n 216β- **Pricing**: Free tier with 500 bonus credits. Kiro Pro at $20/month, Kiro Pro+ at $40/month, Kiro Power at $200/month with increasing AI generation credits. Startup Credits Program available until December 31, 2025. [Source](https://kiro.dev/pricing/)\n 217β- **Usage Limits**: Credit-based; varies by tier and model selection.\n 218β- **Why It Fits**: Great for teams using AWS services with structured, spec-driven AI coding workflows.\n 219β\n 220β### Amazon Q Developer CLI\n 221β- **Description**: A CLI tool that enhances terminal workflows with AI-powered features like command autocompletion and natural language chat, integrated with AWS ecosystems. [Source](https://aws.amazon.com/q/developer/)\n 222β- **Agent Mode**: Supports multi-step tasks like debugging, code reviews, and structured development with session memory. Can upgrade to Kiro CLI for additional features.\n 223β- **AI Model Support**: Uses Claude Sonnet 4 (as of August 2025) for chat sessions. Through Amazon Bedrock, supports additional Claude models. [Source](https://aws.amazon.com/q/developer/)\n 224β- **Key Features**:\n 225β - Session-aware responses for multi-step tasks.\n 226β - CLI autocompletions and natural language-to-bash translation.\n 227β - AI chat in terminal (locally and over SSH).\n 228β - Strong AWS service integration for cloud workflows.\n 229β - Autonomous agents for feature implementation, refactoring, dependency upgrades.\n 230β - Cost estimation and optimization recommendations.\n 231β - Available in IDE, CLI, AWS Console, and Slack.\n 232β- **Pricing**: Free tier with 1,000 agentic chat interactions/month (from August 2025), 4,000 LOC/month for transformations. Pro tier at $19/month per user with higher limits. [Source](https://aws.amazon.com/q/developer/pricing/)\n 233β- **Usage Limits**: Free tier: 1,000 agentic interactions/month, 1,000 generative SQL queries/month. Pro tier offers higher limits.\n 234β- **Why It Fits**: Ideal for AWS users needing cloud-integrated CLI tools with generous free tier.\n 235β\n 236β### Qwen Code\n 237β- **Description**: An open-source AI agent from Alibaba optimized for Qwen3-Coder, adapted from Gemini CLI. Provides Claude Code-like experience with 2,000 free requests/day via OAuth. [Source](https://github.com/QwenLM/qwen-code)\n 238β- **Agent Mode**: Full agentic workflow with Skills, SubAgents, and Plan Mode.\n 239β- **AI Model Support**: Optimized for Qwen3-Coder-480B (480B parameters, 35B active with MoE). Supports 256K native context, 1M with extrapolation. State-of-the-art among open models for agentic coding. [Source](https://qwenlm.github.io/blog/qwen3-coder/)\n 240β- **Key Features**:\n 241β - Deep code understanding & editing beyond normal context windows.\n 242β - Workflow automation: PR handling, rebases, formatting.\n 243β - Enhanced parser optimized for Qwen-Coder models.\n 244β - Vision model support for multimodal analysis.\n 245β - OpenAI-compatible API.\n 246β - OAuth free tier: 2,000 requests/day.\n 247β - Terminal-first, IDE-friendly (VS Code, Zed integration).\n 248β - Fully open-source (both framework and model).\n 249β- **Pricing**: Free to use with OAuth (2,000 requests/day). OpenAI-compatible API available. [Source](https://github.com/QwenLM/qwen-code)\n 250β- **Usage Limits**: OAuth free tier: 2,000 requests/day.\n 251β- **Why It Fits**: Best free option with powerful open-source model and generous daily limits.\n 252β\n 253β### Droid by Factory\n 254β- **Description**: Enterprise-grade AI coding agent from Factory that lives in your terminal and handles end-to-end development workflows. #1 on Terminal-Bench with 58.75% score. [Source](https://factory.ai/news/terminal-bench)\n 255β- **Agent Mode**: Full autonomous agent with multi-model orchestration. Extracts more capability from each model than labs' own agents.\n 256β- **AI Model Support**: Supports Anthropic (Opus, Sonnet) and OpenAI (GPT-5) models. Droid with Opus (58.8%) beats Claude Code with Opus (43.2%). [Source](https://factory.ai/)\n 257β- **Key Features**:\n 258β - Multi-model support: switch between labs without switching tools.\n 259β - Specialized Droids: Knowledge, Reliability, Product agents.\n 260β - IDE integration: VS Code, JetBrains, Vim.\n 261β - Web interface, IDE extension, and CLI.\n 262β - CI/CD integration for migrations and maintenance.\n 263β - Automated code review and self-healing builds.\n 264β - Enterprise-grade with team features.\n 265β- **Pricing**: Free trial available. Enterprise pricing. [Source](https://factory.ai/)\n 266β- **Usage Limits**: Contact for enterprise limits.\n 267β- **Why It Fits**: Best for enterprises needing top benchmark performance and specialized agent types.\n 268β\n 269β### Roo Code\n 270β- **Description**: An open-source AI coding agent for VS Code with 21.4K GitHub stars, providing a whole dev team of AI agents in your code editor. Fork/derivation of Cline. [Source](https://github.com/RooCodeInc/Roo-Code)\n 271β- **Agent Mode**: Multiple modes (Code, Architect, Ask, Debug, Custom) for different development tasks. Supports multi-file edits, test execution, and browser control.\n 272β- **AI Model Support**: Fully customizable, integrating any AI model (OpenAI, Anthropic, local LLMs). [Source](https://roocode.com)\n 273β- **Key Features**:\n 274β - Multiple modes: Code, Architect, Ask, Debug, Custom.\n 275β - Sticky models: preserves stateful preferences per mode.\n 276β - Multi-file edits and refactoring.\n 277β - Test execution and browser control.\n 278β - Completely free and open-source.\n 279β - Privacy: code never leaves your machine unless you connect to external API.\n 280β - 901K installs on VS Code Marketplace.\n 281β- **Pricing**: Free and open-source. API costs depend on chosen model provider. [Source](https://roocode.com)\n 282β- **Usage Limits**: API usage-based.\n 283β- **Why It Fits**: Best for developers wanting multiple AI agent modes within VS Code.\n 284β\n 285β### OpenHands (formerly OpenDevin)\n 286β- **Description**: An open-source (MIT license) platform for AI-powered software development with SDK, CLI, and GUI interfaces. Creates autonomous AI agents that emulate human software developers. [Source](https://openhands.dev/)\n 287β- **Agent Mode**: Full autonomous agent capable of modifying code, executing commands, browsing the web, and interacting with APIs. Solves over 50% of real GitHub issues on SWE-bench.\n 288β- **AI Model Support**: Model-agnostic platform supporting Claude, GPT, and any LLM. [Source](https://github.com/OpenHands/OpenHands)\n 289β- **Key Features**:\n 290β - SDK: composable Python library for defining agents.\n 291β - CLI: Claude Code/Codex-like experience.\n 292β - Local GUI: React application with REST API.\n 293β - Cloud deployment: scale to 1000s of agents.\n 294β - Sandboxed environment for safe execution.\n 295β - $10 free credit for new users.\n 296β - Task management integrations: Jira, Linear.\n 297β- **Pricing**: Free and open-source (MIT license, except enterprise directory). $10 free credit. [Source](https://openhands.dev/)\n 298β- **Usage Limits**: API usage-based.\n 299β- **Why It Fits**: Best for developers wanting a complete platform for autonomous AI development with multiple interfaces.\n 300β\n 301β## Comparison Table\n 302β\n 303β| **CLI Tool** | **GitHub Stars** | **Open-Source** | **AI Model Support** | **Pricing** | **Free Tier** | **Key Strengths** | **Best For** |\n 304β|--------------|------------------|-----------------|----------------------|-------------|---------------|-------------------|--------------|\n 305β| **Claude Code** | 49K | No | Sonnet 4/4.5, Opus 4/4.5 | Pro $20/mo, Max $100-200/mo | No (Pro required) | Deep codebase understanding, multi-file edits, LSP support | Complex, multi-file projects |\n 306β| **Gemini CLI** | 88.5K | Yes (Apache 2.0) | Gemini 2.5 Pro, Gemini 3 Flash/Pro | Free, AI Pro $19.99/mo | Yes (1000 req/day) | Largest free tier, 1M token context, GitHub Actions | Large-context refactors |\n 307β| **OpenAI Codex CLI** | 54.7K | Yes (Apache 2.0) | GPT-5.2-Codex, GPT-5, o3, o4-mini | Free, API pay-as-you-go | Yes | Agent skills, GitHub/Linear integration | Deep GitHub integration |\n 308β| **Cline** | 50K+ | Yes | Any LLM (Sonnet 4, Opus 4, GPT-5, Grok 4) | Free, API pay-as-you-go | Yes | Plan/Act modes, fastest-growing, enterprise features | IDE-integrated autonomy |\n 309β| **Aider** | ~35K | Yes | Any LLM (Claude 4.1, GPT-5, Grok 4, local) | Free, API pay-as-you-go | Yes | Git integration, multi-language, voice input | Open-source Git workflows |\n 310β| **Goose** | 24.8K | Yes (Apache 2.0) | Any LLM with tool calling | Free, API pay-as-you-go | Yes | Local execution, AAIF member, ACP support | Privacy-focused, extensible |\n 311β| **OpenCode** | 41K | Yes | Any LLM (OpenAI, Anthropic, Ollama) | Free, API pay-as-you-go | Yes | Multi-session, LSP-enabled, shareable sessions | Claude Code alternative |\n 312β| **Warp** | N/A | No | Claude 3.5, GPT-4o, BYOK | Free, Build $20/mo | Yes (75-150 credits/mo) | AI-native terminal, BYOK, multi-platform | AI-native terminal experience |\n 313β| **Kiro CLI** | N/A | No | Claude Haiku 4.5, Auto mode | Free, Pro $20-200/mo | Yes (500 bonus) | Spec-driven development, AWS integration | AWS teams, structured workflows |\n 314β| **Amazon Q Developer CLI** | N/A | No | Claude Sonnet 4 via Bedrock | Free, Pro $19/mo | Yes (1000 interactions/mo) | AWS integration, cost optimization | AWS users, cloud workflows |\n 315β| **Qwen Code** | New | Yes (Apache 2.0) | Qwen3-Coder-480B (256K-1M context) | Free (2000 req/day OAuth) | Yes (2000 req/day) | Open-source model, vision support | Free usage, open models |\n 316β| **Droid** | N/A | No | Opus 4, Sonnet 4, GPT-5 | Free trial, Enterprise | Trial | #1 Terminal-Bench, multi-model | Enterprise, top performance |\n 317β| **Roo Code** | 21.4K | Yes | Any LLM (OpenAI, Anthropic, local) | Free, API pay-as-you-go | Yes | Multiple modes, VS Code integration | Multi-mode VS Code agent |\n 318β| **OpenHands** | N/A | Yes (MIT) | Any LLM (Claude, GPT) | Free ($10 credit), API | Yes ($10 credit) | SDK/CLI/GUI, 50%+ SWE-bench | Platform for AI dev |\n 319β\n 320β## Analysis and Recommendations\n 321β\n 322βBased on the evidence gathered in December 2025, all major tools support or can be configured to support the latest AI models. The market has seen significant consolidation around MCP (Model Context Protocol) and AGENTS.md standards.\n 323β\n 324β**Recommendations**:\n 325β- **For complex projects**: Choose **Claude Code** for its precision and deep codebase comprehension, starting at $20/month.\n 326β- **For maximum free usage**: Choose **Gemini CLI** for its industry-leading 1,000 requests/day free tier and 1M token context.\n 327β- **For open-source with GPT-5**: Choose **OpenAI Codex CLI** for agent skills and GitHub integration.\n 328β- **For fastest-growing community**: Choose **Cline** with 50K+ stars and enterprise features.\n 329β- **For Git-integrated workflows**: Choose **Aider** for automatic commits and flexible model support.\n 330β- **For local execution and privacy**: Choose **Goose** for fully local operation with any LLM.\n 331β- **For Claude Code alternative**: Choose **OpenCode** for multi-session support and LSP features.\n 332β- **For AI-native terminal**: Choose **Warp** for a reimagined terminal experience with BYOK.\n 333β- **For AWS users**: Choose **Amazon Q Developer CLI** or **Kiro CLI** for cloud-integrated coding.\n 334β- **For free open-source model**: Choose **Qwen Code** for 2,000 requests/day with Qwen3-Coder.\n 335β- **For top benchmark performance**: Choose **Droid by Factory** (#1 on Terminal-Bench).\n 336β- **For multi-mode IDE agent**: Choose **Roo Code** for Code/Architect/Debug/Ask modes.\n 337β- **For complete AI dev platform**: Choose **OpenHands** for SDK, CLI, and GUI interfaces.\n 338β\n 339β## References\n 340β\n 341βFor further details, explore the official documentation:\n 342β- [Claude Code](https://github.com/anthropics/claude-code)\n 343β- [Gemini CLI](https://github.com/google-gemini/gemini-cli)\n 344β- [OpenAI Codex CLI](https://github.com/openai/codex)\n 345β- [Cline](https://cline.bot/)\n 346β- [Aider](https://aider.chat/)\n 347β- [Goose](https://github.com/block/goose)\n 348β- [OpenCode](https://opencode.ai/)\n 349β- [Warp](https://www.warp.dev/)\n 350β- [Kiro CLI](https://kiro.dev/cli/)\n 351β- [Amazon Q Developer CLI](https://aws.amazon.com/q/developer/)\n 352β- [Qwen Code](https://github.com/QwenLM/qwen-code)\n 353β- [Factory Droid](https://factory.ai/)\n 354β- [Roo Code](https://roocode.com/)\n 355β- [OpenHands](https://openhands.dev/)\n 356β\n 357β### Additional Sources\n 358β- [GPT-5.2-Codex Announcement](https://openai.com/index/introducing-gpt-5-2-codex/)\n 359β- [Claude Opus 4.5 Announcement](https://www.anthropic.com/news/claude-opus-4-5)\n 360β- [Gemini 3 Flash in Gemini CLI](https://developers.googleblog.com/gemini-3-flash-is-now-available-in-gemini-cli/)\n 361β- [Grok 4 Announcement](https://x.ai/news/grok-4/)\n 362β- [Qwen3-Coder Announcement](https://qwenlm.github.io/blog/qwen3-coder/)\n 363β- [Agentic AI Foundation (Linux Foundation)](https://www.linuxfoundation.org/press/linux-foundation-announces-the-formation-of-the-agentic-ai-foundation)\n 364β- [Droid Terminal-Bench Results](https://factory.ai/news/terminal-bench)\n 365β- [Cline Fastest Growing AI Project](https://cline.bot/blog/cline-the-fastest-growing-ai-open-source-project-on-github-in-2025-thanks-to-you)\n 366β- [Claude Pricing](https://www.anthropic.com/pricing)\n 367β- [Gemini CLI Pricing](https://geminicli.com/docs/quota-and-pricing/)\n 368β- [Amazon Q Developer Pricing](https://aws.amazon.com/q/developer/pricing/)\n 369β- [Kiro Pricing](https://kiro.dev/pricing/)\n 370β- [Warp Pricing](https://www.warp.dev/pricing)\n 371β\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n"}]},"parent_tool_use_id":null,"session_id":"37701ccf-99c0-4955-a30f-f61eb4145748","uuid":"68e6244b-8dc3-4206-ad88-60584f3a3a93","tool_use_result":{"type":"text","file":{"filePath":"/tmp/gh-issue-solver-1766891018916/ai-agentic-cli-tools.md","content":"# Agentic CLI Tools for Coding: A Comprehensive Guide\n\nThis guide provides a clear and concise comparison of agentic CLI tools for coding, tailored to help you choose the best tool for your needs. These tools allow you to write, edit, and manage code directly from the terminal using AI-powered assistance. Below, we evaluate leading toolsβClaude Code, Gemini CLI, OpenAI Codex CLI, Cline, Aider, Goose, OpenCode, Warp, Kiro CLI, Amazon Q Developer CLI, Qwen Code, Droid, Roo Code, and OpenHandsβfocusing on their support for advanced AI models, pricing, and key features. The analysis prioritizes fair pricing and open-source options where possible, ensuring you have the information needed to make an informed decision.\n\n### Key Points (Updated December 2025)\n- **Claude Code** is Anthropic's terminal-based agentic coding tool with 49K GitHub stars, excelling in complex multi-file projects with deep codebase understanding, available via Pro ($20/month) and Max ($100-$200/month) plans.\n- **Gemini CLI** from Google is the most starred CLI tool (88.5K stars) with an industry-leading free tier (1,000 requests/day) and access to Gemini 3 Flash with 1M token context.\n- **OpenAI Codex CLI** is open-source (54.7K stars) with GPT-5.2-Codex as the default model, featuring new agent skills and GitHub/Linear integrations.\n- **Cline** is GitHub's fastest-growing AI open source project (50K+ stars), offering Plan/Act modes and IDE integration.\n- **Aider** is the pioneer open-source AI pair programmer with Git integration and support for virtually any LLM.\n- **Goose** from Block (24.8K stars) is now part of the Linux Foundation's Agentic AI Foundation, offering fully local execution with any LLM.\n- **OpenCode** (41K stars) is a truly open-source alternative to Claude Code with multi-session support and LSP-enabled architecture.\n- **Warp** is an AI-native terminal with new Build plan ($20/month) and bring-your-own-key support.\n- **Kiro CLI** from AWS reached general availability in November 2025 with spec-driven development and team features.\n- **Amazon Q Developer CLI** integrates well with AWS, offering a free tier and a $19/month Pro plan.\n- **Qwen Code** is Alibaba's open-source CLI optimized for Qwen3-Coder with 2,000 free requests/day via OAuth.\n- **Droid by Factory** is #1 on Terminal-Bench with 58.75% score, offering multi-model orchestration.\n- **Roo Code** (21.4K stars) provides multiple AI modes (Code, Architect, Debug, Ask) in VS Code.\n- **OpenHands** is an open-source platform for autonomous AI software development with SDK, CLI, and GUI interfaces.\n\n### Why Choose an Agentic CLI Tool?\nAgentic CLI tools are designed for developers who prefer working in the terminal, offering AI-driven assistance to generate code, fix bugs, and automate tasks. These tools understand your codebase, execute commands, and integrate with version control, making them ideal for efficient, hands-on coding workflows. Unlike passive autocomplete tools, an agentic CLI actively plans and executes multi-step tasks: reading your repository, generating or editing files, running tests, resolving Git history, and orchestrating shell commands through natural-language prompts.\n\n### Top Tools at a Glance\n- **Claude Code**: Ideal for complex, multi-file projects requiring deep codebase understanding. Best terminal UX for rapid prototyping.\n- **Gemini CLI**: Excellent for developers wanting generous free usage with massive context window (1M tokens) and Google Search integration. Best for large-context refactors.\n- **OpenAI Codex CLI**: Great for cost-conscious users with GPT-5.2-Codex, agent skills, and deep GitHub/Linear integration.\n- **Cline**: Suited for autonomous coding with IDE integration, Plan/Act modes, and strong community (fastest-growing on GitHub).\n- **Aider**: Perfect for open-source enthusiasts who value Git integration and model flexibility.\n- **Goose**: Ideal for developers wanting local execution with extensible agent capabilities and enterprise privacy.\n- **OpenCode**: Best open-source alternative to Claude Code with multi-session support.\n- **Warp**: Best for developers wanting an AI-native terminal experience with BYOK support.\n- **Kiro CLI**: Great for teams using AWS services with spec-driven development and structured workflows.\n- **Amazon Q Developer CLI**: Optimal for AWS users needing cloud-integrated tools.\n- **Qwen Code**: Excellent for users wanting a free, open-source CLI with Qwen3-Coder's 256K context.\n- **Droid**: Best for enterprise users needing top benchmark performance and multi-model orchestration.\n\n### How to Choose\n- **If you're working on large projects**: Claude Code's robust features make it a strong choice.\n- **If you want maximum free usage**: Gemini CLI offers 1,000 requests/day free with 1M token context.\n- **If you need deep GitHub integration**: OpenAI Codex CLI with @codex mentions and agent skills.\n- **If budget is a concern**: Gemini CLI, OpenAI Codex CLI, Aider, Cline, Goose, OpenCode, or Qwen Code offer free usage with API costs.\n- **If you prefer local execution**: Goose runs entirely locally with any LLM.\n- **If you want an AI-native terminal**: Warp provides a reimagined terminal experience with built-in agents.\n- **If you use AWS**: Amazon Q Developer CLI or Kiro CLI provide seamless cloud integration.\n- **If you need top benchmark performance**: Droid by Factory leads on Terminal-Bench.\n\n---\n\n# Comprehensive Analysis of Agentic CLI Tools (Updated December 2025)\n\nThis comprehensive analysis evaluates agentic CLI tools for coding, focusing on the most popular and capable tools available as of December 2025. These tools enable developers to generate, edit, and refactor code directly in the terminal using advanced AI models. The report assesses their support for the latest AI models, pricing, usage limits, and suitability for autonomous coding tasks. It emphasizes fair pricing and open-source options, providing a detailed guide for developers.\n\n## Background and Context\nAgentic CLI tools are conversational, AI-driven tools that operate in the terminal, allowing developers to perform coding tasks such as code generation, debugging, and multi-file refactoring without leaving the command line. These tools leverage advanced AI models to understand codebases, execute commands, and integrate with version control systems like Git. The analysis prioritizes fair pricing and open-source options, ensuring alignment with the latest data as of December 2025.\n\n### Model Availability Summary (December 2025)\n- **GPT-5 Series**: GPT-5 released August 7, 2025; GPT-5.1 released November 2025; GPT-5.2-Codex released December 2025. [Source](https://openai.com/index/introducing-gpt-5-2-codex/)\n- **Claude 4 Series**: Claude Opus 4/Sonnet 4 released May 22, 2025; Opus 4.1 released August 2025; Sonnet 4.5 released September 2025; Opus 4.5 released November 24, 2025. [Source](https://www.anthropic.com/news/claude-opus-4-5)\n- **Gemini 3 Series**: Gemini 3 Flash available in Gemini CLI since December 17, 2025, with 78% SWE-bench score. [Source](https://developers.googleblog.com/gemini-3-flash-is-now-available-in-gemini-cli/)\n- **Grok 4**: Released July 9, 2025 via xAI API. [Source](https://x.ai/news/grok-4/)\n- **Qwen3-Coder**: Alibaba's 480B parameter open-source coding model with 256K native context. [Source](https://qwenlm.github.io/blog/qwen3-coder/)\n\n## Methodology\nThe research involved extensive web searches to verify the features, supported models, pricing, and usage limits of each agentic CLI tool. Official documentation, blogs, GitHub repositories, and community discussions were cross-referenced to ensure accuracy. GitHub star counts and recent releases were verified directly from source repositories.\n\n## Detailed Analysis of Agentic CLI Tools\n\n### Claude Code\n- **Description**: Claude Code is Anthropic's terminal-based agentic coding tool with 49K GitHub stars, designed for complex software engineering tasks like code generation, debugging, and multi-file refactoring. It understands your entire codebase and helps you code faster by executing routine tasks, explaining complex code, and handling git workflows. [Source](https://github.com/anthropics/claude-code)\n- **Agent Mode**: Maps entire codebases for deep understanding, executes tests, and integrates with GitHub Actions for automated workflows.\n- **AI Model Support**: Directly supports Claude Sonnet 4, Sonnet 4.5, Opus 4, Opus 4.5, and older Claude models. Supports other providers via API configuration.\n- **Key Features**:\n - Automatic codebase context gathering for precise edits.\n - Multi-file edits and test execution with high accuracy.\n - CLAUDE.md files for project-specific instructions.\n - WebSearch, WebFetch, and MultiEdit tools for enhanced functionality.\n - LSP (Language Server Protocol) tool for code intelligence (v2.0.74+).\n - Available in terminal, VS Code, JetBrains, and Slack.\n- **Pricing**: Pro plan at $20/month (light usage, shared limits with Claude web/desktop); Max plans at $100/month (5x more than Pro) or $200/month (20x more than Pro) with access to Opus 4.5; API pricing at $3/$15 per million tokens (input/output) for Sonnet 4.5, $5/$25 for Opus 4.5 (67% reduction from Opus 4.1). [Source](https://www.anthropic.com/pricing)\n- **Usage Limits**: Usage limits reset every five hours and are shared across Claude (web, desktop, mobile) and Claude Code. Weekly rate limits added August 2025 for heavy users.\n- **Why It Fits**: Excels in complex, multi-file projects with deep codebase comprehension. Best for rapid prototypes and productive terminal UX.\n\n### Gemini CLI\n- **Description**: Gemini CLI is Google's open-source (Apache 2.0) AI agent with 88.5K GitHub stars that brings the power of Gemini directly into your terminal. It uses a Reason and Act (ReAct) loop to complete complex use cases like fixing bugs, creating new features, and improving test coverage. [Source](https://github.com/google-gemini/gemini-cli)\n- **Agent Mode**: Uses ReAct loop with built-in tools and MCP server support to complete complex tasks autonomously.\n- **AI Model Support**: Uses Gemini 2.5 Pro by default; Gemini 3 Flash available since December 17, 2025 (78% SWE-bench Verified score). Gemini 3 Pro available for AI Ultra subscribers. [Source](https://developers.googleblog.com/gemini-3-flash-is-now-available-in-gemini-cli/)\n- **Key Features**:\n - Industry-leading free tier: 60 requests/minute, 1,000 requests/day.\n - 1 million token context window for large codebase analysis.\n - Built-in tools: Google Search grounding, file operations, shell commands, web fetching.\n - Model Context Protocol (MCP) support for custom integrations.\n - Multimodal: supports PDFs, images, and sketches.\n - GitHub Actions integration for CI/CD workflows.\n - Fully open-source (Apache 2.0).\n- **Pricing**: Free tier with 1,000 requests/day. Google AI Pro at $19.99/month (5x limits). Google AI Ultra for intensive, multi-agent workflows (20x limits). Pay-as-you-go via Gemini API. Gemini 3 Flash at $0.50/$3 per million input/output tokens. [Source](https://geminicli.com/docs/quota-and-pricing/)\n- **Usage Limits**: Free tier: 60 requests/minute, 1,000 requests/day. Paid tiers offer higher limits.\n- **Why It Fits**: Best for large-context refactors with generous free tier and Google Search integration.\n\n### OpenAI Codex CLI\n- **Description**: An open-source (Apache 2.0) command-line tool from OpenAI with 54.7K GitHub stars that brings reasoning models to the terminal, enabling local code reading, modification, and execution. Latest version 0.78.0. [Source](https://github.com/openai/codex)\n- **Agent Mode**: Offers Suggest, Auto Edit, and Full Auto modes for task automation, including code generation, bug fixing, and test execution with sandboxed execution and approval workflows.\n- **AI Model Support**: Default model is GPT-5.2-Codex (December 2025), the most advanced agentic coding model. Also supports GPT-5, GPT-5.1, o3, o4-mini. [Source](https://openai.com/index/introducing-gpt-5-2-codex/)\n- **Key Features**:\n - Agent Skills: reusable bundles of instructions ($skill-installer, $create-plan, etc.).\n - Slash commands (/review, /plan) for specialized workflows.\n - Multimodal inputs (text, screenshots, diagrams).\n - AGENTS.md files for codebase navigation and standards.\n - Sandboxed execution with approval workflows.\n - GitHub integration: @codex mentions in PRs and Issues.\n - Linear integration for task management.\n - Model Context Protocol (MCP) support.\n - Open-source (Apache 2.0 license) for customization.\n- **Pricing**: Free to use; pay-as-you-go API pricing. [Source](https://openai.com/api/pricing/)\n- **Usage Limits**: API usage-based.\n- **Why It Fits**: Best for developers needing deep GitHub/Linear integration with GPT-5.2-Codex capabilities.\n\n### Cline\n- **Description**: An open-source AI coding assistant with 50K+ GitHub stars, recognized as GitHub's fastest-growing AI open source project (4,704% YoY growth). Acts as an autonomous coding agent with Plan/Act modes. [Source](https://cline.bot/)\n- **Agent Mode**: Supports planning and executing complex tasks, including multi-file edits and command execution with human-in-the-loop approval.\n- **AI Model Support**: Model-agnostic, supporting Claude Sonnet 4/4.5, Opus 4/4.5, GPT-5, o3, o4-mini, Grok 4, and any API-compatible model. [Source](https://github.com/cline/cline)\n- **Key Features**:\n - Deep context understanding for accurate code changes.\n - Permission-based file edits and command execution.\n - Model Context Protocol (MCP) support for tool integration.\n - Plan/Act modes for structured task execution.\n - Browser capabilities for debugging and UI fixes.\n - CLI extension (Beta) for scripts, cron jobs, and CI pipelines.\n - Available for VS Code, JetBrains, and Cursor.\n - Enterprise features: SSO, audit trails, private networking, self-hosted deployments.\n- **Pricing**: Free to use; pay-as-you-go API pricing for chosen model. [Source](https://cline.bot/)\n- **Usage Limits**: API usage-based.\n- **Why It Fits**: Fastest-growing community with Plan/Act modes and enterprise-ready features.\n\n### Aider\n- **Description**: An open-source CLI tool for AI pair programming in your terminal, supporting conversational prompting, multi-file edits, and Git-integrated workflows. One of the first open-source AI coding assistants. [Source](https://aider.chat/)\n- **Agent Mode**: Features inline editing, multi-turn refinement, and task automation for collaborative coding. Architect/Editor mode for SOTA benchmark results.\n- **AI Model Support**: Works best with Claude 4.1 Opus, DeepSeek V3, OpenAI GPT-5 and -4.1. Supports Grok-4, Gemini models. Can connect to almost any LLM, including local models. [Source](https://github.com/Aider-AI/aider)\n- **Key Features**:\n - Multi-file and multi-language support (Python, JavaScript, C++, etc.).\n - Git-based code tracking with automatic commits and sensible messages.\n - Conversational prompting for iterative refinements.\n - Repository map for better context understanding.\n - Image and web page support for visual context.\n - Voice input support for hands-free coding.\n - Automatic lint and test execution after changes.\n - Shell completions for bash, zsh, etc.\n - Optional web UI and VS Code extensions.\n- **Pricing**: Free to use; pay-as-you-go API pricing for chosen model. [Source](https://aider.chat/)\n- **Usage Limits**: API usage-based.\n- **Why It Fits**: Best value CLI tool with optimized context fetching and pioneering Git integration.\n\n### Goose\n- **Description**: An open-source (Apache 2.0), extensible AI agent from Block with 24.8K GitHub stars, now part of the Linux Foundation's Agentic AI Foundation (AAIF). Goes beyond code suggestionsβcan install, execute, edit, and test with any LLM. Runs entirely locally. [Source](https://github.com/block/goose)\n- **Agent Mode**: Full autonomous agent capable of building entire projects from scratch, writing and executing code, debugging failures, orchestrating workflows, and interacting with external APIs.\n- **AI Model Support**: Works with any language model that has tool calling capabilities, including DeepSeek, OpenAI models (GPT-5), Anthropic models (Claude Opus 4, Sonnet 4), Google models, and XAI models. [Source](https://block.github.io/goose/)\n- **Key Features**:\n - Fully local execution for privacy and control.\n - Modular design with Model Context Protocol (MCP) support.\n - Desktop app and CLI interfaces available.\n - Extensible with custom tools and integrations (Jira, GitHub, etc.).\n - Transparent operationβsee exactly what the agent is doing.\n - Permission modes: Autonomous or Manual Approval.\n - Agent Client Protocol (ACP) support for editor integration.\n - Slash commands: /prompts, /prompt, /compact, /clear (December 2025).\n - OpenRouter & XAI streaming support.\n- **Pricing**: Free and open-source (Apache 2.0). API costs depend on chosen model provider. [Source](https://github.com/block/goose)\n- **Usage Limits**: API usage-based depending on chosen model.\n- **Why It Fits**: Ideal for developers wanting local execution, privacy, and extensible agent capabilities. Part of Linux Foundation AAIF.\n\n### OpenCode\n- **Description**: An open-source AI coding agent with 41K GitHub stars, truly open-source alternative to Claude Code. Built by neovim users and creators of terminal.shop. [Source](https://github.com/sst/opencode)\n- **Agent Mode**: Full agentic capabilities for multi-file editing, refactoring, and complex development tasks.\n- **AI Model Support**: Supports any model via OpenAI, Anthropic, or local models like Ollama. [Source](https://opencode.ai/)\n- **Key Features**:\n - Multi-session support: multiple AI agents on same project without conflict.\n - LSP-enabled architecture: auto-detects best tools for each language.\n - Shareable sessions for debugging and collaboration.\n - Deep project context: scans project files for dependencies.\n - GitHub integration: /opencode or /oc mentions in comments.\n - Desktop app and CLI interfaces.\n - Haskell LSP support (December 2025).\n- **Pricing**: Free and open-source. API costs depend on chosen model provider. [Source](https://opencode.ai/)\n- **Usage Limits**: API usage-based.\n- **Why It Fits**: Best open-source alternative to Claude Code with unique multi-session and LSP features.\n\n### Warp\n- **Description**: Warp is an agentic development environmentβa reimagined terminal with AI agents built-in. Features Agent Mode, Warp Pair, and Dispatch Mode for different levels of autonomy. [Source](https://www.warp.dev/)\n- **Agent Mode**: Agent Mode tackles multi-step tasks by executing commands with permission. Dispatch Mode operates fully autonomously. Warp Pair enables collaborative AI coding.\n- **AI Model Support**: Access to Claude 3.5 Sonnet (default), Claude 3.5 Haiku, and GPT-4o. Enterprise controls for custom models. BYOK support for OpenAI, Anthropic, or Google models on Build plan. [Source](https://www.warp.dev/warp-ai)\n- **Key Features**:\n - Native terminal with AI agents built-in.\n - Agent steering with code review and file editing support.\n - WARP.md files (compatible with AGENTS.md, CLAUDE.md, cursor rules).\n - MCP support and codebase embeddings.\n - Privacy: No data used for model training, Zero Data Retention policies.\n - Available on macOS, Linux, and Windows.\n - Works with Zsh, Bash, fish, PowerShell, WSL, Git Bash.\n- **Pricing**: Free tier with 75-150 credits/month. Build plan at $20/month with 1,500 credits and BYOK support. Business at $50/month with SSO and SOC 2 compliance. [Source](https://www.warp.dev/pricing)\n- **Usage Limits**: Free: 75-150 credits/month. Build: 1,500 credits/month with rollover.\n- **Why It Fits**: Best for developers wanting an AI-native terminal experience with BYOK flexibility.\n\n### Kiro CLI\n- **Description**: Kiro CLI from AWS brings AI-powered development tools directly to the terminal. Generally available since November 2025 with 250,000+ developers. [Source](https://kiro.dev/cli/)\n- **Agent Mode**: Full agentic capabilities for building features, automating workflows, analyzing errors, and suggesting fixes in an interactive loop. Spec-driven development framework.\n- **AI Model Support**: Uses Claude Haiku 4.5, and Auto mode which balances performance, efficiency, and output quality. [Source](https://kiro.dev/blog/introducing-kiro-cli/)\n- **Key Features**:\n - Spec-driven development: plan, generate, and validate code through AI agents.\n - Property-Based Testing (PBT) and Checkpointing.\n - Custom agents for specialized tasks with pre-approved tool permissions.\n - Seamless transfer of IDE configurations (MCP servers, steering rules).\n - Native MCP support.\n - Multi-root workspace support.\n - Works with macOS and Linux.\n - Available in US East (N. Virginia) and Europe (Frankfurt) regions.\n- **Pricing**: Free tier with 500 bonus credits. Kiro Pro at $20/month, Kiro Pro+ at $40/month, Kiro Power at $200/month with increasing AI generation credits. Startup Credits Program available until December 31, 2025. [Source](https://kiro.dev/pricing/)\n- **Usage Limits**: Credit-based; varies by tier and model selection.\n- **Why It Fits**: Great for teams using AWS services with structured, spec-driven AI coding workflows.\n\n### Amazon Q Developer CLI\n- **Description**: A CLI tool that enhances terminal workflows with AI-powered features like command autocompletion and natural language chat, integrated with AWS ecosystems. [Source](https://aws.amazon.com/q/developer/)\n- **Agent Mode**: Supports multi-step tasks like debugging, code reviews, and structured development with session memory. Can upgrade to Kiro CLI for additional features.\n- **AI Model Support**: Uses Claude Sonnet 4 (as of August 2025) for chat sessions. Through Amazon Bedrock, supports additional Claude models. [Source](https://aws.amazon.com/q/developer/)\n- **Key Features**:\n - Session-aware responses for multi-step tasks.\n - CLI autocompletions and natural language-to-bash translation.\n - AI chat in terminal (locally and over SSH).\n - Strong AWS service integration for cloud workflows.\n - Autonomous agents for feature implementation, refactoring, dependency upgrades.\n - Cost estimation and optimization recommendations.\n - Available in IDE, CLI, AWS Console, and Slack.\n- **Pricing**: Free tier with 1,000 agentic chat interactions/month (from August 2025), 4,000 LOC/month for transformations. Pro tier at $19/month per user with higher limits. [Source](https://aws.amazon.com/q/developer/pricing/)\n- **Usage Limits**: Free tier: 1,000 agentic interactions/month, 1,000 generative SQL queries/month. Pro tier offers higher limits.\n- **Why It Fits**: Ideal for AWS users needing cloud-integrated CLI tools with generous free tier.\n\n### Qwen Code\n- **Description**: An open-source AI agent from Alibaba optimized for Qwen3-Coder, adapted from Gemini CLI. Provides Claude Code-like experience with 2,000 free requests/day via OAuth. [Source](https://github.com/QwenLM/qwen-code)\n- **Agent Mode**: Full agentic workflow with Skills, SubAgents, and Plan Mode.\n- **AI Model Support**: Optimized for Qwen3-Coder-480B (480B parameters, 35B active with MoE). Supports 256K native context, 1M with extrapolation. State-of-the-art among open models for agentic coding. [Source](https://qwenlm.github.io/blog/qwen3-coder/)\n- **Key Features**:\n - Deep code understanding & editing beyond normal context windows.\n - Workflow automation: PR handling, rebases, formatting.\n - Enhanced parser optimized for Qwen-Coder models.\n - Vision model support for multimodal analysis.\n - OpenAI-compatible API.\n - OAuth free tier: 2,000 requests/day.\n - Terminal-first, IDE-friendly (VS Code, Zed integration).\n - Fully open-source (both framework and model).\n- **Pricing**: Free to use with OAuth (2,000 requests/day). OpenAI-compatible API available. [Source](https://github.com/QwenLM/qwen-code)\n- **Usage Limits**: OAuth free tier: 2,000 requests/day.\n- **Why It Fits**: Best free option with powerful open-source model and generous daily limits.\n\n### Droid by Factory\n- **Description**: Enterprise-grade AI coding agent from Factory that lives in your terminal and handles end-to-end development workflows. #1 on Terminal-Bench with 58.75% score. [Source](https://factory.ai/news/terminal-bench)\n- **Agent Mode**: Full autonomous agent with multi-model orchestration. Extracts more capability from each model than labs' own agents.\n- **AI Model Support**: Supports Anthropic (Opus, Sonnet) and OpenAI (GPT-5) models. Droid with Opus (58.8%) beats Claude Code with Opus (43.2%). [Source](https://factory.ai/)\n- **Key Features**:\n - Multi-model support: switch between labs without switching tools.\n - Specialized Droids: Knowledge, Reliability, Product agents.\n - IDE integration: VS Code, JetBrains, Vim.\n - Web interface, IDE extension, and CLI.\n - CI/CD integration for migrations and maintenance.\n - Automated code review and self-healing builds.\n - Enterprise-grade with team features.\n- **Pricing**: Free trial available. Enterprise pricing. [Source](https://factory.ai/)\n- **Usage Limits**: Contact for enterprise limits.\n- **Why It Fits**: Best for enterprises needing top benchmark performance and specialized agent types.\n\n### Roo Code\n- **Description**: An open-source AI coding agent for VS Code with 21.4K GitHub stars, providing a whole dev team of AI agents in your code editor. Fork/derivation of Cline. [Source](https://github.com/RooCodeInc/Roo-Code)\n- **Agent Mode**: Multiple modes (Code, Architect, Ask, Debug, Custom) for different development tasks. Supports multi-file edits, test execution, and browser control.\n- **AI Model Support**: Fully customizable, integrating any AI model (OpenAI, Anthropic, local LLMs). [Source](https://roocode.com)\n- **Key Features**:\n - Multiple modes: Code, Architect, Ask, Debug, Custom.\n - Sticky models: preserves stateful preferences per mode.\n - Multi-file edits and refactoring.\n - Test execution and browser control.\n - Completely free and open-source.\n - Privacy: code never leaves your machine unless you connect to external API.\n - 901K installs on VS Code Marketplace.\n- **Pricing**: Free and open-source. API costs depend on chosen model provider. [Source](https://roocode.com)\n- **Usage Limits**: API usage-based.\n- **Why It Fits**: Best for developers wanting multiple AI agent modes within VS Code.\n\n### OpenHands (formerly OpenDevin)\n- **Description**: An open-source (MIT license) platform for AI-powered software development with SDK, CLI, and GUI interfaces. Creates autonomous AI agents that emulate human software developers. [Source](https://openhands.dev/)\n- **Agent Mode**: Full autonomous agent capable of modifying code, executing commands, browsing the web, and interacting with APIs. Solves over 50% of real GitHub issues on SWE-bench.\n- **AI Model Support**: Model-agnostic platform supporting Claude, GPT, and any LLM. [Source](https://github.com/OpenHands/OpenHands)\n- **Key Features**:\n - SDK: composable Python library for defining agents.\n - CLI: Claude Code/Codex-like experience.\n - Local GUI: React application with REST API.\n - Cloud deployment: scale to 1000s of agents.\n - Sandboxed environment for safe execution.\n - $10 free credit for new users.\n - Task management integrations: Jira, Linear.\n- **Pricing**: Free and open-source (MIT license, except enterprise directory). $10 free credit. [Source](https://openhands.dev/)\n- **Usage Limits**: API usage-based.\n- **Why It Fits**: Best for developers wanting a complete platform for autonomous AI development with multiple interfaces.\n\n## Comparison Table\n\n| **CLI Tool** | **GitHub Stars** | **Open-Source** | **AI Model Support** | **Pricing** | **Free Tier** | **Key Strengths** | **Best For** |\n|--------------|------------------|-----------------|----------------------|-------------|---------------|-------------------|--------------|\n| **Claude Code** | 49K | No | Sonnet 4/4.5, Opus 4/4.5 | Pro $20/mo, Max $100-200/mo | No (Pro required) | Deep codebase understanding, multi-file edits, LSP support | Complex, multi-file projects |\n| **Gemini CLI** | 88.5K | Yes (Apache 2.0) | Gemini 2.5 Pro, Gemini 3 Flash/Pro | Free, AI Pro $19.99/mo | Yes (1000 req/day) | Largest free tier, 1M token context, GitHub Actions | Large-context refactors |\n| **OpenAI Codex CLI** | 54.7K | Yes (Apache 2.0) | GPT-5.2-Codex, GPT-5, o3, o4-mini | Free, API pay-as-you-go | Yes | Agent skills, GitHub/Linear integration | Deep GitHub integration |\n| **Cline** | 50K+ | Yes | Any LLM (Sonnet 4, Opus 4, GPT-5, Grok 4) | Free, API pay-as-you-go | Yes | Plan/Act modes, fastest-growing, enterprise features | IDE-integrated autonomy |\n| **Aider** | ~35K | Yes | Any LLM (Claude 4.1, GPT-5, Grok 4, local) | Free, API pay-as-you-go | Yes | Git integration, multi-language, voice input | Open-source Git workflows |\n| **Goose** | 24.8K | Yes (Apache 2.0) | Any LLM with tool calling | Free, API pay-as-you-go | Yes | Local execution, AAIF member, ACP support | Privacy-focused, extensible |\n| **OpenCode** | 41K | Yes | Any LLM (OpenAI, Anthropic, Ollama) | Free, API pay-as-you-go | Yes | Multi-session, LSP-enabled, shareable sessions | Claude Code alternative |\n| **Warp** | N/A | No | Claude 3.5, GPT-4o, BYOK | Free, Build $20/mo | Yes (75-150 credits/mo) | AI-native terminal, BYOK, multi-platform | AI-native terminal experience |\n| **Kiro CLI** | N/A | No | Claude Haiku 4.5, Auto mode | Free, Pro $20-200/mo | Yes (500 bonus) | Spec-driven development, AWS integration | AWS teams, structured workflows |\n| **Amazon Q Developer CLI** | N/A | No | Claude Sonnet 4 via Bedrock | Free, Pro $19/mo | Yes (1000 interactions/mo) | AWS integration, cost optimization | AWS users, cloud workflows |\n| **Qwen Code** | New | Yes (Apache 2.0) | Qwen3-Coder-480B (256K-1M context) | Free (2000 req/day OAuth) | Yes (2000 req/day) | Open-source model, vision support | Free usage, open models |\n| **Droid** | N/A | No | Opus 4, Sonnet 4, GPT-5 | Free trial, Enterprise | Trial | #1 Terminal-Bench, multi-model | Enterprise, top performance |\n| **Roo Code** | 21.4K | Yes | Any LLM (OpenAI, Anthropic, local) | Free, API pay-as-you-go | Yes | Multiple modes, VS Code integration | Multi-mode VS Code agent |\n| **OpenHands** | N/A | Yes (MIT) | Any LLM (Claude, GPT) | Free ($10 credit), API | Yes ($10 credit) | SDK/CLI/GUI, 50%+ SWE-bench | Platform for AI dev |\n\n## Analysis and Recommendations\n\nBased on the evidence gathered in December 2025, all major tools support or can be configured to support the latest AI models. The market has seen significant consolidation around MCP (Model Context Protocol) and AGENTS.md standards.\n\n**Recommendations**:\n- **For complex projects**: Choose **Claude Code** for its precision and deep codebase comprehension, starting at $20/month.\n- **For maximum free usage**: Choose **Gemini CLI** for its industry-leading 1,000 requests/day free tier and 1M token context.\n- **For open-source with GPT-5**: Choose **OpenAI Codex CLI** for agent skills and GitHub integration.\n- **For fastest-growing community**: Choose **Cline** with 50K+ stars and enterprise features.\n- **For Git-integrated workflows**: Choose **Aider** for automatic commits and flexible model support.\n- **For local execution and privacy**: Choose **Goose** for fully local operation with any LLM.\n- **For Claude Code alternative**: Choose **OpenCode** for multi-session support and LSP features.\n- **For AI-native terminal**: Choose **Warp** for a reimagined terminal experience with BYOK.\n- **For AWS users**: Choose **Amazon Q Developer CLI** or **Kiro CLI** for cloud-integrated coding.\n- **For free open-source model**: Choose **Qwen Code** for 2,000 requests/day with Qwen3-Coder.\n- **For top benchmark performance**: Choose **Droid by Factory** (#1 on Terminal-Bench).\n- **For multi-mode IDE agent**: Choose **Roo Code** for Code/Architect/Debug/Ask modes.\n- **For complete AI dev platform**: Choose **OpenHands** for SDK, CLI, and GUI interfaces.\n\n## References\n\nFor further details, explore the official documentation:\n- [Claude Code](https://github.com/anthropics/claude-code)\n- [Gemini CLI](https://github.com/google-gemini/gemini-cli)\n- [OpenAI Codex CLI](https://github.com/openai/codex)\n- [Cline](https://cline.bot/)\n- [Aider](https://aider.chat/)\n- [Goose](https://github.com/block/goose)\n- [OpenCode](https://opencode.ai/)\n- [Warp](https://www.warp.dev/)\n- [Kiro CLI](https://kiro.dev/cli/)\n- [Amazon Q Developer CLI](https://aws.amazon.com/q/developer/)\n- [Qwen Code](https://github.com/QwenLM/qwen-code)\n- [Factory Droid](https://factory.ai/)\n- [Roo Code](https://roocode.com/)\n- [OpenHands](https://openhands.dev/)\n\n### Additional Sources\n- [GPT-5.2-Codex Announcement](https://openai.com/index/introducing-gpt-5-2-codex/)\n- [Claude Opus 4.5 Announcement](https://www.anthropic.com/news/claude-opus-4-5)\n- [Gemini 3 Flash in Gemini CLI](https://developers.googleblog.com/gemini-3-flash-is-now-available-in-gemini-cli/)\n- [Grok 4 Announcement](https://x.ai/news/grok-4/)\n- [Qwen3-Coder Announcement](https://qwenlm.github.io/blog/qwen3-coder/)\n- [Agentic AI Foundation (Linux Foundation)](https://www.linuxfoundation.org/press/linux-foundation-announces-the-formation-of-the-agentic-ai-foundation)\n- [Droid Terminal-Bench Results](https://factory.ai/news/terminal-bench)\n- [Cline Fastest Growing AI Project](https://cline.bot/blog/cline-the-fastest-growing-ai-open-source-project-on-github-in-2025-thanks-to-you)\n- [Claude Pricing](https://www.anthropic.com/pricing)\n- [Gemini CLI Pricing](https://geminicli.com/docs/quota-and-pricing/)\n- [Amazon Q Developer Pricing](https://aws.amazon.com/q/developer/pricing/)\n- [Kiro Pricing](https://kiro.dev/pricing/)\n- [Warp Pricing](https://www.warp.dev/pricing)\n","numLines":371,"startLine":1,"totalLines":371}}} | |
| [2025-12-28T03:04:14.800Z] [INFO] {"type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01X6KcZi9RuPqHBZVsvfaDRS","type":"tool_result","content":" 1β# Comprehensive Analysis of AI Code Editors with Agent Mode (Updated as of December 2025)\n 2β\n 3βThis comprehensive analysis, updated on **December 27, 2025**, evaluates AI code editors with agent modes, focusing on the most popular tools of the current day, support for advanced models, pricing structures, and key features. The analysis ensures alignment with the latest data, emphasizing fair pricing and a preference for open-source options where possible. Below, we detail each editor, their features, model support, pricing, usage limits, and recommendations, providing a thorough overview for users seeking autonomous coding assistance.\n 4β\n 5β## Background and Context\n 6β\n 7βAI code editors with agent mode have evolved significantly in 2025. Unlike passive autocomplete tools, agentic editors actively plan and execute multi-step tasks: reading your repository, generating or editing files, running tests, resolving Git history, and orchestrating shell commands through natural-language prompts. According to the 2025 Stack Overflow Survey, 78% of developers now use or plan to use AI tools, and 23% employ AI agents at least weekly.\n 8β\n 9βThis analysis covers the leading editors including Cursor, GitHub Copilot, Windsurf, Zed, Cline, Continue, JetBrains Junie, and newer entrants like Devin AI, Augment Code, Qodo, PearAI, Roo Code, Tabnine, and Replit Agent.\n 10β\n 11β## Methodology\n 12β\n 13βThe research involved web searches to verify AI code editors with agent mode, cross-referencing official documentation, blogs, pricing pages, and community discussions to confirm model support, pricing, usage limits, and agent mode capabilities.\n 14β\n 15β## Detailed Analysis of AI Code Editors\n 16β\n 17β### Cursor\n 18β\n 19β- **Description**: Cursor is a VS Code-based AI code editor with a robust agent mode that autonomously generates code, runs terminal commands, and applies fixes across multiple files. Cursor 2.0 (2025) introduced Composerβtheir first coding modelβand a redesigned interface centered on agents rather than just files. Cursor 2.2 was released on December 10, 2025 ([Cursor Website](https://cursor.com)).\n 20β- **Agent Mode**: Features a powerful agent mode that generates code across files, auto-detects context, and applies changes instantly. With \"YOLO mode\" enabled, it can execute terminal commands without asking each timeβuseful for test-driven development loops. Agent mode includes multi-agent judging, pinned chats, and AI code review in editor.\n 21β- **AI Model Support**: Supports frontier models from OpenAI (GPT-5, GPT-4.1, o3), Anthropic (Claude Opus 4, Sonnet 4), Google (Gemini 2.5 Pro), and xAI (Grok 4) via partnerships. \"Auto\" mode lets Cursor choose the optimal model ([Cursor Pricing](https://cursor.com/pricing)).\n 22β- **Key Features**:\n 23β - Autocomplete and smart rewrite for efficient refactoring.\n 24β - Natural language code generation and codebase indexing.\n 25β - Automatic lint error detection and fixes.\n 26β - Privacy mode ensures code is not stored remotely without consent.\n 27β - Supports multimodal inputs (text, screenshots, diagrams).\n 28β - Plan Mode, AI Code Review, and Instant Grep (v2.1+).\n 29β- **Pricing**: Hobby (Free, 2,000 completions + 50 slow requests), Pro ($20/month, $20 credit pool for advanced models), Pro+ ($60/month, 3x credits, 1,500 fast agent requests), Ultra ($200/month, 20x credits, 5,000 fast agent requests, experimental models), Teams ($40/user/month, 500 agent requests per member) ([Cursor Pricing](https://cursor.com/pricing)).\n 30β- **Usage Limits**: Auto requests are unlimited on Pro/Ultra. Non-Auto requests consume the pool at rates based on the underlying model's API cost. Overages charged at raw API rates.\n 31β- **Why It Fits**: The de facto standard for AI-native development, offering a polished agent mode ideal for complex, multi-file projects.\n 32β\n 33β### GitHub Copilot\n 34β\n 35β- **Description**: GitHub Copilot is an AI pair programmer integrated into IDEs like VS Code and JetBrains, with agent mode for autonomous code changes and issue resolution. With 53.8 million installs, it's the most widely adopted AI coding tool ([GitHub Copilot](https://github.com/features/copilot)).\n 36β- **Agent Mode**: Agent mode transforms Copilot into an \"autonomous peer programmer\" that can perform multi-step coding tasks. You can assign issues directly to Copilot, and it autonomously writes code, creates pull requests, and responds to feedback. As of July 2025, each coding agent session uses just ONE premium request regardless of complexity ([GitHub Blog](https://github.blog/news-insights/product-news/github-copilot-meet-the-new-coding-agent/)).\n 37β- **AI Model Support**: Supports GPT-5 mini, GPT-4.1, GPT-4o (included in paid plans), with Pro+ adding access to all AI models including Claude Opus 4 and OpenAI o3 ([GitHub Copilot Models](https://docs.github.com/en/copilot/reference/ai-models/supported-ai-models-in-copilot)).\n 38β- **Key Features**:\n 39β - Context-aware code suggestions and multi-file edits.\n 40β - Copilot Chat for coding-related queries.\n 41β - Integration with GitHub repositories for enhanced context.\n 42β - Supports multimodal inputs (text, images).\n 43β - Code review and agent mode for autonomous development.\n 44β- **Pricing**: Free (2,000 inline suggestions, 50 premium requests), Pro ($10/month, 300 premium requests, unlimited completions), Pro+ ($39/month, 1,500 premium requests, access to all AI models), Business ($19/user/month, centralized management), Enterprise ($39/user/month, 1,000 premium requests, knowledge bases) ([GitHub Copilot Pricing](https://github.com/features/copilot/plans)).\n 45β- **Usage Limits**: Premium requests power agent mode, code review, and advanced models. Overage is $0.04/request. December 2025 billing changes removed legacy $0 budgets for enterprise accounts.\n 46β- **Why It Fits**: Most cost-effective at $10/month for Pro with reliable model access, making it ideal for agentic workflows with strong GitHub integration.\n 47β\n 48β### Windsurf\n 49β\n 50β- **Description**: Windsurf (formerly Codeium) is an AI-native IDE described as \"the first agentic IDE.\" Its Cascade feature autonomously handles coding tasks and debugging. Named a Gartner Leader in September 2025. News of OpenAI's planned acquisition has been reported ([Windsurf Website](https://windsurf.com)).\n 51β- **Agent Mode**: Cascade combines deep codebase understanding with real-time awareness of developer actions. It plans multi-step edits, calls tools, and uses deep repo context. Flow Awareness allows the AI to operate on a shared timeline with the developer, understanding incomplete work and long-running tasks ([Windsurf Editor](https://windsurf.com/editor)).\n 52β- **AI Model Support**: SWE-1 is the flagship frontier model for advanced reasoning. SWE-1-lite is unlimited for all users including free plans. Supports Claude Sonnet 4.5, GPT-4o, and other models via BYOK ([Windsurf Pricing](https://windsurf.com/pricing)).\n 53β- **Key Features**:\n 54β - Deep contextual awareness for production codebases.\n 55β - AI-powered terminal for command generation.\n 56β - Privacy-first policies with optional zero-day retention (ZDR).\n 57β - Seamless VS Code settings import.\n 58β - Tab + Supercomplete with multi-line suggestions.\n 59β - Supports 70+ programming languages.\n 60β- **Pricing**: Free (25 credits/month, SWE-1-lite unlimited), Pro ($15/month, 500 credits), Teams ($30/user/month), Enterprise ($60/user/month with ZDR defaults) ([Windsurf Pricing](https://windsurf.com/pricing)).\n 61β- **Usage Limits**: Credits consumed per prompt; premium models cost more credits. SWE-1-lite and SWE-1-mini are unlimited for all users.\n 62β- **Why It Fits**: Strong autonomous agent mode with affordable pricing and robust multi-file editing capabilities.\n 63β\n 64β### Zed\n 65β\n 66β- **Description**: Zed is a high-performance, open-source code editor written in Rust by the former Atom team. It leverages multiple CPU cores and GPU for millisecond typing latency even in million-line repositories. 150K monthly active users; 2nd most popular AI IDE among Rust developers ([Zed Website](https://zed.dev)).\n 67β- **Agent Mode**: Agentic Editing allows users to describe changes in natural language. The Zed AI agent patches files, shows diffs, and asks for approval. Diffs are fully editable with normal multi-cursor and language server features ([Zed Agentic](https://zed.dev/agentic)).\n 68β- **AI Model Support**: Expanded to include GPT-5 (with mini and nano variants), Gemini 2.5 Pro/Flash, all Anthropic models, plus OpenRouter, Ollama, and local models. Zetaβtheir open-source edit prediction modelβpowers AI autocomplete ([Zed AI](https://zed.dev/ai)).\n 69β- **Key Features**:\n 70β - Blazing-fast performance with GPU acceleration.\n 71β - Real-time collaboration and native Git support.\n 72β - Inline assistant for code transformations.\n 73β - Zeta Edit Prediction (AI Autocomplete) runs locally, free while in beta.\n 74β - Option to run models locally via Ollama.\n 75β - Agent Client Protocol (ACP) support for external agents like Claude Code.\n 76β- **Pricing**: Token-based pricing (switched from prompt-based in late 2025). Zed Pro includes $5 monthly credit, billed at API list price +10%. Free tier available for non-AI usage. BYOK supported for free ([Zed Pricing](https://zed.dev/pricing)).\n 77β- **Usage Limits**: Token-basedβyou're only charged for the text your prompts and responses consume. Costs vary by model.\n 78β- **Why It Fits**: Appeals to users prioritizing speed and open-source solutions with flexible agent mode capabilities.\n 79β\n 80β### Cline\n 81β\n 82β- **Description**: Cline is an open-source AI coding assistant for VS Code (4M+ developers) and JetBrains, designed as an autonomous coding agent with Plan/Act modes and terminal execution ([Cline Website](https://cline.bot)).\n 83β- **Agent Mode**: Features dual Plan/Act modes where the agent devises a plan and executes steps one by one. Can read the entire project, search within files, and perform terminal commands. Each step requires explicit user approval, giving engineers full control ([Cline GitHub](https://github.com/cline/cline)).\n 84β- **AI Model Support**: Model-agnostic, supporting Claude Sonnet 4.5, GPT-4o, Gemini 2.5 Pro, DeepSeek, and any model via API including OpenAI, Anthropic, Google, AWS Bedrock, and local models ([Cline Documentation](https://cline.bot/pricing)).\n 85β- **Key Features**:\n 86β - Deep context understanding for accurate assistance.\n 87β - Permission-based file changes and command execution.\n 88β - Supports Model Context Protocol (MCP) for tool integration.\n 89β - Real-time debugging and browser capabilities.\n 90β - JetBrains extension available.\n 91β- **Pricing**: Free extensionβyou pay AI providers directly. Token pricing varies by model (e.g., Claude Sonnet 4.5 ~$3/$15 per million input/output tokens). Open Source Teams ($20/month after 2025, first 10 seats always free) adds team management and centralized billing ([Cline Pricing](https://cline.bot/pricing)).\n 92β- **Usage Limits**: API usage-based; costs scale with usage.\n 93β- **Why It Fits**: Perfect for users seeking an open-source, autonomous coding assistant with full control and flexible model support.\n 94β\n 95β### Continue\n 96β\n 97β- **Description**: Continue is an open-source AI code agent available as an extension for VS Code and JetBrains, or as a CLI for terminal/headless operation. The leading open-source option with 20K+ GitHub stars ([Continue Website](https://www.continue.dev)).\n 98β- **Agent Mode**: Features background agents for automation, launched in seconds. Start with battle-tested workflows for GitHub, Sentry, Snyk, Linearβthen customize prompts, models, and MCP tools. Trigger on events or schedules ([Continue Documentation](https://docs.continue.dev)).\n 99β- **AI Model Support**: Works with virtually any AI modelβfast local models for routine autocompletions, or Claude Opus for complex decisions. Supports OpenAI, Anthropic, local models via Ollama, and more ([Continue GitHub](https://github.com/continuedev/continue)).\n 100β- **Key Features**:\n 101β - Real-time code suggestions and error detection.\n 102β - Supports local and cloud-based models for privacy.\n 103β - Multi-file edit capabilities with user approval.\n 104β - TUI mode as coding agent or Headless mode for background agents.\n 105β - Deploy workflows anywhere: local bash scripts, CI/CD, cron.\n 106β - Model Context Protocol (MCP) support.\n 107β- **Pricing**: FreeβSolo plan includes all core features. You only pay for API access to chosen models or use free local models via Ollama ([Continue Website](https://www.continue.dev)).\n 108β- **Usage Limits**: API usage-based.\n 109β- **Why It Fits**: Ideal for tech-savvy users who want an open-source, customizable solution with flexible model support and terminal-native operation.\n 110β\n 111β### JetBrains Junie\n 112β\n 113β- **Description**: Junie is an AI coding agent by JetBrains, designed to autonomously handle complex coding tasks within JetBrains' IDEs (IntelliJ IDEA, PyCharm, etc.). Now integrated into AI chat with the separate interfaces merged into a single, unified space ([Junie Website](https://www.jetbrains.com/junie)).\n 114β- **Agent Mode**: Works autonomously to plan and execute multi-step code tasks. Can make large-scale code changes, run tests, and verify steps. JetBrains benchmarks models and trains Junie to verify stepsβnot just generate code faster, but create maintainable solutions ([Junie Documentation](https://www.jetbrains.com/help/junie)).\n 115β- **AI Model Support**: Uses leading LLMs optimized for each task. BYOK (Bring Your Own Key) is now available (December 2025) for Claude 4, GPT-5, Gemini, locally hosted models, and moreβno subscription required for BYOK ([JetBrains Blog](https://blog.jetbrains.com/ai/2025/12/bring-your-own-key-byok-is-now-live-in-jetbrains-ides/)).\n 116β- **Key Features**:\n 117β - Autonomous task execution with progress reporting.\n 118β - Ability to make large-scale code changes and run tests.\n 119β - Deep integration with JetBrains' IDEs.\n 120β - Unified AI chat interface combining AI Assistant and Junie.\n 121β - Transparent quota model with AI Credits top-ups that carry over.\n 122β- **Pricing**: AI Free (unlimited code completion, limited cloud AI quota), AI Pro (suitable for occasional Junie use, with top-up option), AI Ultimate (larger quota for agentic workflows), AI Enterprise (large quota, advanced management, on-premises option) ([JetBrains AI Pricing](https://www.jetbrains.com/ai-ides/buy/)).\n 123β- **Usage Limits**: Monthly cloud usage plus optional AI Credits. Junie tasks consume more credits due to verification steps, but produce better results.\n 124β- **Why It Fits**: Ideal for users within the JetBrains ecosystem seeking a powerful autonomous coding agent with deep IDE integration.\n 125β\n 126β### Devin AI\n 127β\n 128β- **Description**: Devin AI by Cognition Labs is billed as \"the world's first AI software engineer\"βan autonomous agent that handles the entire software development cycle. Devin 2.0 launched in April 2025 with significantly lower pricing ([Devin Website](https://devin.ai)).\n 129β- **Agent Mode**: After receiving a natural language task, Devin generates an implementation plan, writes code, runs it in a sandbox, debugs issues, and continues until completion. Features Interactive Planning, Devin Search for codebase understanding, and automatic repository indexing with architecture diagrams ([Cognition Blog](https://cognition.ai/blog/devin-2)).\n 130β- **AI Model Support**: Proprietary AI models optimized for software engineering. Integrates with Jira, Linear, Slack, and Teams for issue/task management.\n 131β- **Key Features**:\n 132β - Spin up multiple parallel Devins, each with cloud-based IDE.\n 133β - Interactive Planning for collaborative task scoping.\n 134β - Devin Search for codebase questions with cited code.\n 135β - Automatic PR creation, review, and responses.\n 136β - Repository wikis with architecture diagrams.\n 137β- **Pricing**: Core ($20/month + $2.25/ACU), Team ($500/month, 250 ACUs included, $2/ACU extra), Enterprise (custom). An ACU equals ~15 minutes of active Devin work ([Devin Pricing](https://devin.ai/pricing)).\n 138β- **Usage Limits**: ACU-based (Agent Compute Units). Devin 2.0 completes 83% more tasks per ACU than its predecessor.\n 139β- **Why It Fits**: Best for organizations wanting a fully autonomous AI software engineer that handles complete tasks end-to-end.\n 140β\n 141β### Augment Code\n 142β\n 143β- **Description**: Augment Code is a developer AI platform that deeply indexes your codebase to power code completions, natural-language instructions, and autonomous agents. Uses intelligent multi-model architecture, routing to optimal models. Claude Sonnet 4.5 is the default model as of late 2025 ([Augment Website](https://www.augmentcode.com)).\n 144β- **Agent Mode**: The Agent introduces Memories that automatically update and persist across conversations. Can access GitHub, Jira, Confluence, Notion, Linear, and more through native tools, plus full MCP support ([Augment Product](https://www.augmentcode.com/product)).\n 145β- **AI Model Support**: Intelligent multi-model architecture routing to optimal models. Supports Claude Sonnet 4.5 (default), GPT-4o, and others.\n 146β- **Key Features**:\n 147β - Industry-leading context capacityβtwice that of comparable tools.\n 148β - 200K context window for better codebase understanding.\n 149β - Memories feature that persists context across conversations.\n 150β - Integrates with VS Code, JetBrains, and Vim/Neovim.\n 151β - Full MCP support for Vercel, Cloudflare, and other integrations.\n 152β- **Pricing**: Credit-based model (since October 2025). Trial (30,000 credits), Indie ($20/month, 40,000 credits), Developer ($50/month, more credits), Enterprise (custom). Top-up credits valid for 12 months ([Augment Pricing](https://www.augmentcode.com/pricing)).\n 153β- **Usage Limits**: Credit-based reflecting actual compute cost. Users notified when approaching limits.\n 154β- **Why It Fits**: Excellent for teams needing deep codebase understanding with persistent AI memory and broad tool integrations.\n 155β\n 156β### Qodo (formerly CodiumAI)\n 157β\n 158β- **Description**: Qodo is a quality-first AI code review platform recognized as a Visionary in the 2025 Gartner Magic Quadrant for AI Code Assistants. Specialized agents focus on testing, code analysis, and automated code improvement ([Qodo Website](https://www.qodo.ai)).\n 159β- **Agent Mode**: Multiple specialized agentsβQodo Gen (code generation and tests in IDE), Qodo Merge (open-source PR agent for reviews), Qodo Command (terminal/CI scripted agents), Qodo Cover (repository analysis and test generation), Qodo Aware (codebase intelligence) ([Qodo Pricing](https://www.qodo.ai/pricing)).\n 160β- **AI Model Support**: Supports GPT-4o, Claude Opus, and other models. Premium models consume more credits.\n 161β- **Key Features**:\n 162β - PR review scanning every pull request, ranking issues by severity.\n 163β - Inline chats in GitHub, GitLab, and Bitbucket.\n 164β - Test coverage improvement through Qodo Cover.\n 165β - Full SDLC coverage.\n 166β - SOC 2 Type II-audited; deploy SaaS, on-prem, VPC, or air-gapped.\n 167β- **Pricing**: Developer (Free, 75 PRs + 250 credits/month), Teams ($30/user/month, 2,500 credits), Enterprise ($45/user, SSO, priority support, on-prem options) ([Qodo Pricing](https://www.qodo.ai/pricing)).\n 168β- **Usage Limits**: Credits reset monthly. 40K+ weekly active users.\n 169β- **Why It Fits**: Perfect for teams prioritizing code quality, testing, and automated PR reviews.\n 170β\n 171β### PearAI\n 172β\n 173β- **Description**: PearAI is an open-source AI code editor (fork of VS Code) with AI chat, coding agent, and AI debugging. Uses PearAI Router to connect to highest-performing AI models ([PearAI Website](https://www.trypear.ai)).\n 174β- **Agent Mode**: Coding agent can automatically implement features and fix bugs. Integration with Aider CLI and Roo Code/Cline as coding agents ([PearAI GitHub](https://github.com/trypear/pearai-app)).\n 175β- **AI Model Support**: PearAI Router automatically selects best-performing models. Select 'PearAI Model' for optimal performance.\n 176β- **Key Features**:\n 177β - Familiar VS Code UI with advanced AI capabilities.\n 178β - Codebase context awareness (stored locally).\n 179β - CMD+I for inline editing, CMD+L for new chat.\n 180β - @codebase to retrieve relevant snippets.\n 181β - PearAI Login and Launch (coming soon).\n 182β- **Pricing**: Free with BYOK, or $15/month for server access ([PearAI Website](https://www.trypear.ai)).\n 183β- **Usage Limits**: Based on chosen API provider.\n 184β- **Why It Fits**: Great open-source option for users wanting VS Code familiarity with integrated AI agents.\n 185β\n 186β### Roo Code\n 187β\n 188β- **Description**: Roo Code is an open-source VS Code extension (started as fork of Cline) providing a whole dev team of AI agents with custom modes/personas. Features Cloud Agents and Roomote Control for remote task management ([Roo Code Website](https://roocode.com)).\n 189β- **Agent Mode**: Multi-agent modes with specialized AI personalitiesβsecurity expert, performance optimizer, documentation writer, QA engineer. Boomerang tasks and Git-like checkpointing system ([Roo Code GitHub](https://github.com/RooCodeInc/Roo-Code)).\n 190β- **AI Model Support**: Open-source and fully customizable; integrate any AI model (OpenAI, Anthropic, local LLMs via Ollama).\n 191β- **Key Features**:\n 192β - Custom AI modes for different types of work.\n 193β - Multi-file edits with project-wide refactoring.\n 194β - Permission-based file changes and command execution.\n 195β - Roomote Control for remote VS Code control.\n 196β - Cloud Agents accessible from web, Slack, or GitHub.\n 197β - Code stays local unless connecting to external API.\n 198β- **Pricing**: Free and open-source (pay only for API usage). Cloud Agents: $5/hour while running ([Roo Code Pricing](https://roocode.com/pricing)).\n 199β- **Usage Limits**: API usage-based for models; Cloud Agents billed hourly.\n 200β- **Why It Fits**: Ideal for teams wanting specialized AI agents with deep customization and multi-persona support.\n 201β\n 202β### Tabnine\n 203β\n 204β- **Description**: Tabnine provides AI-powered coding assistance with a focus on enterprise security and compliance. Won \"Best Innovation in AI Coding\" at 2025 AI TechAwards for Code Review Agent ([Tabnine Website](https://www.tabnine.com)).\n 205β- **Agent Mode**: Org-Native Agents including Code Review Agent (catches defects, style issues, policy violations at PR time) and AI Test Agent. Image-to-Code converts Figma mockups, ER diagrams, or flowcharts into React components, SQL scripts, or orchestration code.\n 206β- **AI Model Support**: Supports leading LLMs from Anthropic, OpenAI, Google, Meta, Mistral. Enterprise admins can register private endpoints for Llama 3, Claude 4, Gemini 2.5, or internal models ([Tabnine Pricing](https://www.tabnine.com/pricing)).\n 207β- **Key Features**:\n 208β - AI chat supporting every SDLC step.\n 209β - 600+ programming languages support.\n 210β - Flexible deployment: SaaS, VPC, on-premises, or air-gapped.\n 211β - GDPR, SOC 2, ISO 27001 compliance.\n 212β - Zero code retention.\n 213β- **Pricing**: Free (basic completions, local), Pro ($12/user/month, 90-day trial, best-in-class models), Enterprise ($39/user/month, private deployment, fine-tuned models) ([Tabnine Pricing](https://www.tabnine.com/pricing)).\n 214β- **Usage Limits**: Based on plan tier.\n 215β- **Why It Fits**: Best for enterprises requiring private deployment, compliance, and specialized code review agents.\n 216β\n 217β### Replit Agent\n 218β\n 219β- **Description**: Replit is an AI-powered development platform with the Replit Agent for autonomous code generation, completion, and debugging. Effort-based pricing introduced June 2025 ([Replit Website](https://replit.com)).\n 220β- **Agent Mode**: The Agent writes production-ready code, evolves it as you iterate, and handles complete development tasks. Features high-power model option and extended thinking for complex problems ([Replit Blog](https://blog.replit.com/effort-based-pricing)).\n 221β- **AI Model Support**: Claude Sonnet 3.7, OpenAI GPT-4o, and other advanced models available with Core plan.\n 222β- **Key Features**:\n 223β - Built-in Authentication, Database, Hosting, and Monitoring.\n 224β - Services like Stripe or OpenAI plug in seamlessly.\n 225β - Multi-language support (Python, JavaScript, TypeScript, Java, C++, Go).\n 226β - One-click deployment for web apps, APIs, and static sites.\n 227β - Browser-based developmentβno local setup required.\n 228β- **Pricing**: Starter (Free, limited AI, 3 public apps), Replit Core ($20-25/month, $25 credits, ~100 Agent checkpoints, full AI access), Teams ($35-40/user/month, $40 credits, RBAC), Enterprise (custom) ([Replit Pricing](https://replit.com/pricing)).\n 229β- **Usage Limits**: Credit-based covering AI usage, deployments, and cloud services. Simple changes ~$0.25; complex tasks scale accordingly.\n 230β- **Why It Fits**: Perfect for browser-based development with integrated deployment and AI agent capabilities.\n 231β\n 232β### Amazon Q Developer\n 233β\n 234β- **Description**: Amazon Q Developer (formerly CodeWhisperer) is AWS's AI assistant for software development with agentic capabilities for multi-step tasks ([Amazon Q Developer](https://aws.amazon.com/q/developer)).\n 235β- **Agent Mode**: Autonomous agents can implement features, document, test, review, refactor code, and perform software upgrades. Session-aware for multi-step tasks.\n 236β- **AI Model Support**: Through Amazon Bedrock, supports Claude Sonnet 4, Opus 4, and other models.\n 237β- **Key Features**:\n 238β - Code suggestions and reference tracking for open-source snippets.\n 239β - Security scans and vulnerability detection.\n 240β - Strong AWS service integration.\n 241β - Works with VS Code, JetBrains, Visual Studio, Eclipse.\n 242β - SOC, ISO, HIPAA, and PCI compliant.\n 243β- **Pricing**: Free (1,000 LOC upgrades/month, 50 agentic requests/month), Pro ($19/user/month, 1,000 agentic requests, 4,000 LOC, data isolation, IP indemnity) ([Amazon Q Pricing](https://aws.amazon.com/q/developer/pricing)).\n 244β- **Usage Limits**: Overage at $0.003 per LOC for code transformation.\n 245β- **Why It Fits**: Ideal for AWS users needing cloud-integrated CLI tools with enterprise compliance.\n 246β\n 247β## Additional Editors Considered\n 248β\n 249β- **Tabby**: Open-source, self-hosted AI coding assistant with agentic workflows. Model support varies based on configuration.\n 250β- **Sourcegraph Cody**: AI coding assistant with codebase-wide context. Integrates with various IDEs and supports multiple LLMs.\n 251β- **Goose**: Open-source (Apache 2.0) AI agent framework from Block that runs locally and supports any LLM. Fully autonomous with extensible capabilities.\n 252β- **Antigravity**: Released November 2025, free public preview powered by Gemini 3 Pro + Claude Sonnet 4.5 + GPT-OSS. Features Editor View and Agent Manager modes.\n 253β- **CodeGPT**: AI coding agent platform for VS Code, JetBrains, and Cursor with repository-wide context and multi-model support.\n 254β\n 255β## Comparison Table\n 256β\n 257β| **AI Code Editor** | **Open-Source** | **AI Model Support** | **Pricing** | **Usage Limits** | **Key Strengths** | **Best For** |\n 258β|--------------------|-----------------|----------------------|-------------|------------------|-------------------|--------------|\n 259β| **Cursor** | No | GPT-5, Claude Opus 4/Sonnet 4, Gemini 2.5 Pro, Grok 4 | Free tier, Pro $20/mo, Pro+ $60/mo, Ultra $200/mo | Credit-based, Pro: $20 pool; Ultra: 5,000 agent requests | AI-first IDE, advanced agent mode, multi-model support | Complex multi-file projects with agentic workflows |\n 260β| **GitHub Copilot** | No (Chat extension open-source) | GPT-5 mini, GPT-4.1, Claude Opus 4 (Pro+) | Free tier, Pro $10/mo, Pro+ $39/mo, Enterprise $39/user | Premium requests: Free 50, Pro 300, Pro+ 1,500 | Widespread adoption, reliable agent mode, GitHub integration | Users needing guaranteed model access and issue automation |\n 261β| **Windsurf** | No | SWE-1, SWE-1-lite (unlimited), Claude Sonnet 4.5, GPT-4o | Free tier, Pro $15/mo, Teams $30/user, Enterprise $60/user | Credits per prompt; SWE-1-lite/mini unlimited | First agentic IDE, Cascade agent, deep context awareness | Autonomous task execution with affordable pricing |\n 262β| **Zed** | Yes | GPT-5, Gemini 2.5, Anthropic models, Ollama | Token-based, Pro $5/mo credit, BYOK free | Token-based billing at API rate +10% | Fastest editor (Rust), open-source, agentic editing | Performance-focused users with open-source preference |\n 263β| **Cline** | Yes | Any LLM (Claude Sonnet 4.5, GPT-4o, Gemini, local models) | Free extension, pay for API | API usage-based | Plan/Act modes, full control, MCP support | Open-source autonomous coding with user approval |\n 264β| **Continue** | Yes | Any LLM (OpenAI, Anthropic, Ollama, local) | Free, pay for API | API usage-based | Background agents, terminal-native, highly customizable | Tech-savvy users wanting open-source flexibility |\n 265β| **JetBrains Junie** | No | Multiple LLMs, BYOK supported | AI Free, AI Pro, AI Ultimate, AI Enterprise | Quota-based with AI Credits | Deep IDE integration, quality-focused agent | JetBrains ecosystem users |\n 266β| **Devin AI** | No | Proprietary models | Core $20/mo + $2.25/ACU, Team $500/mo | ACU-based (~15 min active work) | Fully autonomous AI engineer, parallel Devins | Full end-to-end autonomous development |\n 267β| **Augment Code** | No | Claude Sonnet 4.5 (default), multi-model | Indie $20/mo, Developer $50/mo | Credit-based | Memories feature, 200K context, broad integrations | Teams needing persistent AI memory |\n 268β| **Qodo** | Partially (Qodo Merge) | GPT-4o, Claude Opus | Free tier, Teams $30/user, Enterprise $45/user | Credits reset monthly | Quality-first, PR review, test generation | Code quality and automated reviews |\n 269β| **PearAI** | Yes | PearAI Router (auto-selects best) | Free (BYOK) or $15/mo | API usage-based | VS Code familiar, integrated agents | Open-source with simple pricing |\n 270β| **Roo Code** | Yes | Any LLM (OpenAI, Anthropic, Ollama) | Free, Cloud Agents $5/hr | API usage-based | Multi-persona agents, custom modes | Specialized AI teams with deep customization |\n 271β| **Tabnine** | No | Multiple LLMs, private model support | Free, Pro $12/user, Enterprise $39/user | Plan-based | Enterprise security, code review agent | Enterprises requiring compliance and private deployment |\n 272β| **Replit Agent** | No | Claude Sonnet 3.7, GPT-4o | Free tier, Core $20-25/mo, Teams $35-40/user | Credit-based (~$0.25/checkpoint) | Browser-based, integrated deployment | Browser-based development with AI |\n 273β| **Amazon Q Developer** | No | Claude models via Bedrock | Free tier, Pro $19/user | Agentic requests: Free 50, Pro 1,000 | AWS integration, enterprise compliance | AWS users and cloud workflows |\n 274β\n 275β## Analysis and Recommendations\n 276β\n 277βThe AI code editor landscape has matured significantly in 2025, with clear leaders emerging in different categories:\n 278β\n 279β**For Mainstream AI Development**:\n 280β- **Cursor** has become the de facto standard for AI-native development with its polished agent mode and broad model support at $20/month.\n 281β- **GitHub Copilot** remains the most cost-effective at $10/month with unmatched adoption and strong GitHub integration.\n 282β\n 283β**For Autonomous AI Engineers**:\n 284β- **Devin AI** leads in full autonomy, handling complete development cycles from planning to deployment.\n 285β- **Windsurf** offers the most accessible agentic IDE experience with affordable pricing.\n 286β\n 287β**For Open-Source Enthusiasts**:\n 288β- **Cline** and **Continue** provide maximum flexibility and control with zero lock-in.\n 289β- **Zed** offers the fastest performance with native AI integration.\n 290β- **Roo Code** excels with multi-persona AI agents and deep customization.\n 291β\n 292β**For Enterprise Users**:\n 293β- **Tabnine** provides the strongest enterprise security and compliance.\n 294β- **JetBrains Junie** offers deep IDE integration with quality-focused agents.\n 295β- **Amazon Q Developer** is optimal for AWS-integrated workflows.\n 296β\n 297β**Recommendations by Use Case**:\n 298β- **For guaranteed model access**: Choose **GitHub Copilot Pro** ($10/month) for affordability or **Cursor Pro** ($20/month) for the most polished experience.\n 299β- **For open-source with full control**: Opt for **Cline** or **Continue** with your preferred models.\n 300β- **For maximum performance**: **Zed** offers speed and agent mode with flexible model support.\n 301β- **For full autonomy**: **Devin AI** handles complete software engineering tasks end-to-end.\n 302β- **For code quality focus**: **Qodo** specializes in testing and PR reviews.\n 303β- **For AWS users**: **Amazon Q Developer** provides seamless cloud integration.\n 304β\n 305β## References\n 306β\n 307βFor further details, explore:\n 308β- [Cursor Website](https://cursor.com) | [Pricing](https://cursor.com/pricing)\n 309β- [GitHub Copilot](https://github.com/features/copilot) | [Plans](https://github.com/features/copilot/plans)\n 310β- [Windsurf Website](https://windsurf.com) | [Pricing](https://windsurf.com/pricing)\n 311β- [Zed Website](https://zed.dev) | [Pricing](https://zed.dev/pricing) | [AI](https://zed.dev/ai)\n 312β- [Cline Website](https://cline.bot) | [Pricing](https://cline.bot/pricing)\n 313β- [Continue Website](https://www.continue.dev) | [Documentation](https://docs.continue.dev)\n 314β- [JetBrains Junie](https://www.jetbrains.com/junie) | [AI Pricing](https://www.jetbrains.com/ai-ides/buy/)\n 315β- [Devin AI](https://devin.ai) | [Pricing](https://devin.ai/pricing)\n 316β- [Augment Code](https://www.augmentcode.com) | [Pricing](https://www.augmentcode.com/pricing)\n 317β- [Qodo](https://www.qodo.ai) | [Pricing](https://www.qodo.ai/pricing)\n 318β- [PearAI](https://www.trypear.ai) | [GitHub](https://github.com/trypear/pearai-app)\n 319β- [Roo Code](https://roocode.com) | [Pricing](https://roocode.com/pricing)\n 320β- [Tabnine](https://www.tabnine.com) | [Pricing](https://www.tabnine.com/pricing)\n 321β- [Replit](https://replit.com) | [Pricing](https://replit.com/pricing)\n 322β- [Amazon Q Developer](https://aws.amazon.com/q/developer) | [Pricing](https://aws.amazon.com/q/developer/pricing)\n 323β\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n"}]},"parent_tool_use_id":null,"session_id":"37701ccf-99c0-4955-a30f-f61eb4145748","uuid":"605e7355-e2af-4cc2-9c3b-558d1a69c67d","tool_use_result":{"type":"text","file":{"filePath":"/tmp/gh-issue-solver-1766891018916/ai-agentic-code-editors.md","content":"# Comprehensive Analysis of AI Code Editors with Agent Mode (Updated as of December 2025)\n\nThis comprehensive analysis, updated on **December 27, 2025**, evaluates AI code editors with agent modes, focusing on the most popular tools of the current day, support for advanced models, pricing structures, and key features. The analysis ensures alignment with the latest data, emphasizing fair pricing and a preference for open-source options where possible. Below, we detail each editor, their features, model support, pricing, usage limits, and recommendations, providing a thorough overview for users seeking autonomous coding assistance.\n\n## Background and Context\n\nAI code editors with agent mode have evolved significantly in 2025. Unlike passive autocomplete tools, agentic editors actively plan and execute multi-step tasks: reading your repository, generating or editing files, running tests, resolving Git history, and orchestrating shell commands through natural-language prompts. According to the 2025 Stack Overflow Survey, 78% of developers now use or plan to use AI tools, and 23% employ AI agents at least weekly.\n\nThis analysis covers the leading editors including Cursor, GitHub Copilot, Windsurf, Zed, Cline, Continue, JetBrains Junie, and newer entrants like Devin AI, Augment Code, Qodo, PearAI, Roo Code, Tabnine, and Replit Agent.\n\n## Methodology\n\nThe research involved web searches to verify AI code editors with agent mode, cross-referencing official documentation, blogs, pricing pages, and community discussions to confirm model support, pricing, usage limits, and agent mode capabilities.\n\n## Detailed Analysis of AI Code Editors\n\n### Cursor\n\n- **Description**: Cursor is a VS Code-based AI code editor with a robust agent mode that autonomously generates code, runs terminal commands, and applies fixes across multiple files. Cursor 2.0 (2025) introduced Composerβtheir first coding modelβand a redesigned interface centered on agents rather than just files. Cursor 2.2 was released on December 10, 2025 ([Cursor Website](https://cursor.com)).\n- **Agent Mode**: Features a powerful agent mode that generates code across files, auto-detects context, and applies changes instantly. With \"YOLO mode\" enabled, it can execute terminal commands without asking each timeβuseful for test-driven development loops. Agent mode includes multi-agent judging, pinned chats, and AI code review in editor.\n- **AI Model Support**: Supports frontier models from OpenAI (GPT-5, GPT-4.1, o3), Anthropic (Claude Opus 4, Sonnet 4), Google (Gemini 2.5 Pro), and xAI (Grok 4) via partnerships. \"Auto\" mode lets Cursor choose the optimal model ([Cursor Pricing](https://cursor.com/pricing)).\n- **Key Features**:\n - Autocomplete and smart rewrite for efficient refactoring.\n - Natural language code generation and codebase indexing.\n - Automatic lint error detection and fixes.\n - Privacy mode ensures code is not stored remotely without consent.\n - Supports multimodal inputs (text, screenshots, diagrams).\n - Plan Mode, AI Code Review, and Instant Grep (v2.1+).\n- **Pricing**: Hobby (Free, 2,000 completions + 50 slow requests), Pro ($20/month, $20 credit pool for advanced models), Pro+ ($60/month, 3x credits, 1,500 fast agent requests), Ultra ($200/month, 20x credits, 5,000 fast agent requests, experimental models), Teams ($40/user/month, 500 agent requests per member) ([Cursor Pricing](https://cursor.com/pricing)).\n- **Usage Limits**: Auto requests are unlimited on Pro/Ultra. Non-Auto requests consume the pool at rates based on the underlying model's API cost. Overages charged at raw API rates.\n- **Why It Fits**: The de facto standard for AI-native development, offering a polished agent mode ideal for complex, multi-file projects.\n\n### GitHub Copilot\n\n- **Description**: GitHub Copilot is an AI pair programmer integrated into IDEs like VS Code and JetBrains, with agent mode for autonomous code changes and issue resolution. With 53.8 million installs, it's the most widely adopted AI coding tool ([GitHub Copilot](https://github.com/features/copilot)).\n- **Agent Mode**: Agent mode transforms Copilot into an \"autonomous peer programmer\" that can perform multi-step coding tasks. You can assign issues directly to Copilot, and it autonomously writes code, creates pull requests, and responds to feedback. As of July 2025, each coding agent session uses just ONE premium request regardless of complexity ([GitHub Blog](https://github.blog/news-insights/product-news/github-copilot-meet-the-new-coding-agent/)).\n- **AI Model Support**: Supports GPT-5 mini, GPT-4.1, GPT-4o (included in paid plans), with Pro+ adding access to all AI models including Claude Opus 4 and OpenAI o3 ([GitHub Copilot Models](https://docs.github.com/en/copilot/reference/ai-models/supported-ai-models-in-copilot)).\n- **Key Features**:\n - Context-aware code suggestions and multi-file edits.\n - Copilot Chat for coding-related queries.\n - Integration with GitHub repositories for enhanced context.\n - Supports multimodal inputs (text, images).\n - Code review and agent mode for autonomous development.\n- **Pricing**: Free (2,000 inline suggestions, 50 premium requests), Pro ($10/month, 300 premium requests, unlimited completions), Pro+ ($39/month, 1,500 premium requests, access to all AI models), Business ($19/user/month, centralized management), Enterprise ($39/user/month, 1,000 premium requests, knowledge bases) ([GitHub Copilot Pricing](https://github.com/features/copilot/plans)).\n- **Usage Limits**: Premium requests power agent mode, code review, and advanced models. Overage is $0.04/request. December 2025 billing changes removed legacy $0 budgets for enterprise accounts.\n- **Why It Fits**: Most cost-effective at $10/month for Pro with reliable model access, making it ideal for agentic workflows with strong GitHub integration.\n\n### Windsurf\n\n- **Description**: Windsurf (formerly Codeium) is an AI-native IDE described as \"the first agentic IDE.\" Its Cascade feature autonomously handles coding tasks and debugging. Named a Gartner Leader in September 2025. News of OpenAI's planned acquisition has been reported ([Windsurf Website](https://windsurf.com)).\n- **Agent Mode**: Cascade combines deep codebase understanding with real-time awareness of developer actions. It plans multi-step edits, calls tools, and uses deep repo context. Flow Awareness allows the AI to operate on a shared timeline with the developer, understanding incomplete work and long-running tasks ([Windsurf Editor](https://windsurf.com/editor)).\n- **AI Model Support**: SWE-1 is the flagship frontier model for advanced reasoning. SWE-1-lite is unlimited for all users including free plans. Supports Claude Sonnet 4.5, GPT-4o, and other models via BYOK ([Windsurf Pricing](https://windsurf.com/pricing)).\n- **Key Features**:\n - Deep contextual awareness for production codebases.\n - AI-powered terminal for command generation.\n - Privacy-first policies with optional zero-day retention (ZDR).\n - Seamless VS Code settings import.\n - Tab + Supercomplete with multi-line suggestions.\n - Supports 70+ programming languages.\n- **Pricing**: Free (25 credits/month, SWE-1-lite unlimited), Pro ($15/month, 500 credits), Teams ($30/user/month), Enterprise ($60/user/month with ZDR defaults) ([Windsurf Pricing](https://windsurf.com/pricing)).\n- **Usage Limits**: Credits consumed per prompt; premium models cost more credits. SWE-1-lite and SWE-1-mini are unlimited for all users.\n- **Why It Fits**: Strong autonomous agent mode with affordable pricing and robust multi-file editing capabilities.\n\n### Zed\n\n- **Description**: Zed is a high-performance, open-source code editor written in Rust by the former Atom team. It leverages multiple CPU cores and GPU for millisecond typing latency even in million-line repositories. 150K monthly active users; 2nd most popular AI IDE among Rust developers ([Zed Website](https://zed.dev)).\n- **Agent Mode**: Agentic Editing allows users to describe changes in natural language. The Zed AI agent patches files, shows diffs, and asks for approval. Diffs are fully editable with normal multi-cursor and language server features ([Zed Agentic](https://zed.dev/agentic)).\n- **AI Model Support**: Expanded to include GPT-5 (with mini and nano variants), Gemini 2.5 Pro/Flash, all Anthropic models, plus OpenRouter, Ollama, and local models. Zetaβtheir open-source edit prediction modelβpowers AI autocomplete ([Zed AI](https://zed.dev/ai)).\n- **Key Features**:\n - Blazing-fast performance with GPU acceleration.\n - Real-time collaboration and native Git support.\n - Inline assistant for code transformations.\n - Zeta Edit Prediction (AI Autocomplete) runs locally, free while in beta.\n - Option to run models locally via Ollama.\n - Agent Client Protocol (ACP) support for external agents like Claude Code.\n- **Pricing**: Token-based pricing (switched from prompt-based in late 2025). Zed Pro includes $5 monthly credit, billed at API list price +10%. Free tier available for non-AI usage. BYOK supported for free ([Zed Pricing](https://zed.dev/pricing)).\n- **Usage Limits**: Token-basedβyou're only charged for the text your prompts and responses consume. Costs vary by model.\n- **Why It Fits**: Appeals to users prioritizing speed and open-source solutions with flexible agent mode capabilities.\n\n### Cline\n\n- **Description**: Cline is an open-source AI coding assistant for VS Code (4M+ developers) and JetBrains, designed as an autonomous coding agent with Plan/Act modes and terminal execution ([Cline Website](https://cline.bot)).\n- **Agent Mode**: Features dual Plan/Act modes where the agent devises a plan and executes steps one by one. Can read the entire project, search within files, and perform terminal commands. Each step requires explicit user approval, giving engineers full control ([Cline GitHub](https://github.com/cline/cline)).\n- **AI Model Support**: Model-agnostic, supporting Claude Sonnet 4.5, GPT-4o, Gemini 2.5 Pro, DeepSeek, and any model via API including OpenAI, Anthropic, Google, AWS Bedrock, and local models ([Cline Documentation](https://cline.bot/pricing)).\n- **Key Features**:\n - Deep context understanding for accurate assistance.\n - Permission-based file changes and command execution.\n - Supports Model Context Protocol (MCP) for tool integration.\n - Real-time debugging and browser capabilities.\n - JetBrains extension available.\n- **Pricing**: Free extensionβyou pay AI providers directly. Token pricing varies by model (e.g., Claude Sonnet 4.5 ~$3/$15 per million input/output tokens). Open Source Teams ($20/month after 2025, first 10 seats always free) adds team management and centralized billing ([Cline Pricing](https://cline.bot/pricing)).\n- **Usage Limits**: API usage-based; costs scale with usage.\n- **Why It Fits**: Perfect for users seeking an open-source, autonomous coding assistant with full control and flexible model support.\n\n### Continue\n\n- **Description**: Continue is an open-source AI code agent available as an extension for VS Code and JetBrains, or as a CLI for terminal/headless operation. The leading open-source option with 20K+ GitHub stars ([Continue Website](https://www.continue.dev)).\n- **Agent Mode**: Features background agents for automation, launched in seconds. Start with battle-tested workflows for GitHub, Sentry, Snyk, Linearβthen customize prompts, models, and MCP tools. Trigger on events or schedules ([Continue Documentation](https://docs.continue.dev)).\n- **AI Model Support**: Works with virtually any AI modelβfast local models for routine autocompletions, or Claude Opus for complex decisions. Supports OpenAI, Anthropic, local models via Ollama, and more ([Continue GitHub](https://github.com/continuedev/continue)).\n- **Key Features**:\n - Real-time code suggestions and error detection.\n - Supports local and cloud-based models for privacy.\n - Multi-file edit capabilities with user approval.\n - TUI mode as coding agent or Headless mode for background agents.\n - Deploy workflows anywhere: local bash scripts, CI/CD, cron.\n - Model Context Protocol (MCP) support.\n- **Pricing**: FreeβSolo plan includes all core features. You only pay for API access to chosen models or use free local models via Ollama ([Continue Website](https://www.continue.dev)).\n- **Usage Limits**: API usage-based.\n- **Why It Fits**: Ideal for tech-savvy users who want an open-source, customizable solution with flexible model support and terminal-native operation.\n\n### JetBrains Junie\n\n- **Description**: Junie is an AI coding agent by JetBrains, designed to autonomously handle complex coding tasks within JetBrains' IDEs (IntelliJ IDEA, PyCharm, etc.). Now integrated into AI chat with the separate interfaces merged into a single, unified space ([Junie Website](https://www.jetbrains.com/junie)).\n- **Agent Mode**: Works autonomously to plan and execute multi-step code tasks. Can make large-scale code changes, run tests, and verify steps. JetBrains benchmarks models and trains Junie to verify stepsβnot just generate code faster, but create maintainable solutions ([Junie Documentation](https://www.jetbrains.com/help/junie)).\n- **AI Model Support**: Uses leading LLMs optimized for each task. BYOK (Bring Your Own Key) is now available (December 2025) for Claude 4, GPT-5, Gemini, locally hosted models, and moreβno subscription required for BYOK ([JetBrains Blog](https://blog.jetbrains.com/ai/2025/12/bring-your-own-key-byok-is-now-live-in-jetbrains-ides/)).\n- **Key Features**:\n - Autonomous task execution with progress reporting.\n - Ability to make large-scale code changes and run tests.\n - Deep integration with JetBrains' IDEs.\n - Unified AI chat interface combining AI Assistant and Junie.\n - Transparent quota model with AI Credits top-ups that carry over.\n- **Pricing**: AI Free (unlimited code completion, limited cloud AI quota), AI Pro (suitable for occasional Junie use, with top-up option), AI Ultimate (larger quota for agentic workflows), AI Enterprise (large quota, advanced management, on-premises option) ([JetBrains AI Pricing](https://www.jetbrains.com/ai-ides/buy/)).\n- **Usage Limits**: Monthly cloud usage plus optional AI Credits. Junie tasks consume more credits due to verification steps, but produce better results.\n- **Why It Fits**: Ideal for users within the JetBrains ecosystem seeking a powerful autonomous coding agent with deep IDE integration.\n\n### Devin AI\n\n- **Description**: Devin AI by Cognition Labs is billed as \"the world's first AI software engineer\"βan autonomous agent that handles the entire software development cycle. Devin 2.0 launched in April 2025 with significantly lower pricing ([Devin Website](https://devin.ai)).\n- **Agent Mode**: After receiving a natural language task, Devin generates an implementation plan, writes code, runs it in a sandbox, debugs issues, and continues until completion. Features Interactive Planning, Devin Search for codebase understanding, and automatic repository indexing with architecture diagrams ([Cognition Blog](https://cognition.ai/blog/devin-2)).\n- **AI Model Support**: Proprietary AI models optimized for software engineering. Integrates with Jira, Linear, Slack, and Teams for issue/task management.\n- **Key Features**:\n - Spin up multiple parallel Devins, each with cloud-based IDE.\n - Interactive Planning for collaborative task scoping.\n - Devin Search for codebase questions with cited code.\n - Automatic PR creation, review, and responses.\n - Repository wikis with architecture diagrams.\n- **Pricing**: Core ($20/month + $2.25/ACU), Team ($500/month, 250 ACUs included, $2/ACU extra), Enterprise (custom). An ACU equals ~15 minutes of active Devin work ([Devin Pricing](https://devin.ai/pricing)).\n- **Usage Limits**: ACU-based (Agent Compute Units). Devin 2.0 completes 83% more tasks per ACU than its predecessor.\n- **Why It Fits**: Best for organizations wanting a fully autonomous AI software engineer that handles complete tasks end-to-end.\n\n### Augment Code\n\n- **Description**: Augment Code is a developer AI platform that deeply indexes your codebase to power code completions, natural-language instructions, and autonomous agents. Uses intelligent multi-model architecture, routing to optimal models. Claude Sonnet 4.5 is the default model as of late 2025 ([Augment Website](https://www.augmentcode.com)).\n- **Agent Mode**: The Agent introduces Memories that automatically update and persist across conversations. Can access GitHub, Jira, Confluence, Notion, Linear, and more through native tools, plus full MCP support ([Augment Product](https://www.augmentcode.com/product)).\n- **AI Model Support**: Intelligent multi-model architecture routing to optimal models. Supports Claude Sonnet 4.5 (default), GPT-4o, and others.\n- **Key Features**:\n - Industry-leading context capacityβtwice that of comparable tools.\n - 200K context window for better codebase understanding.\n - Memories feature that persists context across conversations.\n - Integrates with VS Code, JetBrains, and Vim/Neovim.\n - Full MCP support for Vercel, Cloudflare, and other integrations.\n- **Pricing**: Credit-based model (since October 2025). Trial (30,000 credits), Indie ($20/month, 40,000 credits), Developer ($50/month, more credits), Enterprise (custom). Top-up credits valid for 12 months ([Augment Pricing](https://www.augmentcode.com/pricing)).\n- **Usage Limits**: Credit-based reflecting actual compute cost. Users notified when approaching limits.\n- **Why It Fits**: Excellent for teams needing deep codebase understanding with persistent AI memory and broad tool integrations.\n\n### Qodo (formerly CodiumAI)\n\n- **Description**: Qodo is a quality-first AI code review platform recognized as a Visionary in the 2025 Gartner Magic Quadrant for AI Code Assistants. Specialized agents focus on testing, code analysis, and automated code improvement ([Qodo Website](https://www.qodo.ai)).\n- **Agent Mode**: Multiple specialized agentsβQodo Gen (code generation and tests in IDE), Qodo Merge (open-source PR agent for reviews), Qodo Command (terminal/CI scripted agents), Qodo Cover (repository analysis and test generation), Qodo Aware (codebase intelligence) ([Qodo Pricing](https://www.qodo.ai/pricing)).\n- **AI Model Support**: Supports GPT-4o, Claude Opus, and other models. Premium models consume more credits.\n- **Key Features**:\n - PR review scanning every pull request, ranking issues by severity.\n - Inline chats in GitHub, GitLab, and Bitbucket.\n - Test coverage improvement through Qodo Cover.\n - Full SDLC coverage.\n - SOC 2 Type II-audited; deploy SaaS, on-prem, VPC, or air-gapped.\n- **Pricing**: Developer (Free, 75 PRs + 250 credits/month), Teams ($30/user/month, 2,500 credits), Enterprise ($45/user, SSO, priority support, on-prem options) ([Qodo Pricing](https://www.qodo.ai/pricing)).\n- **Usage Limits**: Credits reset monthly. 40K+ weekly active users.\n- **Why It Fits**: Perfect for teams prioritizing code quality, testing, and automated PR reviews.\n\n### PearAI\n\n- **Description**: PearAI is an open-source AI code editor (fork of VS Code) with AI chat, coding agent, and AI debugging. Uses PearAI Router to connect to highest-performing AI models ([PearAI Website](https://www.trypear.ai)).\n- **Agent Mode**: Coding agent can automatically implement features and fix bugs. Integration with Aider CLI and Roo Code/Cline as coding agents ([PearAI GitHub](https://github.com/trypear/pearai-app)).\n- **AI Model Support**: PearAI Router automatically selects best-performing models. Select 'PearAI Model' for optimal performance.\n- **Key Features**:\n - Familiar VS Code UI with advanced AI capabilities.\n - Codebase context awareness (stored locally).\n - CMD+I for inline editing, CMD+L for new chat.\n - @codebase to retrieve relevant snippets.\n - PearAI Login and Launch (coming soon).\n- **Pricing**: Free with BYOK, or $15/month for server access ([PearAI Website](https://www.trypear.ai)).\n- **Usage Limits**: Based on chosen API provider.\n- **Why It Fits**: Great open-source option for users wanting VS Code familiarity with integrated AI agents.\n\n### Roo Code\n\n- **Description**: Roo Code is an open-source VS Code extension (started as fork of Cline) providing a whole dev team of AI agents with custom modes/personas. Features Cloud Agents and Roomote Control for remote task management ([Roo Code Website](https://roocode.com)).\n- **Agent Mode**: Multi-agent modes with specialized AI personalitiesβsecurity expert, performance optimizer, documentation writer, QA engineer. Boomerang tasks and Git-like checkpointing system ([Roo Code GitHub](https://github.com/RooCodeInc/Roo-Code)).\n- **AI Model Support**: Open-source and fully customizable; integrate any AI model (OpenAI, Anthropic, local LLMs via Ollama).\n- **Key Features**:\n - Custom AI modes for different types of work.\n - Multi-file edits with project-wide refactoring.\n - Permission-based file changes and command execution.\n - Roomote Control for remote VS Code control.\n - Cloud Agents accessible from web, Slack, or GitHub.\n - Code stays local unless connecting to external API.\n- **Pricing**: Free and open-source (pay only for API usage). Cloud Agents: $5/hour while running ([Roo Code Pricing](https://roocode.com/pricing)).\n- **Usage Limits**: API usage-based for models; Cloud Agents billed hourly.\n- **Why It Fits**: Ideal for teams wanting specialized AI agents with deep customization and multi-persona support.\n\n### Tabnine\n\n- **Description**: Tabnine provides AI-powered coding assistance with a focus on enterprise security and compliance. Won \"Best Innovation in AI Coding\" at 2025 AI TechAwards for Code Review Agent ([Tabnine Website](https://www.tabnine.com)).\n- **Agent Mode**: Org-Native Agents including Code Review Agent (catches defects, style issues, policy violations at PR time) and AI Test Agent. Image-to-Code converts Figma mockups, ER diagrams, or flowcharts into React components, SQL scripts, or orchestration code.\n- **AI Model Support**: Supports leading LLMs from Anthropic, OpenAI, Google, Meta, Mistral. Enterprise admins can register private endpoints for Llama 3, Claude 4, Gemini 2.5, or internal models ([Tabnine Pricing](https://www.tabnine.com/pricing)).\n- **Key Features**:\n - AI chat supporting every SDLC step.\n - 600+ programming languages support.\n - Flexible deployment: SaaS, VPC, on-premises, or air-gapped.\n - GDPR, SOC 2, ISO 27001 compliance.\n - Zero code retention.\n- **Pricing**: Free (basic completions, local), Pro ($12/user/month, 90-day trial, best-in-class models), Enterprise ($39/user/month, private deployment, fine-tuned models) ([Tabnine Pricing](https://www.tabnine.com/pricing)).\n- **Usage Limits**: Based on plan tier.\n- **Why It Fits**: Best for enterprises requiring private deployment, compliance, and specialized code review agents.\n\n### Replit Agent\n\n- **Description**: Replit is an AI-powered development platform with the Replit Agent for autonomous code generation, completion, and debugging. Effort-based pricing introduced June 2025 ([Replit Website](https://replit.com)).\n- **Agent Mode**: The Agent writes production-ready code, evolves it as you iterate, and handles complete development tasks. Features high-power model option and extended thinking for complex problems ([Replit Blog](https://blog.replit.com/effort-based-pricing)).\n- **AI Model Support**: Claude Sonnet 3.7, OpenAI GPT-4o, and other advanced models available with Core plan.\n- **Key Features**:\n - Built-in Authentication, Database, Hosting, and Monitoring.\n - Services like Stripe or OpenAI plug in seamlessly.\n - Multi-language support (Python, JavaScript, TypeScript, Java, C++, Go).\n - One-click deployment for web apps, APIs, and static sites.\n - Browser-based developmentβno local setup required.\n- **Pricing**: Starter (Free, limited AI, 3 public apps), Replit Core ($20-25/month, $25 credits, ~100 Agent checkpoints, full AI access), Teams ($35-40/user/month, $40 credits, RBAC), Enterprise (custom) ([Replit Pricing](https://replit.com/pricing)).\n- **Usage Limits**: Credit-based covering AI usage, deployments, and cloud services. Simple changes ~$0.25; complex tasks scale accordingly.\n- **Why It Fits**: Perfect for browser-based development with integrated deployment and AI agent capabilities.\n\n### Amazon Q Developer\n\n- **Description**: Amazon Q Developer (formerly CodeWhisperer) is AWS's AI assistant for software development with agentic capabilities for multi-step tasks ([Amazon Q Developer](https://aws.amazon.com/q/developer)).\n- **Agent Mode**: Autonomous agents can implement features, document, test, review, refactor code, and perform software upgrades. Session-aware for multi-step tasks.\n- **AI Model Support**: Through Amazon Bedrock, supports Claude Sonnet 4, Opus 4, and other models.\n- **Key Features**:\n - Code suggestions and reference tracking for open-source snippets.\n - Security scans and vulnerability detection.\n - Strong AWS service integration.\n - Works with VS Code, JetBrains, Visual Studio, Eclipse.\n - SOC, ISO, HIPAA, and PCI compliant.\n- **Pricing**: Free (1,000 LOC upgrades/month, 50 agentic requests/month), Pro ($19/user/month, 1,000 agentic requests, 4,000 LOC, data isolation, IP indemnity) ([Amazon Q Pricing](https://aws.amazon.com/q/developer/pricing)).\n- **Usage Limits**: Overage at $0.003 per LOC for code transformation.\n- **Why It Fits**: Ideal for AWS users needing cloud-integrated CLI tools with enterprise compliance.\n\n## Additional Editors Considered\n\n- **Tabby**: Open-source, self-hosted AI coding assistant with agentic workflows. Model support varies based on configuration.\n- **Sourcegraph Cody**: AI coding assistant with codebase-wide context. Integrates with various IDEs and supports multiple LLMs.\n- **Goose**: Open-source (Apache 2.0) AI agent framework from Block that runs locally and supports any LLM. Fully autonomous with extensible capabilities.\n- **Antigravity**: Released November 2025, free public preview powered by Gemini 3 Pro + Claude Sonnet 4.5 + GPT-OSS. Features Editor View and Agent Manager modes.\n- **CodeGPT**: AI coding agent platform for VS Code, JetBrains, and Cursor with repository-wide context and multi-model support.\n\n## Comparison Table\n\n| **AI Code Editor** | **Open-Source** | **AI Model Support** | **Pricing** | **Usage Limits** | **Key Strengths** | **Best For** |\n|--------------------|-----------------|----------------------|-------------|------------------|-------------------|--------------|\n| **Cursor** | No | GPT-5, Claude Opus 4/Sonnet 4, Gemini 2.5 Pro, Grok 4 | Free tier, Pro $20/mo, Pro+ $60/mo, Ultra $200/mo | Credit-based, Pro: $20 pool; Ultra: 5,000 agent requests | AI-first IDE, advanced agent mode, multi-model support | Complex multi-file projects with agentic workflows |\n| **GitHub Copilot** | No (Chat extension open-source) | GPT-5 mini, GPT-4.1, Claude Opus 4 (Pro+) | Free tier, Pro $10/mo, Pro+ $39/mo, Enterprise $39/user | Premium requests: Free 50, Pro 300, Pro+ 1,500 | Widespread adoption, reliable agent mode, GitHub integration | Users needing guaranteed model access and issue automation |\n| **Windsurf** | No | SWE-1, SWE-1-lite (unlimited), Claude Sonnet 4.5, GPT-4o | Free tier, Pro $15/mo, Teams $30/user, Enterprise $60/user | Credits per prompt; SWE-1-lite/mini unlimited | First agentic IDE, Cascade agent, deep context awareness | Autonomous task execution with affordable pricing |\n| **Zed** | Yes | GPT-5, Gemini 2.5, Anthropic models, Ollama | Token-based, Pro $5/mo credit, BYOK free | Token-based billing at API rate +10% | Fastest editor (Rust), open-source, agentic editing | Performance-focused users with open-source preference |\n| **Cline** | Yes | Any LLM (Claude Sonnet 4.5, GPT-4o, Gemini, local models) | Free extension, pay for API | API usage-based | Plan/Act modes, full control, MCP support | Open-source autonomous coding with user approval |\n| **Continue** | Yes | Any LLM (OpenAI, Anthropic, Ollama, local) | Free, pay for API | API usage-based | Background agents, terminal-native, highly customizable | Tech-sav | |
| [2025-12-28T03:04:14.808Z] [INFO] vy users wanting open-source flexibility |\n| **JetBrains Junie** | No | Multiple LLMs, BYOK supported | AI Free, AI Pro, AI Ultimate, AI Enterprise | Quota-based with AI Credits | Deep IDE integration, quality-focused agent | JetBrains ecosystem users |\n| **Devin AI** | No | Proprietary models | Core $20/mo + $2.25/ACU, Team $500/mo | ACU-based (~15 min active work) | Fully autonomous AI engineer, parallel Devins | Full end-to-end autonomous development |\n| **Augment Code** | No | Claude Sonnet 4.5 (default), multi-model | Indie $20/mo, Developer $50/mo | Credit-based | Memories feature, 200K context, broad integrations | Teams needing persistent AI memory |\n| **Qodo** | Partially (Qodo Merge) | GPT-4o, Claude Opus | Free tier, Teams $30/user, Enterprise $45/user | Credits reset monthly | Quality-first, PR review, test generation | Code quality and automated reviews |\n| **PearAI** | Yes | PearAI Router (auto-selects best) | Free (BYOK) or $15/mo | API usage-based | VS Code familiar, integrated agents | Open-source with simple pricing |\n| **Roo Code** | Yes | Any LLM (OpenAI, Anthropic, Ollama) | Free, Cloud Agents $5/hr | API usage-based | Multi-persona agents, custom modes | Specialized AI teams with deep customization |\n| **Tabnine** | No | Multiple LLMs, private model support | Free, Pro $12/user, Enterprise $39/user | Plan-based | Enterprise security, code review agent | Enterprises requiring compliance and private deployment |\n| **Replit Agent** | No | Claude Sonnet 3.7, GPT-4o | Free tier, Core $20-25/mo, Teams $35-40/user | Credit-based (~$0.25/checkpoint) | Browser-based, integrated deployment | Browser-based development with AI |\n| **Amazon Q Developer** | No | Claude models via Bedrock | Free tier, Pro $19/user | Agentic requests: Free 50, Pro 1,000 | AWS integration, enterprise compliance | AWS users and cloud workflows |\n\n## Analysis and Recommendations\n\nThe AI code editor landscape has matured significantly in 2025, with clear leaders emerging in different categories:\n\n**For Mainstream AI Development**:\n- **Cursor** has become the de facto standard for AI-native development with its polished agent mode and broad model support at $20/month.\n- **GitHub Copilot** remains the most cost-effective at $10/month with unmatched adoption and strong GitHub integration.\n\n**For Autonomous AI Engineers**:\n- **Devin AI** leads in full autonomy, handling complete development cycles from planning to deployment.\n- **Windsurf** offers the most accessible agentic IDE experience with affordable pricing.\n\n**For Open-Source Enthusiasts**:\n- **Cline** and **Continue** provide maximum flexibility and control with zero lock-in.\n- **Zed** offers the fastest performance with native AI integration.\n- **Roo Code** excels with multi-persona AI agents and deep customization.\n\n**For Enterprise Users**:\n- **Tabnine** provides the strongest enterprise security and compliance.\n- **JetBrains Junie** offers deep IDE integration with quality-focused agents.\n- **Amazon Q Developer** is optimal for AWS-integrated workflows.\n\n**Recommendations by Use Case**:\n- **For guaranteed model access**: Choose **GitHub Copilot Pro** ($10/month) for affordability or **Cursor Pro** ($20/month) for the most polished experience.\n- **For open-source with full control**: Opt for **Cline** or **Continue** with your preferred models.\n- **For maximum performance**: **Zed** offers speed and agent mode with flexible model support.\n- **For full autonomy**: **Devin AI** handles complete software engineering tasks end-to-end.\n- **For code quality focus**: **Qodo** specializes in testing and PR reviews.\n- **For AWS users**: **Amazon Q Developer** provides seamless cloud integration.\n\n## References\n\nFor further details, explore:\n- [Cursor Website](https://cursor.com) | [Pricing](https://cursor.com/pricing)\n- [GitHub Copilot](https://github.com/features/copilot) | [Plans](https://github.com/features/copilot/plans)\n- [Windsurf Website](https://windsurf.com) | [Pricing](https://windsurf.com/pricing)\n- [Zed Website](https://zed.dev) | [Pricing](https://zed.dev/pricing) | [AI](https://zed.dev/ai)\n- [Cline Website](https://cline.bot) | [Pricing](https://cline.bot/pricing)\n- [Continue Website](https://www.continue.dev) | [Documentation](https://docs.continue.dev)\n- [JetBrains Junie](https://www.jetbrains.com/junie) | [AI Pricing](https://www.jetbrains.com/ai-ides/buy/)\n- [Devin AI](https://devin.ai) | [Pricing](https://devin.ai/pricing)\n- [Augment Code](https://www.augmentcode.com) | [Pricing](https://www.augmentcode.com/pricing)\n- [Qodo](https://www.qodo.ai) | [Pricing](https://www.qodo.ai/pricing)\n- [PearAI](https://www.trypear.ai) | [GitHub](https://github.com/trypear/pearai-app)\n- [Roo Code](https://roocode.com) | [Pricing](https://roocode.com/pricing)\n- [Tabnine](https://www.tabnine.com) | [Pricing](https://www.tabnine.com/pricing)\n- [Replit](https://replit.com) | [Pricing](https://replit.com/pricing)\n- [Amazon Q Developer](https://aws.amazon.com/q/developer) | [Pricing](https://aws.amazon.com/q/developer/pricing)\n","numLines":323,"startLine":1,"totalLines":323}}} | |
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| "content": "{\"body\":\"## Summary\\n\\nThis PR addresses issue #3 by:\\n\\n1. **Updating ai-agentic-cli-tools.md** with the latest December 2025 research and fact-checked information\\n2. **Creating ai-agentic-cli-tools-features.md** with a comprehensive feature-by-feature comparison\\n\\n### Changes to ai-agentic-cli-tools.md\\n\\n- **Added new tools**: OpenCode (41K stars), Qwen Code, Droid by Factory, Roo Code, OpenHands\\n- **Updated GitHub star counts** from live sources:\\n - Claude Code: 49K stars\\n - Gemini CLI: 88.5K stars (most starred)\\n - OpenAI Codex CLI: 54.7K stars\\n - Cline: 50K+ stars (fastest-growing)\\n - Goose: 24.8K stars\\n - OpenCode: 41K stars\\n - Roo Code: 21.4K stars\\n- **Updated pricing information**:\\n - Claude Opus 4.5: $5/$25 per MTok (67% reduction from Opus 4.1)\\n - Warp Build plan: $20/mo with BYOK support\\n - Kiro GA pricing: Free tier with 500 bonus credits\\n - Gemini 3 Flash: $0.50/$3 per MTok\\n- **Added new features**:\\n - GPT-5.2-Codex (December 2025) with agent skills\\n - Gemini 3 Flash with 78% SWE-bench score\\n - Linux Foundation Agentic AI Foundation (AAIF) membership for Goose\\n - Cline recognized as GitHub's fastest-growing AI project\\n- **Updated model availability**: GPT-5 series, Claude 4 series, Gemini 3, Qwen3-Coder\\n- **Reorganized comparison table** with GitHub stars column\\n\\n### New file: ai-agentic-cli-tools-features.md\\n\\nA comprehensive feature comparison document with 14 detailed categories:\\n\\n1. Agent Capabilities\\n2. AI Model Support\\n3. Context & Memory\\n4. File & Code Operations\\n5. Version Control Integration\\n6. IDE & Editor Integration\\n7. Terminal & Shell Features\\n8. Extensibility & Customization\\n9. Enterprise & Team Features\\n10. Pricing & Free Tiers\\n11. Open Source & Licensing\\n12. Quick Feature Summary by Use Case\\n13. Benchmark Performance (Terminal-Bench, SWE-bench)\\n14. MCP Ecosystem Overview\\n\\n### Research Sources\\n\\nAll facts were verified using web searches to official sources:\\n- GitHub repositories for star counts and release notes\\n- Official documentation and pricing pages\\n- Announcement blog posts (GPT-5.2-Codex, Claude Opus 4.5, Gemini 3 Flash)\\n- Linux Foundation press releases (AAIF formation)\\n- Benchmark results (Terminal-Bench, SWE-bench)\\n\\nFixes #3\\n\\nπ€ Generated with [Claude Code](https://claude.com/claude-code)\",\"files\":[{\"path\":\"ai-agentic-cli-tools-features.md\",\"additions\":271,\"deletions\":0},{\"path\":\"ai-agentic-cli-tools.md\",\"additions\":247,\"deletions\":137}],\"title\":\"Update AI agentic CLI tools with December 2025 research and add features comparison\"}", | |
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| "content": "Web search results for query: \"unified AI API provider multiple models OpenAI Anthropic Google 2025\"\n\nLinks: [{\"title\":\"OpenRouter: The Universal API for AI Development in 2025 | CodeGPT\",\"url\":\"https://www.codegpt.co/blog/openrouter-universal-api-ai-development\"},{\"title\":\"Foundations: Providers and Models\",\"url\":\"https://ai-sdk.dev/docs/foundations/providers-and-models\"},{\"title\":\"Unified API (OpenAI compat) Β· Cloudflare AI Gateway docs\",\"url\":\"https://developers.cloudflare.com/ai-gateway/usage/chat-completion/\"},{\"title\":\"Top 11 LLM API Providers in 2025\",\"url\":\"https://www.helicone.ai/blog/llm-api-providers\"},{\"title\":\"Top One API Alternatives: The Best Unified LLM APIs to Use in 2025\",\"url\":\"https://sider.ai/blog/ai-tools/top-one-api-alternatives-the-best-unified-llm-apis-to-use-in-2025\"},{\"title\":\"AI SDK Providers: Anthropic\",\"url\":\"https://ai-sdk.dev/providers/ai-sdk-providers/anthropic\"},{\"title\":\"AI APIs in 2025\",\"url\":\"https://www.builder.io/blog/ai-apis\"},{\"title\":\"AI Gateway Provider\",\"url\":\"https://ai-sdk.dev/providers/ai-sdk-providers/ai-gateway\"},{\"title\":\"AI/ML API | Promptfoo\",\"url\":\"https://www.promptfoo.dev/docs/providers/aimlapi/\"},{\"title\":\"OpenAI-Compatible API\",\"url\":\"https://vercel.com/docs/ai-gateway/openai-compat\"}]\n\nHere are the search results for unified AI API providers that support multiple models from OpenAI, Anthropic, Google, and other providers in 2025:\n\n## Key Unified AI API Providers\n\n### OpenRouter\nIn an increasingly fragmented AI landscape where new models emerge weekly from OpenAI, Anthropic, Google, xAI, and dozens of other providers, OpenRouter has become the essential infrastructure layer that makes the entire ecosystem usable.(no content)It offers a single, standardized API to access 500+ models from 60+ providers and is fully OpenAI compatibleβdevelopers can \"just change the endpoint URL\" in existing code.(no content)The platform allows teams to \"A/B test multiple models quickly\" and \"switch between hundreds of models without changing your code\".(no content)Developers choose OpenRouter for its ability to provide easy access to multiple AI models through a single API interface. The platform offers automatic failovers and competitive pricing while eliminating the need to integrate and manage multiple provider APIs separately.\n\n### Vercel AI SDK / AI Gateway\nAI SDK Core offers a standardized approach to interacting with LLMs through a language model specification that abstracts differences between providers. This unified interface allows you to switch between providers with ease while using the same API for all providers.(no content)The AI Gateway provider connects you to models from multiple AI providers through a single interface. Instead of integrating with each provider separately, you can access OpenAI, Anthropic, Google, Meta, xAI, and other providers and their models.(no content)The AI Gateway supports models from OpenAI, Anthropic, Google, Meta, xAI, Mistral, DeepSeek, Amazon Bedrock, Cohere, Perplexity, Alibaba, and other providers.\n\n### Cloudflare AI Gateway\nCloudflare AI Gateway supports providers including Anthropic, OpenAI, Groq, Mistral, Cohere, Perplexity, Workers AI, Google-AI-Studio, Google Vertex AI, xAI, DeepSeek, Cerebras, and Baseten.\n\n### AI/ML API\nAI/ML API provides access to 300+ AI models through a unified OpenAI-compatible interface, including state-of-the-art models from OpenAI, Anthropic, Google, Meta, and more.(no content)AI/ML API's endpoints are compatible with OpenAI's API, which means all parameters available in the OpenAI provider work with AI/ML API.\n\n## Key Benefits of Unified APIs\nThese aggregator APIs promise a single endpoint, one billing setup, and easy model switching. They abstract away providers, reduce vendor lock-in, and keep your app shipping even when one provider rate-limits or changes policies.(no content)Instead of tracking \"multiple bills from different vendors,\" developers receive \"one consolidated invoice\". This is critical for cost analysis and observability in any project.\n\n\nREMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks." | |
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| "title": "OpenRouter: The Universal API for AI Development in 2025 | CodeGPT", | |
| "url": "https://www.codegpt.co/blog/openrouter-universal-api-ai-development" | |
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| { | |
| "title": "Foundations: Providers and Models", | |
| "url": "https://ai-sdk.dev/docs/foundations/providers-and-models" | |
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| "title": "Unified API (OpenAI compat) Β· Cloudflare AI Gateway docs", | |
| "url": "https://developers.cloudflare.com/ai-gateway/usage/chat-completion/" | |
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| "title": "Top 11 LLM API Providers in 2025", | |
| "url": "https://www.helicone.ai/blog/llm-api-providers" | |
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| "title": "Top One API Alternatives: The Best Unified LLM APIs to Use in 2025", | |
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| "url": "https://www.builder.io/blog/ai-apis" | |
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| "url": "https://www.promptfoo.dev/docs/providers/aimlapi/" | |
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| "Here are the search results for unified AI API providers that support multiple models from OpenAI, Anthropic, Google, and other providers in 2025:\n\n## Key Unified AI API Providers\n\n### OpenRouter\nIn an increasingly fragmented AI landscape where new models emerge weekly from OpenAI, Anthropic, Google, xAI, and dozens of other providers, OpenRouter has become the essential infrastructure layer that makes the entire ecosystem usable.(no content)It offers a single, standardized API to access 500+ models from 60+ providers and is fully OpenAI compatibleβdevelopers can \"just change the endpoint URL\" in existing code.(no content)The platform allows teams to \"A/B test multiple models quickly\" and \"switch between hundreds of models without changing your code\".(no content)Developers choose OpenRouter for its ability to provide easy access to multiple AI models through a single API interface. The platform offers automatic failovers and competitive pricing while eliminating the need to integrate and manage multiple provider APIs separately.\n\n### Vercel AI SDK / AI Gateway\nAI SDK Core offers a standardized approach to interacting with LLMs through a language model specification that abstracts differences between providers. This unified interface allows you to switch between providers with ease while using the same API for all providers.(no content)The AI Gateway provider connects you to models from multiple AI providers through a single interface. Instead of integrating with each provider separately, you can access OpenAI, Anthropic, Google, Meta, xAI, and other providers and their models.(no content)The AI Gateway supports models from OpenAI, Anthropic, Google, Meta, xAI, Mistral, DeepSeek, Amazon Bedrock, Cohere, Perplexity, Alibaba, and other providers.\n\n### Cloudflare AI Gateway\nCloudflare AI Gateway supports providers including Anthropic, OpenAI, Groq, Mistral, Cohere, Perplexity, Workers AI, Google-AI-Studio, Google Vertex AI, xAI, DeepSeek, Cerebras, and Baseten.\n\n### AI/ML API\nAI/ML API provides access to 300+ AI models through a unified OpenAI-compatible interface, including state-of-the-art models from OpenAI, Anthropic, Google, Meta, and more.(no content)AI/ML API's endpoints are compatible with OpenAI's API, which means all parameters available in the OpenAI provider work with AI/ML API.\n\n## Key Benefits of Unified APIs\nThese aggregator APIs promise a single endpoint, one billing setup, and easy model switching. They abstract away providers, reduce vendor lock-in, and keep your app shipping even when one provider rate-limits or changes policies.(no content)Instead of tracking \"multiple bills from different vendors,\" developers receive \"one consolidated invoice\". This is critical for cost analysis and observability in any project." | |
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| "content": "Web search results for query: \"AI API aggregator gateway services 2025 OpenRouter alternatives\"\n\nLinks: [{\"title\":\"Top 5 AI Gateways for OpenAI: OpenRouter Alternatives\",\"url\":\"https://research.aimultiple.com/ai-gateway/\"},{\"title\":\"Best OpenRouter Alternatives | Eden AI\",\"url\":\"https://www.edenai.co/post/best-alternatives-to-openrouter\"},{\"title\":\"OpenRouter Alternatives in 2025\",\"url\":\"https://www.helicone.ai/blog/openrouter-alternatives\"},{\"title\":\"7 Best OpenRouter Alternatives 2025 | ShareAI\",\"url\":\"https://shareai.now/blog/alternatives/openrouter-alternatives/\"},{\"title\":\"Best OpenRouter Alternatives for deepseek 2025\",\"url\":\"https://www.byteplus.com/en/topic/375936\"},{\"title\":\"Top Openrouter.ai Alternatives in 2025\",\"url\":\"https://topai.tools/alternatives/openrouter-ai\"},{\"title\":\"Best OpenRouter Alternatives for Production AI Systems\",\"url\":\"https://www.truefoundry.com/blog/openrouter-alternatives\"},{\"title\":\"OpenRouter Alternatives in 2025 | Best OpenRouter Alternatives - Toolify\",\"url\":\"https://www.toolify.ai/alternative/openrouter-ai\"},{\"title\":\"Azure API Management (GenAI) Alternatives 2025\",\"url\":\"https://shareai.now/blog/alternatives/azure-api-management-alternatives/\"},{\"title\":\"Exploring OpenRouter Alternatives: Choose the Right LLM API Gateway for Your Projects | by Andy Nguyen | Synthetic Futures | Medium\",\"url\":\"https://medium.com/synthetic-futures/exploring-openrouter-alternatives-choose-the-right-llm-api-gateway-for-your-projects-600171cd722e\"}]\n\nBased on my search, here's an overview of AI API aggregator gateway services and OpenRouter alternatives in 2025:\n\n## Overview\n\nManaging multiple AI model accounts, billing, and API keys can be cumbersome. Model aggregators solve this by offering a single API to switch between different LLMs easily.(no content)OpenRouter is a well-known model aggregator, providing access to multiple AI providers through one unified API.\n\n## Key OpenRouter Alternatives in 2025\n\n### **Helicone AI Gateway**\nHelicone AI Gateway offers zero markup, sub-2-minute setup, production features (health-aware load balancing, auto failover), and built-in observability. Edge caching cuts both cost and latency.(no content)It's Rust-based and focuses on speed and observability.\n\n### **LiteLLM**\nLiteLLM is an open-source alternative designed for users who want more control over their AI integrations. It allows developers to self-host models and manage their API requests, providing greater flexibility than OpenRouter. Unlike proprietary platforms, LiteLLM offers full transparency and customization.(no content)LiteLLM and Kong AI Gateway are the most common self-hosted starting points, with LiteLLM being the fastest to stand up with OpenAI-compatible endpoints.\n\n### **Portkey**\nPortkey is another strong alternative, offering a platform to manage and optimize LLM usage efficiently with features such as caching and rate limiting. Its smart routing capability automatically selects the best model for each request. It helps reduce API costs through caching and optimized routing and provides advanced monitoring tools.(no content)Portkey is ideal for teams needing enterprise guardrails and compliance features, and is worth the premium for regulated industries.\n\n### **Kong AI Gateway**\nKong AI Gateway is a free, open-source alternative to OpenRouter, offering a scalable, customizable, self-hosted LLM aggregation solution. However, it may not appeal to those seeking a hassle-free, managed service due to its need for additional maintenance and setup.(no content)Kong AI Gateway adds AI plugins (prompt templates, data governance, content safety) to a high-performance OSS gatewayβideal if you want self-host plus plugin flexibility.\n\n### **Eden AI**\nEden AI positions itself as a comprehensive AI platform, going beyond just LLMs to offer a unified API for a wide array of AI services, including image generation, translation, speech-to-text, and more. This makes it an excellent choice for developers building applications that require multiple AI functionalities.\n\n### **Together AI**\nTogether AI is cloud-managed and emphasizes open-source models and low latency.(no content)TogetherAI functions as both an AI provider and a hardware vendor.\n\n### **Groq & SambaNova**\nGroq and SambaNova operate on proprietary, purpose-built hardware (LPUs and RDUs), which is explicitly optimized for low-latency inference.(no content)Groq offers ultra-fast inference, ideal for latency-sensitive tasks.\n\n## Why Consider Alternatives?\n\nOpenRouter has a 5% markupβon $100K/month spend, you're paying $5K yearly just for routing. It has limited observability, whereas robust observability is table-stakes in this market. You need per-user token tracking, latency distributions, and cost optimization insights. It's also closed-source with no visibility into what they store in house or potential security vulnerabilities.(no content)While OpenRouter is effective for simplifying access to multiple models, it is fundamentally designed as a public aggregation layer. As organizations scale AI workloads into production, this architecture can introduce limitations. For enterprises where compliance, security, and deep debugging are non-negotiable, several architectural limitations often necessitate a move toward more robust, dedicated AI Gateways.\n\n\nREMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks." | |
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| "title": "Best OpenRouter Alternatives | Eden AI", | |
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| "title": "7 Best OpenRouter Alternatives 2025 | ShareAI", | |
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| "title": "OpenRouter Alternatives in 2025 | Best OpenRouter Alternatives - Toolify", | |
| "url": "https://www.toolify.ai/alternative/openrouter-ai" | |
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| "url": "https://shareai.now/blog/alternatives/azure-api-management-alternatives/" | |
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| { | |
| "title": "Exploring OpenRouter Alternatives: Choose the Right LLM API Gateway for Your Projects | by Andy Nguyen | Synthetic Futures | Medium", | |
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| "Based on my search, here's an overview of AI API aggregator gateway services and OpenRouter alternatives in 2025:\n\n## Overview\n\nManaging multiple AI model accounts, billing, and API keys can be cumbersome. Model aggregators solve this by offering a single API to switch between different LLMs easily.(no content)OpenRouter is a well-known model aggregator, providing access to multiple AI providers through one unified API.\n\n## Key OpenRouter Alternatives in 2025\n\n### **Helicone AI Gateway**\nHelicone AI Gateway offers zero markup, sub-2-minute setup, production features (health-aware load balancing, auto failover), and built-in observability. Edge caching cuts both cost and latency.(no content)It's Rust-based and focuses on speed and observability.\n\n### **LiteLLM**\nLiteLLM is an open-source alternative designed for users who want more control over their AI integrations. It allows developers to self-host models and manage their API requests, providing greater flexibility than OpenRouter. Unlike proprietary platforms, LiteLLM offers full transparency and customization.(no content)LiteLLM and Kong AI Gateway are the most common self-hosted starting points, with LiteLLM being the fastest to stand up with OpenAI-compatible endpoints.\n\n### **Portkey**\nPortkey is another strong alternative, offering a platform to manage and optimize LLM usage efficiently with features such as caching and rate limiting. Its smart routing capability automatically selects the best model for each request. It helps reduce API costs through caching and optimized routing and provides advanced monitoring tools.(no content)Portkey is ideal for teams needing enterprise guardrails and compliance features, and is worth the premium for regulated industries.\n\n### **Kong AI Gateway**\nKong AI Gateway is a free, open-source alternative to OpenRouter, offering a scalable, customizable, self-hosted LLM aggregation solution. However, it may not appeal to those seeking a hassle-free, managed service due to its need for additional maintenance and setup.(no content)Kong AI Gateway adds AI plugins (prompt templates, data governance, content safety) to a high-performance OSS gatewayβideal if you want self-host plus plugin flexibility.\n\n### **Eden AI**\nEden AI positions itself as a comprehensive AI platform, going beyond just LLMs to offer a unified API for a wide array of AI services, including image generation, translation, speech-to-text, and more. This makes it an excellent choice for developers building applications that require multiple AI functionalities.\n\n### **Together AI**\nTogether AI is cloud-managed and emphasizes open-source models and low latency.(no content)TogetherAI functions as both an AI provider and a hardware vendor.\n\n### **Groq & SambaNova**\nGroq and SambaNova operate on proprietary, purpose-built hardware (LPUs and RDUs), which is explicitly optimized for low-latency inference.(no content)Groq offers ultra-fast inference, ideal for latency-sensitive tasks.\n\n## Why Consider Alternatives?\n\nOpenRouter has a 5% markupβon $100K/month spend, you're paying $5K yearly just for routing. It has limited observability, whereas robust observability is table-stakes in this market. You need per-user token tracking, latency distributions, and cost optimization insights. It's also closed-source with no visibility into what they store in house or potential security vulnerabilities.(no content)While OpenRouter is effective for simplifying access to multiple models, it is fundamentally designed as a public aggregation layer. As organizations scale AI workloads into production, this architecture can introduce limitations. For enterprises where compliance, security, and deep debugging are non-negotiable, several architectural limitations often necessitate a move toward more robust, dedicated AI Gateways." | |
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| "content": "Web search results for query: \"OpenRouter pricing API models December 2025\"\n\nLinks: [{\"title\":\"Pricing - OpenRouter | OpenRouter\",\"url\":\"https://openrouter.ai/pricing\"},{\"title\":\"OpenRouter Review 2025: Unified AI Model API, Pricing & Privacy\",\"url\":\"https://skywork.ai/blog/openrouter-review-2025-unified-ai-model-api-pricing-privacy/\"},{\"title\":\"Models | OpenRouter\",\"url\":\"https://openrouter.ai/models\"},{\"title\":\"OpenRouter Models | Access 400+ AI Models Through One API | OpenRouter | Documentation\",\"url\":\"https://openrouter.ai/docs/guides/overview/models\"},{\"title\":\"OpenRouter Models Pricing Calculator | Compare Model Costs Instantly\",\"url\":\"https://invertedstone.com/calculators/openrouter-pricing\"},{\"title\":\"OpenRouter Review 2025: API Gateway, Latency & Pricing Compared\",\"url\":\"https://skywork.ai/blog/openrouter-review-2025-api-gateway-latency-pricing/\"},{\"title\":\"Top AI Models on OpenRouter 2025: Cost vs Performance Analysis | Complete Guide @ Teamday.ai Blog Top AI Models on OpenRouter 2025: Cost vs Performance Analysis | Complete Guide @ Teamday.ai Blog\",\"url\":\"https://www.teamday.ai/blog/top-ai-models-openrouter-2025\"},{\"title\":\"OpenRouter Review 2025: Unified AI API Models, Pricing & Privacy\",\"url\":\"https://skywork.ai/blog/openrouter-review-2025-2/\"},{\"title\":\"ChatGPT-4o compared to other AI Models | OpenRouter\",\"url\":\"https://openrouter.ai/compare/openai/chatgpt-4o-latest\"},{\"title\":\"OpenRouter\",\"url\":\"https://openrouter.ai/\"}]\n\nHere's what I found about OpenRouter pricing and API models:\n\n## OpenRouter Pricing Overview\n\n### Pricing Model\nOpenRouter does not mark up provider pricing. Pricing shown in the model catalog is what you pay, which is exactly what you will see on provider's websites.\n\n### Billing Options\nPay-as-you-go: You buy credits and use them as you wish. You can automatically top-up your account or do it manually. Enterprise pricing is based on volume, prepayment credits, annual commits, and many other factors.\n\n### Platform Fees (2025)\nAs of mid-2025, OpenRouter simplified its platform fee: credit purchases via card incur a 5.5% fee (minimum $0.80), and crypto purchases a 5% fee with no minimum. OpenRouter removed a fixed Stripe component to make fees more predictable.\n\n### Key Pricing Features\n- When routing/fallback is enabled, you're billed only for the successful model run.\n- Pricing is per token regardless of streaming.\n- They support prepayment credits, volume discounts, annual commits, and invoicing/POs.\n- Pay-as-you-go accepts credit/debit cards, crypto, and bank transfers.\n\n### Model Access\nYou can explore and browse 400+ models and providers on the OpenRouter website, or with their API. You can also subscribe to their RSS feed to stay updated on new models. Their Models API makes the most important information about all LLMs freely available as soon as they confirm it.(no content)All pricing values are in USD per token/request/unit. A value of \"0\" indicates the feature is free.\n\n### Token Pricing Structure\nAI model costs range dramatically from completely free to over $100 per million tokens. Models charge separately for input tokens (what you send) and output tokens (what the model generates), with output typically costing 2-5x more.(no content)Multiple providers offer free tiers including Mistral, DeepSeek, Google, and Meta - giving you plenty of options to experiment and build without any upfront costs.\n\n### 2025 Updates\nFeature velocity is a differentiator, and 2025 saw several notable updates including GPT-5 availability via OpenRouter (August 2025), multimodal input improvements including audio and PDF inputs for apps and API (August 2025), and continued expansion of frontier/open-weight options.(no content)If you're building multi-model features or want unified billing and privacy filters without juggling multiple vendors, OpenRouter is a practical choice. Prices and availability change frequently, so you'll want to verify per-model pages before deploying.\n\nFor current specific model pricing, you can visit [OpenRouter's Models page](https://openrouter.ai/models) or their [Pricing page](https://openrouter.ai/pricing).\n\n\nREMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks." | |
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| "title": "Pricing - OpenRouter | OpenRouter", | |
| "url": "https://openrouter.ai/pricing" | |
| }, | |
| { | |
| "title": "OpenRouter Review 2025: Unified AI Model API, Pricing & Privacy", | |
| "url": "https://skywork.ai/blog/openrouter-review-2025-unified-ai-model-api-pricing-privacy/" | |
| }, | |
| { | |
| "title": "Models | OpenRouter", | |
| "url": "https://openrouter.ai/models" | |
| }, | |
| { | |
| "title": "OpenRouter Models | Access 400+ AI Models Through One API | OpenRouter | Documentation", | |
| "url": "https://openrouter.ai/docs/guides/overview/models" | |
| }, | |
| { | |
| "title": "OpenRouter Models Pricing Calculator | Compare Model Costs Instantly", | |
| "url": "https://invertedstone.com/calculators/openrouter-pricing" | |
| }, | |
| { | |
| "title": "OpenRouter Review 2025: API Gateway, Latency & Pricing Compared", | |
| "url": "https://skywork.ai/blog/openrouter-review-2025-api-gateway-latency-pricing/" | |
| }, | |
| { | |
| "title": "Top AI Models on OpenRouter 2025: Cost vs Performance Analysis | Complete Guide @ Teamday.ai Blog Top AI Models on OpenRouter 2025: Cost vs Performance Analysis | Complete Guide @ Teamday.ai Blog", | |
| "url": "https://www.teamday.ai/blog/top-ai-models-openrouter-2025" | |
| }, | |
| { | |
| "title": "OpenRouter Review 2025: Unified AI API Models, Pricing & Privacy", | |
| "url": "https://skywork.ai/blog/openrouter-review-2025-2/" | |
| }, | |
| { | |
| "title": "ChatGPT-4o compared to other AI Models | OpenRouter", | |
| "url": "https://openrouter.ai/compare/openai/chatgpt-4o-latest" | |
| }, | |
| { | |
| "title": "OpenRouter", | |
| "url": "https://openrouter.ai/" | |
| } | |
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| "Here's what I found about OpenRouter pricing and API models:\n\n## OpenRouter Pricing Overview\n\n### Pricing Model\nOpenRouter does not mark up provider pricing. Pricing shown in the model catalog is what you pay, which is exactly what you will see on provider's websites.\n\n### Billing Options\nPay-as-you-go: You buy credits and use them as you wish. You can automatically top-up your account or do it manually. Enterprise pricing is based on volume, prepayment credits, annual commits, and many other factors.\n\n### Platform Fees (2025)\nAs of mid-2025, OpenRouter simplified its platform fee: credit purchases via card incur a 5.5% fee (minimum $0.80), and crypto purchases a 5% fee with no minimum. OpenRouter removed a fixed Stripe component to make fees more predictable.\n\n### Key Pricing Features\n- When routing/fallback is enabled, you're billed only for the successful model run.\n- Pricing is per token regardless of streaming.\n- They support prepayment credits, volume discounts, annual commits, and invoicing/POs.\n- Pay-as-you-go accepts credit/debit cards, crypto, and bank transfers.\n\n### Model Access\nYou can explore and browse 400+ models and providers on the OpenRouter website, or with their API. You can also subscribe to their RSS feed to stay updated on new models. Their Models API makes the most important information about all LLMs freely available as soon as they confirm it.(no content)All pricing values are in USD per token/request/unit. A value of \"0\" indicates the feature is free.\n\n### Token Pricing Structure\nAI model costs range dramatically from completely free to over $100 per million tokens. Models charge separately for input tokens (what you send) and output tokens (what the model generates), with output typically costing 2-5x more.(no content)Multiple providers offer free tiers including Mistral, DeepSeek, Google, and Meta - giving you plenty of options to experiment and build without any upfront costs.\n\n### 2025 Updates\nFeature velocity is a differentiator, and 2025 saw several notable updates including GPT-5 availability via OpenRouter (August 2025), multimodal input improvements including audio and PDF inputs for apps and API (August 2025), and continued expansion of frontier/open-weight options.(no content)If you're building multi-model features or want unified billing and privacy filters without juggling multiple vendors, OpenRouter is a practical choice. Prices and availability change frequently, so you'll want to verify per-model pages before deploying.\n\nFor current specific model pricing, you can visit [OpenRouter's Models page](https://openrouter.ai/models) or their [Pricing page](https://openrouter.ai/pricing)." | |
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| "content": "Web search results for query: \"Portkey AI gateway pricing features enterprise 2025\"\n\nLinks: [{\"title\":\"Enterprise-grade AI Gateway | Portkey\",\"url\":\"https://portkey.ai/features/ai-gateway\"},{\"title\":\"Portkey | Control Panel for Production AI\",\"url\":\"https://portkey.ai/pricing\"},{\"title\":\"How to choose an AI gateway in 2025\",\"url\":\"https://portkey.ai/blog/how-to-choose-an-ai-gateway-in-2025/\"},{\"title\":\"Production Stack for Gen AI Builders|Portkey\",\"url\":\"https://portkey.ai/\"},{\"title\":\"GitHub - Portkey-AI/gateway: A blazing fast AI Gateway with integrated guardrails. Route to 200+ LLMs, 50+ AI Guardrails with 1 fast & friendly API.\",\"url\":\"https://github.com/Portkey-AI/gateway\"},{\"title\":\"Best AI Gateway Solutions\",\"url\":\"https://portkey.ai/buyers-guide/ai-gateway-solutions\"},{\"title\":\"Best LLM Observability Tools in 2025\",\"url\":\"https://www.firecrawl.dev/blog/best-llm-observability-tools\"},{\"title\":\"Model Pricing and Cost Management - Portkey Docs\",\"url\":\"https://portkey.ai/docs/product/observability/cost-management\"},{\"title\":\"Top 5 LLM Gateways in 2025: The Complete Guide to Choosing the Best AI Gateway\",\"url\":\"https://www.helicone.ai/blog/top-llm-gateways-comparison-2025\"},{\"title\":\"Top 5 AI Gateways for 2026: Building Reliable Multi-Provider AI Infrastructure - DEV Community\",\"url\":\"https://dev.to/kuldeep_paul/top-5-ai-gateways-for-2026-building-reliable-multi-provider-ai-infrastructure-16e3\"}]\n\nBased on the search results, here's what I found about Portkey AI Gateway's pricing, features, and enterprise offerings in 2025:\n\n## Portkey AI Gateway Overview\n\nPortkey equips AI teams with everything they need to go to production - AI Gateway, Observability, Guardrails, Governance, and Prompt Management, all in one platform.\n\n## Pricing Structure\n\nPortkey offers a usage-based pricing model with a free tier for initial development and testing.(no content)Enterprise plans include advanced governance, audit logging, and dedicated regional deployments.(no content)The free tier covers 10,000 requests per month, with paid plans adding advanced routing and analytics.(no content)Portkey starts at $49/month for paid plans.\n\n## Pricing Tiers\n\nThe free tier is perfect for prototyping and testing or evaluating enterprise POCs, but is not suitable for production workloads.(no content)A production tier is great for teams ready to deploy LLM apps in production, though it's not recommended for organizations requiring custom security controls or data residency guarantees.(no content)The enterprise tier is built for organizations with complex compliance needs and high-volume production workloads, offering the full Portkey feature set with enterprise support and multiple deployment configurations.\n\n## Enterprise Features\n\nEnterprise includes Private Cloud Deployment, Data Export to Data Lakes, VPC Hosting, Advanced Compliance (SOC2 Type 2, GDPR, HIPAA), Custom BAAs, and Data Isolation.(no content)The LLM Gateway's enterprise version offers advanced capabilities for org management, governance, security and more out of the box.(no content)Portkey provides role-based access control, audit logging, compliance reporting, and policy enforcement. Organizations with regulatory requirements or complex internal governance find these features essential.(no content)Virtual keys and budget management enable different teams to manage independent API budgets without exposing actual credentials.\n\n## Core Gateway Features\n\nConnect, manage, and secure AI interactions across 1600+ LLMs with centralized control, real-time monitoring, and enterprise-grade governance.(no content)Connect to 1600+ LLMs and providers across different modalities via the AI gateway - no separate integration required. Dynamically switch between models, distribute workloads, and ensure failover with configurable rules.(no content)Store LLM keys safely in Portkey's vault and manage access with virtual keys. Rotate, revoke, and monitor usage with full control.(no content)The open source gateway (10,000+ GitHub stars) runs on global edge workers with just 20-40ms latency overhead, handling millions of requests per minute at 99.99% uptime.(no content)The platform is ISO 27001 and SOC 2 certified with GDPR and HIPAA compliance, making it viable for regulated industries.\n\n## Why Choose Portkey (2025 Perspective)\n\nAI Gateways appear in the Gartner Hype Cycle for Generative AI, 2025. In 2025, they're no longer optional. They've become a critical part of the AI stack.(no content)Portkey is best for enterprise organizations requiring comprehensive governance, advanced observability, and sophisticated access controls. Portkey is built specifically for enterprises managing AI deployments across multiple teams and departments.\n\n\nREMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks." | |
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| { | |
| "title": "Enterprise-grade AI Gateway | Portkey", | |
| "url": "https://portkey.ai/features/ai-gateway" | |
| }, | |
| { | |
| "title": "Portkey | Control Panel for Production AI", | |
| "url": "https://portkey.ai/pricing" | |
| }, | |
| { | |
| "title": "How to choose an AI gateway in 2025", | |
| "url": "https://portkey.ai/blog/how-to-choose-an-ai-gateway-in-2025/" | |
| }, | |
| { | |
| "title": "Production Stack for Gen AI Builders|Portkey", | |
| "url": "https://portkey.ai/" | |
| }, | |
| { | |
| "title": "GitHub - Portkey-AI/gateway: A blazing fast AI Gateway with integrated guardrails. Route to 200+ LLMs, 50+ AI Guardrails with 1 fast & friendly API.", | |
| "url": "https://github.com/Portkey-AI/gateway" | |
| }, | |
| { | |
| "title": "Best AI Gateway Solutions", | |
| "url": "https://portkey.ai/buyers-guide/ai-gateway-solutions" | |
| }, | |
| { | |
| "title": "Best LLM Observability Tools in 2025", | |
| "url": "https://www.firecrawl.dev/blog/best-llm-observability-tools" | |
| }, | |
| { | |
| "title": "Model Pricing and Cost Management - Portkey Docs", | |
| "url": "https://portkey.ai/docs/product/observability/cost-management" | |
| }, | |
| { | |
| "title": "Top 5 LLM Gateways in 2025: The Complete Guide to Choosing the Best AI Gateway", | |
| "url": "https://www.helicone.ai/blog/top-llm-gateways-comparison-2025" | |
| }, | |
| { | |
| "title": "Top 5 AI Gateways for 2026: Building Reliable Multi-Provider AI Infrastructure - DEV Community", | |
| "url": "https://dev.to/kuldeep_paul/top-5-ai-gateways-for-2026-building-reliable-multi-provider-ai-infrastructure-16e3" | |
| } | |
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| "Based on the search results, here's what I found about Portkey AI Gateway's pricing, features, and enterprise offerings in 2025:\n\n## Portkey AI Gateway Overview\n\nPortkey equips AI teams with everything they need to go to production - AI Gateway, Observability, Guardrails, Governance, and Prompt Management, all in one platform.\n\n## Pricing Structure\n\nPortkey offers a usage-based pricing model with a free tier for initial development and testing.(no content)Enterprise plans include advanced governance, audit logging, and dedicated regional deployments.(no content)The free tier covers 10,000 requests per month, with paid plans adding advanced routing and analytics.(no content)Portkey starts at $49/month for paid plans.\n\n## Pricing Tiers\n\nThe free tier is perfect for prototyping and testing or evaluating enterprise POCs, but is not suitable for production workloads.(no content)A production tier is great for teams ready to deploy LLM apps in production, though it's not recommended for organizations requiring custom security controls or data residency guarantees.(no content)The enterprise tier is built for organizations with complex compliance needs and high-volume production workloads, offering the full Portkey feature set with enterprise support and multiple deployment configurations.\n\n## Enterprise Features\n\nEnterprise includes Private Cloud Deployment, Data Export to Data Lakes, VPC Hosting, Advanced Compliance (SOC2 Type 2, GDPR, HIPAA), Custom BAAs, and Data Isolation.(no content)The LLM Gateway's enterprise version offers advanced capabilities for org management, governance, security and more out of the box.(no content)Portkey provides role-based access control, audit logging, compliance reporting, and policy enforcement. Organizations with regulatory requirements or complex internal governance find these features essential.(no content)Virtual keys and budget management enable different teams to manage independent API budgets without exposing actual credentials.\n\n## Core Gateway Features\n\nConnect, manage, and secure AI interactions across 1600+ LLMs with centralized control, real-time monitoring, and enterprise-grade governance.(no content)Connect to 1600+ LLMs and providers across different modalities via the AI gateway - no separate integration required. Dynamically switch between models, distribute workloads, and ensure failover with configurable rules.(no content)Store LLM keys safely in Portkey's vault and manage access with virtual keys. Rotate, revoke, and monitor usage with full control.(no content)The open source gateway (10,000+ GitHub stars) runs on global edge workers with just 20-40ms latency overhead, handling millions of requests per minute at 99.99% uptime.(no content)The platform is ISO 27001 and SOC 2 certified with GDPR and HIPAA compliance, making it viable for regulated industries.\n\n## Why Choose Portkey (2025 Perspective)\n\nAI Gateways appear in the Gartner Hype Cycle for Generative AI, 2025. In 2025, they're no longer optional. They've become a critical part of the AI stack.(no content)Portkey is best for enterprise organizations requiring comprehensive governance, advanced observability, and sophisticated access controls. Portkey is built specifically for enterprises managing AI deployments across multiple teams and departments." | |
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| "content": "Web search results for query: \"LiteLLM features pricing self-hosted AI gateway 2025\"\n\nLinks: [{\"title\":\"LiteLLM\",\"url\":\"https://www.litellm.ai/\"},{\"title\":\"GitHub - BerriAI/litellm: Python SDK, Proxy Server (AI Gateway) to call 100+ LLM APIs in OpenAI (or native) format, with cost tracking, guardrails, loadbalancing and logging. [Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthropic, Sagemaker, HuggingFace, VLLM, NVIDIA NIM]\",\"url\":\"https://github.com/BerriAI/litellm\"},{\"title\":\"Top 5 LLM Gateways in 2025: The Complete Guide to Choosing the Best AI Gateway\",\"url\":\"https://www.helicone.ai/blog/top-llm-gateways-comparison-2025\"},{\"title\":\"LiteLLM Review 2025 | AI Infrastructure & MLOps Tool - Pricing & Features\",\"url\":\"https://aiagentslist.com/agents/litellm\"},{\"title\":\"LiteLLM: Access 100+ AI Models Through a Single API (Free & Self-Hosted) | by Manu Francis | Dec, 2025 | Medium\",\"url\":\"https://medium.com/@manuedavakandam/litellm-access-100-ai-models-through-a-single-api-free-self-hosted-b6f7be7a51dc\"},{\"title\":\"LiteLLM Reviews and Pricing 2025 | F6S\",\"url\":\"https://www.f6s.com/software/litellm\"},{\"title\":\"LiteLLM Review β Cost, Use Cases & Alternatives [2025]\",\"url\":\"https://aichief.com/ai-development-tools/litellm/\"},{\"title\":\"Top LLM Gateways 2025\",\"url\":\"https://agenta.ai/blog/top-llm-gateways\"},{\"title\":\"LiteLLM: A Guide With Practical Examples | DataCamp\",\"url\":\"https://www.datacamp.com/tutorial/litellm\"},{\"title\":\"Best LLM Gateways in 2025: Top Tools for Managing and Securing AI Models | Pomerium\",\"url\":\"https://www.pomerium.com/blog/best-llm-gateways-in-2025\"}]\n\nBased on the search results, here's a comprehensive overview of LiteLLM's features, pricing, and self-hosted AI gateway capabilities in 2025:\n\n## LiteLLM Overview\n\nLiteLLM is an open-source proxy server that unifies access to multiple Large Language Models (LLMs) through a single, standardized API. Instead of managing separate integrations for OpenAI, DeepSeek, Anthropic, Claude, and other providers, LiteLLM acts as a universal gateway.\n\n## Key Features\n\n### Multi-Provider Support\nLiteLLM provides multi-provider support including OpenAI, Anthropic, xAI, VertexAI, NVIDIA, HuggingFace, Azure OpenAI, Ollama, Openrouter, Novita AI, Vercel AI Gateway, and more.\n\n### Unified API Format\nLiteLLM is an OpenAI-compatible LLM gateway (proxy) that provides unified model access, authentication, load balancing, fallbacks and spend tracking across 100+ LLM providers. Key features include OpenAI-format API compatibility, cost attribution and reporting, budgets and rate limits, guardrails, observability/logging integrations, and virtual keys.\n\n### Cost Tracking & Budgeting\nEvery request, response, token count, and cost is logged. With Postgres integration, you can build dashboards to monitor usage patterns, identify expensive queries, and optimize your AI spending.\n\n### Reliability Features\nYou can set up fallback logic β if one provider fails, requests automatically route to another.(no content)LiteLLM offers performance of 8ms P95 latency at 1k RPS. Stable releases with the -stable tag have undergone 12 hour load tests before being published.\n\n### Observability & Logging\nLiteLLM integrates with Lunary, MLflow, Langfuse, Helicone, Promptlayer, Traceloop, and Slack for observability and logging.\n\n## Pricing\n\nLiteLLM is open-source and free to self-host.(no content)The platform offers a free plan, which is known as an open-source or self-hosted with limited access to advanced features.(no content)LiteLLM offers both an open-source self-hosted edition and an enterprise offering with SSO/JWT, audit logs and support.(no content)There is also an enterprise plan beneficial for large teams and enterprises who want cloud and self-hosted-based plans with advanced and premium functionalities.\n\n## Self-Hosted Deployment\n\nGetting started with LiteLLM is straightforward using Docker Compose. The setup includes a Postgres database for persistent logging and the LiteLLM proxy server.(no content)The proxy server acts as a central gateway for teams and companies that need to manage AI services at scale. Built-in cost tracking lets you see spending across all providers in one dashboard. There's also a self-hosting option to run everything on your own servers if you need data privacy or compliance.(no content)The library is MIT-licensed and completely open-source.\n\n## Use Cases\n\nAI-Powered Businesses can use LiteLLM to optimize AI workflows with budget tracking, rate limits, and granular access control. Enterprises & Large Teams can secure deployments with enterprise-grade security, SSO, and audit logs. Researchers & Data Scientists can experiment with various LLMs while logging and tracking AI performance.\n\n\nREMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks." | |
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| { | |
| "title": "LiteLLM", | |
| "url": "https://www.litellm.ai/" | |
| }, | |
| { | |
| "title": "GitHub - BerriAI/litellm: Python SDK, Proxy Server (AI Gateway) to call 100+ LLM APIs in OpenAI (or native) format, with cost tracking, guardrails, loadbalancing and logging. [Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthropic, Sagemaker, HuggingFace, VLLM, NVIDIA NIM]", | |
| "url": "https://github.com/BerriAI/litellm" | |
| }, | |
| { | |
| "title": "Top 5 LLM Gateways in 2025: The Complete Guide to Choosing the Best AI Gateway", | |
| "url": "https://www.helicone.ai/blog/top-llm-gateways-comparison-2025" | |
| }, | |
| { | |
| "title": "LiteLLM Review 2025 | AI Infrastructure & MLOps Tool - Pricing & Features", | |
| "url": "https://aiagentslist.com/agents/litellm" | |
| }, | |
| { | |
| "title": "LiteLLM: Access 100+ AI Models Through a Single API (Free & Self-Hosted) | by Manu Francis | Dec, 2025 | Medium", | |
| "url": "https://medium.com/@manuedavakandam/litellm-access-100-ai-models-through-a-single-api-free-self-hosted-b6f7be7a51dc" | |
| }, | |
| { | |
| "title": "LiteLLM Reviews and Pricing 2025 | F6S", | |
| "url": "https://www.f6s.com/software/litellm" | |
| }, | |
| { | |
| "title": "LiteLLM Review β Cost, Use Cases & Alternatives [2025]", | |
| "url": "https://aichief.com/ai-development-tools/litellm/" | |
| }, | |
| { | |
| "title": "Top LLM Gateways 2025", | |
| "url": "https://agenta.ai/blog/top-llm-gateways" | |
| }, | |
| { | |
| "title": "LiteLLM: A Guide With Practical Examples | DataCamp", | |
| "url": "https://www.datacamp.com/tutorial/litellm" | |
| }, | |
| { | |
| "title": "Best LLM Gateways in 2025: Top Tools for Managing and Securing AI Models | Pomerium", | |
| "url": "https://www.pomerium.com/blog/best-llm-gateways-in-2025" | |
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| "Based on the search results, here's a comprehensive overview of LiteLLM's features, pricing, and self-hosted AI gateway capabilities in 2025:\n\n## LiteLLM Overview\n\nLiteLLM is an open-source proxy server that unifies access to multiple Large Language Models (LLMs) through a single, standardized API. Instead of managing separate integrations for OpenAI, DeepSeek, Anthropic, Claude, and other providers, LiteLLM acts as a universal gateway.\n\n## Key Features\n\n### Multi-Provider Support\nLiteLLM provides multi-provider support including OpenAI, Anthropic, xAI, VertexAI, NVIDIA, HuggingFace, Azure OpenAI, Ollama, Openrouter, Novita AI, Vercel AI Gateway, and more.\n\n### Unified API Format\nLiteLLM is an OpenAI-compatible LLM gateway (proxy) that provides unified model access, authentication, load balancing, fallbacks and spend tracking across 100+ LLM providers. Key features include OpenAI-format API compatibility, cost attribution and reporting, budgets and rate limits, guardrails, observability/logging integrations, and virtual keys.\n\n### Cost Tracking & Budgeting\nEvery request, response, token count, and cost is logged. With Postgres integration, you can build dashboards to monitor usage patterns, identify expensive queries, and optimize your AI spending.\n\n### Reliability Features\nYou can set up fallback logic β if one provider fails, requests automatically route to another.(no content)LiteLLM offers performance of 8ms P95 latency at 1k RPS. Stable releases with the -stable tag have undergone 12 hour load tests before being published.\n\n### Observability & Logging\nLiteLLM integrates with Lunary, MLflow, Langfuse, Helicone, Promptlayer, Traceloop, and Slack for observability and logging.\n\n## Pricing\n\nLiteLLM is open-source and free to self-host.(no content)The platform offers a free plan, which is known as an open-source or self-hosted with limited access to advanced features.(no content)LiteLLM offers both an open-source self-hosted edition and an enterprise offering with SSO/JWT, audit logs and support.(no content)There is also an enterprise plan beneficial for large teams and enterprises who want cloud and self-hosted-based plans with advanced and premium functionalities.\n\n## Self-Hosted Deployment\n\nGetting started with LiteLLM is straightforward using Docker Compose. The setup includes a Postgres database for persistent logging and the LiteLLM proxy server.(no content)The proxy server acts as a central gateway for teams and companies that need to manage AI services at scale. Built-in cost tracking lets you see spending across all providers in one dashboard. There's also a self-hosting option to run everything on your own servers if you need data privacy or compliance.(no content)The library is MIT-licensed and completely open-source.\n\n## Use Cases\n\nAI-Powered Businesses can use LiteLLM to optimize AI workflows with budget tracking, rate limits, and granular access control. Enterprises & Large Teams can secure deployments with enterprise-grade security, SSO, and audit logs. Researchers & Data Scientists can experiment with various LLMs while logging and tracking AI performance." | |
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| "content": "Web search results for query: \"Eden AI API unified platform pricing models 2025\"\n\nLinks: [{\"title\":\"Eden AI | Unified AI API or a Custom one just for you\",\"url\":\"https://www.edenai.co/\"},{\"title\":\"Eden AI Pricing, Plans and Cost Breakdown - Updated 2025\",\"url\":\"https://aihungry.com/tools/eden-ai/pricing\"},{\"title\":\"Pricing | Eden AI\",\"url\":\"https://www.edenai.co//pricing\"},{\"title\":\"Eden AI Reviews and Pricing 2025 | F6S\",\"url\":\"https://www.f6s.com/software/eden-ai\"},{\"title\":\"EDEN AI Review β Features, Pricing & Verdict | AIquiks\",\"url\":\"https://aiquiks.com/ai-tools/eden-ai\"},{\"title\":\"Eden AI Pricing: Cost and Pricing plans\",\"url\":\"https://www.saasworthy.com/product/eden-ai-co/pricing\"},{\"title\":\"Eden AI Review 2025: What It Is, How to Use It & Is It Worth It?\",\"url\":\"https://aihungry.com/tools/eden-ai\"},{\"title\":\"Eden AI - Features & Pricing (November 2025)\",\"url\":\"https://www.saasworthy.com/product/eden-ai-co\"},{\"title\":\"Eden AI: Unified API for Top AI Models & Workflow Automation\",\"url\":\"https://aidude.info/tools/eden-ai\"},{\"title\":\"Eden AI: Connecting over 100+ AI Models via Unified API - Chief AI Sharing Circle\",\"url\":\"https://www.aisharenet.com/en/eden-ai/\"}]\n\nBased on my search, here's what I found about Eden AI's unified API platform pricing models for 2025:\n\n## Eden AI Pricing Overview\n\nEden AI is a platform that unifies multiple AI engines in one API, offering developers access to a variety of AI engines through a single API.\n\n### Pricing Plans\n\n**Start Plan (Free)**\nThe 'Start' plan is free of charge and includes up to 60 API calls per minute, a $10 credit to start with, cost management, and support via Discord. It also offers free plugins for Zapier, Make, Bubble, and Microsoft. No credit card is required to get started with this plan.\n\n**Personal Plan**\nThe 'Personal' plan costs $29 per month plus the cost of your API calls. It offers all the benefits of the Start plan, with an increased limit of up to 300 API calls per minute. Additional features include the ability to bring your own accounts and API caching.\n\n**Advanced/Enterprise Plans**\nAdvanced features include access to +100 models with the unified API, custom AI API builder, workflow, custom chatbot builder (RAG), cost and performance monitoring tools, chat support (24h), and unlimited seats.(no content)Enterprise features include all features of the Advanced plan, custom integration with a Solution Engineer, ongoing optimization of model selection, deployment of the platform on your server, custom addition of AI models and tools, and Eden AI component embedded in your product.\n\n### Pricing Model\n\nYou only pay for the calls you make, with no need to commit to a monthly subscription. You buy credit and pay only for the AI models you request, at the same prices as if you were requesting them directly from the AI model providers.(no content)Eden AI provides flexible pricing models, including pay-as-you-go and customized enterprise plans.(no content)The cost of AI API calls depends on the technology, your data volume, and the chosen provider. Eden AI provides a tool to estimate your AI API calls cost.\n\n### Bring Your Own Account Option\n\nIf you want to benefit from discounts on the intensive use of models from certain vendors, you'll need to create an account with them and enter your API key (\"Bring your own account\") on Eden AI. In this case, you'll be billed directly by the vendor for the use of their models, and may benefit from reduced prices.(no content)The official documentation emphasizes that there is no additional charge for importing external keys, only the vendor's standard billing.\n\n### Payment Options\n\nPayment is by credit card or bank transfer (using Stripe), and you can pay from almost anywhere in the world.\n\n\nREMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks." | |
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| { | |
| "title": "Eden AI - Features & Pricing (November 2025)", | |
| "url": "https://www.saasworthy.com/product/eden-ai-co" | |
| }, | |
| { | |
| "title": "Eden AI: Unified API for Top AI Models & Workflow Automation", | |
| "url": "https://aidude.info/tools/eden-ai" | |
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| "title": "Eden AI: Connecting over 100+ AI Models via Unified API - Chief AI Sharing Circle", | |
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| "Based on my search, here's what I found about Eden AI's unified API platform pricing models for 2025:\n\n## Eden AI Pricing Overview\n\nEden AI is a platform that unifies multiple AI engines in one API, offering developers access to a variety of AI engines through a single API.\n\n### Pricing Plans\n\n**Start Plan (Free)**\nThe 'Start' plan is free of charge and includes up to 60 API calls per minute, a $10 credit to start with, cost management, and support via Discord. It also offers free plugins for Zapier, Make, Bubble, and Microsoft. No credit card is required to get started with this plan.\n\n**Personal Plan**\nThe 'Personal' plan costs $29 per month plus the cost of your API calls. It offers all the benefits of the Start plan, with an increased limit of up to 300 API calls per minute. Additional features include the ability to bring your own accounts and API caching.\n\n**Advanced/Enterprise Plans**\nAdvanced features include access to +100 models with the unified API, custom AI API builder, workflow, custom chatbot builder (RAG), cost and performance monitoring tools, chat support (24h), and unlimited seats.(no content)Enterprise features include all features of the Advanced plan, custom integration with a Solution Engineer, ongoing optimization of model selection, deployment of the platform on your server, custom addition of AI models and tools, and Eden AI component embedded in your product.\n\n### Pricing Model\n\nYou only pay for the calls you make, with no need to commit to a monthly subscription. You buy credit and pay only for the AI models you request, at the same prices as if you were requesting them directly from the AI model providers.(no content)Eden AI provides flexible pricing models, including pay-as-you-go and customized enterprise plans.(no content)The cost of AI API calls depends on the technology, your data volume, and the chosen provider. Eden AI provides a tool to estimate your AI API calls cost.\n\n### Bring Your Own Account Option\n\nIf you want to benefit from discounts on the intensive use of models from certain vendors, you'll need to create an account with them and enter your API key (\"Bring your own account\") on Eden AI. In this case, you'll be billed directly by the vendor for the use of their models, and may benefit from reduced prices.(no content)The official documentation emphasizes that there is no additional charge for importing external keys, only the vendor's standard billing.\n\n### Payment Options\n\nPayment is by credit card or bank transfer (using Stripe), and you can pay from almost anywhere in the world." | |
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| "content": "Web search results for query: \"Helicone AI gateway features pricing 2025\"\n\nLinks: [{\"title\":\"Helicone Pricing | Ship Your AI App With Confidence\",\"url\":\"https://www.helicone.ai/pricing\"},{\"title\":\"Top 5 LLM Gateways in 2025: The Complete Guide to Choosing the Best AI Gateway\",\"url\":\"https://www.helicone.ai/blog/top-llm-gateways-comparison-2025\"},{\"title\":\"OpenRouter Alternatives in 2025\",\"url\":\"https://www.helicone.ai/blog/openrouter-alternatives\"},{\"title\":\"GitHub - Helicone/helicone: π§ Open source LLM observability platform. One line of code to monitor, evaluate, and experiment. YC W23 π\",\"url\":\"https://github.com/Helicone/helicone\"},{\"title\":\"Complete Guide to the Helicone AI Gateway (with Practical Examples)\",\"url\":\"https://www.helicone.ai/blog/how-to-gateway\"},{\"title\":\"Introducing the Helicone AI Gateway\",\"url\":\"https://www.helicone.ai/blog/introducing-ai-gateway\"},{\"title\":\"Helicone / AI Gateway & LLM Observability\",\"url\":\"https://www.helicone.ai/\"},{\"title\":\"Helicone Review 2025 | AI Infrastructure & MLOps Tool - Pricing & Features\",\"url\":\"https://aiagentslist.com/agents/helicone\"},{\"title\":\"Helicone: The Ultimate Guide to LLM Price Comparison and Cost Control\",\"url\":\"https://skywork.ai/skypage/en/Helicone-The-Ultimate-Guide-to-LLM-Price-Comparison-and-Cost-Control/1976164605853626368\"},{\"title\":\"Helicone AI: Open-source LLM Observability for Developers | Product Hunt\",\"url\":\"https://www.producthunt.com/products/helicone-ai\"}]\n\nBased on my search results, here's a comprehensive overview of Helicone AI Gateway features and pricing for 2025:\n\n## Helicone AI Gateway Overview\n\nHelicone AI is an open-source gateway and observability platform for AI applications.(no content)The Helicone AI Gateway is a lightweight Rust router inspired by NGINX that removes the integration tax so you can focus on shipping features.\n\n## Key Features\n\n### Performance & Architecture\n- The Helicone AI Gateway is one of the few LLM routers written in the highly performant Rust programming language. It provides ultra-fast performance (e.g., 8ms P50 latency) and is horizontally scalable.\n- It also features a single binary deployment, making it simple to run on AWS, GCP, Azure, on-prem, Kubernetes, Docker, or bare metal.\n\n### Core Capabilities\n- It offers a single API to connect to over 100 large language models, simplifying how you route requests, debug problems, and analyze performance.\n- The AI Gateway handles failovers, rate limiting, caching, and observability.\n- Helicone AI Gateway uses health-aware routing with circuit breaking to detect failures and route to healthy providers.\n- One API key accesses all providers with OpenAI SDK compatibility. Automatic provider fallbacks keep your application running when issues occur. Zero markup pricing means you pay exactly what providers charge + Stripe payment processing fee.\n\n### Observability\n- It integrates seamlessly with Helicone's observability tools, providing real-time insights into provider performance and usage patterns.\n- Helicone provides native integration with their observability platform: real-time cost tracking, latency metrics, error monitoring.\n\n### Enterprise Features\n- Enterprise Ready: SOC 2 and GDPR compliant.\n- Helicone lets you deploy in your VPC using Docker, K8s, or manual setup.\n\n## Pricing\n\n### Free Tier\n- Generous monthly free tier (10k requests/month) - No credit card required!\n\n### Pricing Model\n- Helicone AI Gateway and LiteLLM are open-source and free to self-host.\n- Unlike traditional API gateways, Helicone AI Gateway includes zero markup pricing and has built-in observability by default, so every request is automatically logged, tracked, and analyzed without additional configuration or pricing.\n- Helicone provides a unified API gateway that simplifies access to over 100 models, offers unified billing with zero markup.\n\n### Plan Tiers (from pricing page)\n- Starter plan for teams, Growing companies tier, and Custom-built packages for enterprise.\n- For startups under 2 years old and $5M in funding, discounts are available for the first year.\n- Special pricing is available for most students and educators.\n\n### Comparison to Competitors\n- OpenRouter adds a 5% markup on all requests. Portkey starts at $49/month.\n- OpenRouter, Helicone AI Gateway, and Portkey can be configured in under 5 minutes with simple API changes.\n\n\nREMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks." | |
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| }, | |
| { | |
| "title": "Top 5 LLM Gateways in 2025: The Complete Guide to Choosing the Best AI Gateway", | |
| "url": "https://www.helicone.ai/blog/top-llm-gateways-comparison-2025" | |
| }, | |
| { | |
| "title": "OpenRouter Alternatives in 2025", | |
| "url": "https://www.helicone.ai/blog/openrouter-alternatives" | |
| }, | |
| { | |
| "title": "GitHub - Helicone/helicone: π§ Open source LLM observability platform. One line of code to monitor, evaluate, and experiment. YC W23 π", | |
| "url": "https://github.com/Helicone/helicone" | |
| }, | |
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| "title": "Complete Guide to the Helicone AI Gateway (with Practical Examples)", | |
| "url": "https://www.helicone.ai/blog/how-to-gateway" | |
| }, | |
| { | |
| "title": "Introducing the Helicone AI Gateway", | |
| "url": "https://www.helicone.ai/blog/introducing-ai-gateway" | |
| }, | |
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| "title": "Helicone / AI Gateway & LLM Observability", | |
| "url": "https://www.helicone.ai/" | |
| }, | |
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| "url": "https://aiagentslist.com/agents/helicone" | |
| }, | |
| { | |
| "title": "Helicone: The Ultimate Guide to LLM Price Comparison and Cost Control", | |
| "url": "https://skywork.ai/skypage/en/Helicone-The-Ultimate-Guide-to-LLM-Price-Comparison-and-Cost-Control/1976164605853626368" | |
| }, | |
| { | |
| "title": "Helicone AI: Open-source LLM Observability for Developers | Product Hunt", | |
| "url": "https://www.producthunt.com/products/helicone-ai" | |
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| "Based on my search results, here's a comprehensive overview of Helicone AI Gateway features and pricing for 2025:\n\n## Helicone AI Gateway Overview\n\nHelicone AI is an open-source gateway and observability platform for AI applications.(no content)The Helicone AI Gateway is a lightweight Rust router inspired by NGINX that removes the integration tax so you can focus on shipping features.\n\n## Key Features\n\n### Performance & Architecture\n- The Helicone AI Gateway is one of the few LLM routers written in the highly performant Rust programming language. It provides ultra-fast performance (e.g., 8ms P50 latency) and is horizontally scalable.\n- It also features a single binary deployment, making it simple to run on AWS, GCP, Azure, on-prem, Kubernetes, Docker, or bare metal.\n\n### Core Capabilities\n- It offers a single API to connect to over 100 large language models, simplifying how you route requests, debug problems, and analyze performance.\n- The AI Gateway handles failovers, rate limiting, caching, and observability.\n- Helicone AI Gateway uses health-aware routing with circuit breaking to detect failures and route to healthy providers.\n- One API key accesses all providers with OpenAI SDK compatibility. Automatic provider fallbacks keep your application running when issues occur. Zero markup pricing means you pay exactly what providers charge + Stripe payment processing fee.\n\n### Observability\n- It integrates seamlessly with Helicone's observability tools, providing real-time insights into provider performance and usage patterns.\n- Helicone provides native integration with their observability platform: real-time cost tracking, latency metrics, error monitoring.\n\n### Enterprise Features\n- Enterprise Ready: SOC 2 and GDPR compliant.\n- Helicone lets you deploy in your VPC using Docker, K8s, or manual setup.\n\n## Pricing\n\n### Free Tier\n- Generous monthly free tier (10k requests/month) - No credit card required!\n\n### Pricing Model\n- Helicone AI Gateway and LiteLLM are open-source and free to self-host.\n- Unlike traditional API gateways, Helicone AI Gateway includes zero markup pricing and has built-in observability by default, so every request is automatically logged, tracked, and analyzed without additional configuration or pricing.\n- Helicone provides a unified API gateway that simplifies access to over 100 models, offers unified billing with zero markup.\n\n### Plan Tiers (from pricing page)\n- Starter plan for teams, Growing companies tier, and Custom-built packages for enterprise.\n- For startups under 2 years old and $5M in funding, discounts are available for the first year.\n- Special pricing is available for most students and educators.\n\n### Comparison to Competitors\n- OpenRouter adds a 5% markup on all requests. Portkey starts at $49/month.\n- OpenRouter, Helicone AI Gateway, and Portkey can be configured in under 5 minutes with simple API changes." | |
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| "content": "Web search results for query: \"Cloudflare AI Gateway pricing features 2025\"\n\nLinks: [{\"title\":\"Pricing Β· Cloudflare AI Gateway docs\",\"url\":\"https://developers.cloudflare.com/ai-gateway/reference/pricing/\"},{\"title\":\"AI Gateway now gives you access to your favorite AI models, dynamic routing and more β through just one endpoint\",\"url\":\"https://blog.cloudflare.com/ai-gateway-aug-2025-refresh/\"},{\"title\":\"AI Gateway | Observability for AI applications | Cloudflare\",\"url\":\"https://www.cloudflare.com/developer-platform/products/ai-gateway/\"},{\"title\":\"Unified Billing Β· Cloudflare AI Gateway docs\",\"url\":\"https://developers.cloudflare.com/ai-gateway/features/unified-billing/\"},{\"title\":\"Costs Β· Cloudflare AI Gateway docs\",\"url\":\"https://developers.cloudflare.com/ai-gateway/observability/costs/\"},{\"title\":\"Features Β· Cloudflare AI Gateway docs\",\"url\":\"https://developers.cloudflare.com/ai-gateway/features/\"},{\"title\":\"Overview Β· Cloudflare AI Gateway docs\",\"url\":\"https://developers.cloudflare.com/ai-gateway/\"},{\"title\":\"Custom costs Β· Cloudflare AI Gateway docs\",\"url\":\"https://developers.cloudflare.com/ai-gateway/configuration/custom-costs/\"},{\"title\":\"Cloudflare Gateway: Pricing, Reviews & Features 2025 | Cloud Tools\",\"url\":\"https://cloud.toolsinfo.com/tool/cloudflare-gateway\"},{\"title\":\"Pricing Β· Cloudflare Workers AI docs\",\"url\":\"https://developers.cloudflare.com/workers-ai/platform/pricing/\"}]\n\nBased on my search results, here's an overview of Cloudflare AI Gateway pricing and features for 2025:\n\n## Pricing\n\nAI Gateway is available to use on all plans.(no content)Persistent logs are available on all plans, with a free allocation for both free and paid plans. Charges for additional logs beyond those limits are based on the number of logs stored per month.(no content)Logpush is only available on the Workers Paid plan.(no content)Cloudflare will continue to build and expand AI Gateway. Some new features may be additional core features that will be free while others may be part of a premium plan, and they will announce these as they become available.\n\n### Unified Billing (New in 2025)\n\nUnified Billing allows users to connect to various AI providers (such as OpenAI, Anthropic, and Google AI Studio) and receive a single Cloudflare bill. To use Unified Billing, you must purchase and load credits into your Cloudflare account in the Cloudflare dashboard.(no content)This eliminates the need to sign up and pay for each individual model provider account. Usage rates are based on then-current list prices from model providers β all you will need to cover is the transaction fee as you load credits into your account.(no content)You can set spend limits to prevent unexpected charges on your loaded credits, with daily, weekly, or monthly limits available. When a limit is reached, the AI Gateway automatically stops processing requests until the period resets or you increase the limit.\n\n## Key Features\n\n### Core Capabilities\n- Cloudflare's AI Gateway allows you to gain visibility and control over your AI apps. By connecting your apps to AI Gateway, you can gather insights on how people are using your application with analytics and logging and control how your application scales with features such as caching, rate limiting, request retries, model fallback, and more.\n\n### Performance & Cost Optimization\n- Caching serves identical requests directly from Cloudflare's global cache, reducing latency by up to 90% and significantly cutting costs by avoiding repeated API calls to AI providers.\n- Rate limiting controls application scaling and protects against abuse with flexible options. You can set limits based on requests per time window with sliding or fixed window techniques.\n\n### Security\n- Token-based authentication secures your AI Gateway. This controls access to your gateways and protects against unauthorized usage.\n- You can securely store and manage AI provider API keys in Cloudflare's encrypted infrastructure, removing hardcoded keys from your applications while maintaining full control.\n\n### Observability\n- Comprehensive analytics provide deep insights into your AI application usage. You can track requests, tokens, costs, errors, and performance across all providers.\n- Detailed logs capture all AI requests and responses for debugging, compliance, and analysis, with configurable log retention and export options.\n- AI Gateway allows users to set custom costs when operating under special pricing agreements or negotiated rates. Custom costs can be applied at the request level, and when applied, they will override the default or public model costs.\n\n### Routing\n- Dynamic routing allows you to create sophisticated request routing flows without code changes. You can route requests based on user segments, geography, content analysis, or A/B testing requirements through a visual interface.\n\n### Provider Support\n- Workers AI, OpenAI, Azure OpenAI, HuggingFace, Replicate, and more work with AI Gateway.\n- All features work seamlessly together and across all 20+ supported AI providers.\n\n\nREMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks." | |
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| "title": "Pricing Β· Cloudflare AI Gateway docs", | |
| "url": "https://developers.cloudflare.com/ai-gateway/reference/pricing/" | |
| }, | |
| { | |
| "title": "AI Gateway now gives you access to your favorite AI models, dynamic routing and more β through just one endpoint", | |
| "url": "https://blog.cloudflare.com/ai-gateway-aug-2025-refresh/" | |
| }, | |
| { | |
| "title": "AI Gateway | Observability for AI applications | Cloudflare", | |
| "url": "https://www.cloudflare.com/developer-platform/products/ai-gateway/" | |
| }, | |
| { | |
| "title": "Unified Billing Β· Cloudflare AI Gateway docs", | |
| "url": "https://developers.cloudflare.com/ai-gateway/features/unified-billing/" | |
| }, | |
| { | |
| "title": "Costs Β· Cloudflare AI Gateway docs", | |
| "url": "https://developers.cloudflare.com/ai-gateway/observability/costs/" | |
| }, | |
| { | |
| "title": "Features Β· Cloudflare AI Gateway docs", | |
| "url": "https://developers.cloudflare.com/ai-gateway/features/" | |
| }, | |
| { | |
| "title": "Overview Β· Cloudflare AI Gateway docs", | |
| "url": "https://developers.cloudflare.com/ai-gateway/" | |
| }, | |
| { | |
| "title": "Custom costs Β· Cloudflare AI Gateway docs", | |
| "url": "https://developers.cloudflare.com/ai-gateway/configuration/custom-costs/" | |
| }, | |
| { | |
| "title": "Cloudflare Gateway: Pricing, Reviews & Features 2025 | Cloud Tools", | |
| "url": "https://cloud.toolsinfo.com/tool/cloudflare-gateway" | |
| }, | |
| { | |
| "title": "Pricing Β· Cloudflare Workers AI docs", | |
| "url": "https://developers.cloudflare.com/workers-ai/platform/pricing/" | |
| } | |
| ] | |
| }, | |
| "Based on my search results, here's an overview of Cloudflare AI Gateway pricing and features for 2025:\n\n## Pricing\n\nAI Gateway is available to use on all plans.(no content)Persistent logs are available on all plans, with a free allocation for both free and paid plans. Charges for additional logs beyond those limits are based on the number of logs stored per month.(no content)Logpush is only available on the Workers Paid plan.(no content)Cloudflare will continue to build and expand AI Gateway. Some new features may be additional core features that will be free while others may be part of a premium plan, and they will announce these as they become available.\n\n### Unified Billing (New in 2025)\n\nUnified Billing allows users to connect to various AI providers (such as OpenAI, Anthropic, and Google AI Studio) and receive a single Cloudflare bill. To use Unified Billing, you must purchase and load credits into your Cloudflare account in the Cloudflare dashboard.(no content)This eliminates the need to sign up and pay for each individual model provider account. Usage rates are based on then-current list prices from model providers β all you will need to cover is the transaction fee as you load credits into your account.(no content)You can set spend limits to prevent unexpected charges on your loaded credits, with daily, weekly, or monthly limits available. When a limit is reached, the AI Gateway automatically stops processing requests until the period resets or you increase the limit.\n\n## Key Features\n\n### Core Capabilities\n- Cloudflare's AI Gateway allows you to gain visibility and control over your AI apps. By connecting your apps to AI Gateway, you can gather insights on how people are using your application with analytics and logging and control how your application scales with features such as caching, rate limiting, request retries, model fallback, and more.\n\n### Performance & Cost Optimization\n- Caching serves identical requests directly from Cloudflare's global cache, reducing latency by up to 90% and significantly cutting costs by avoiding repeated API calls to AI providers.\n- Rate limiting controls application scaling and protects against abuse with flexible options. You can set limits based on requests per time window with sliding or fixed window techniques.\n\n### Security\n- Token-based authentication secures your AI Gateway. This controls access to your gateways and protects against unauthorized usage.\n- You can securely store and manage AI provider API keys in Cloudflare's encrypted infrastructure, removing hardcoded keys from your applications while maintaining full control.\n\n### Observability\n- Comprehensive analytics provide deep insights into your AI application usage. You can track requests, tokens, costs, errors, and performance across all providers.\n- Detailed logs capture all AI requests and responses for debugging, compliance, and analysis, with configurable log retention and export options.\n- AI Gateway allows users to set custom costs when operating under special pricing agreements or negotiated rates. Custom costs can be applied at the request level, and when applied, they will override the default or public model costs.\n\n### Routing\n- Dynamic routing allows you to create sophisticated request routing flows without code changes. You can route requests based on user segments, geography, content analysis, or A/B testing requirements through a visual interface.\n\n### Provider Support\n- Workers AI, OpenAI, Azure OpenAI, HuggingFace, Replicate, and more work with AI Gateway.\n- All features work seamlessly together and across all 20+ supported AI providers." | |
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| [2025-12-28T03:06:45.180Z] [INFO] { | |
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| "content": "Web search results for query: \"Together AI inference API pricing models 2025\"\n\nLinks: [{\"title\":\"Together AI - Pricing\",\"url\":\"https://www.together.ai/pricing\"},{\"title\":\"Fast, Reliable AI Inference at Scale | Together AI\",\"url\":\"https://www.together.ai/inference\"},{\"title\":\"Products: Inference, Fine-Tuning, Training, and GPU Clusters | Together AI\",\"url\":\"https://www.together.ai/products\"},{\"title\":\"Together AI | The AI Native Cloud\",\"url\":\"https://www.together.ai/\"},{\"title\":\"A complete guide to Together AI pricing in 2025 - eesel AI\",\"url\":\"https://www.eesel.ai/blog/together-ai-pricing\"},{\"title\":\"Pricing - Together.ai Docs\",\"url\":\"https://docs.together.ai/docs/fine-tuning-pricing\"},{\"title\":\"Models: Build with 200+ open-source and specialized models | Together AI\",\"url\":\"https://www.together.ai/models\"},{\"title\":\"Faster inference enables up to 5x price reduction on Together API\",\"url\":\"https://www.together.ai/blog/august-2023-pricing-update\"},{\"title\":\"11 Best LLM API Providers: Compare Inferencing Performance & Pricing\",\"url\":\"https://www.helicone.ai/blog/llm-api-providers\"},{\"title\":\"Together API\",\"url\":\"https://api.together.xyz/\"}]\n\nBased on my search, here's what I found about Together AI's inference API pricing models in 2025:\n\n## Together AI Inference API Pricing\n\n### Pricing Structure\n\nTogether AI offers a fast serverless API for 200+ models with pay-per-token pricing.(no content)They also provide customizable Dedicated Endpoints with per-minute billing.\n\n### Cost Comparison\n\nTogether Inference is 11x lower cost than GPT-4o when using Llama 3.3 70B and 9x lower cost than OpenAI o1 when using DeepSeek-R1.(no content)Their optimizations bring the best performance at the lowest cost.\n\n### Features & Performance\n\nYou can use their fast API to run inference on 200+ open-source models powered by the Together Inference Stack.(no content)Together AI offers high-performance inference for 200+ open-source LLMs with sub-100ms latency, automated optimization, and horizontal scaling - all at a lower cost than proprietary solutions.(no content)The service is optimized by the Together Inference Stack, which is 4x faster than vLLM.\n\n### Fine-Tuning Pricing\n\nFine-tuning price is based on the sum of tokens processed in the fine-tuning training dataset (training dataset size * number of epochs) plus any tokens in the optional evaluation dataset (validation dataset size * number of evaluations).(no content)There is no minimum price for fine-tuning jobs. You only pay for the tokens processed.\n\n### Deployment Options\n\nYou can reliably deploy models with unmatched price-performance at scale, benefiting from inference-focused innovations like the ATLAS speculator system and Together Inference Engine.\n\nFor specific per-token pricing for individual models, you would need to visit Together AI's pricing page directly at https://www.together.ai/pricing, as the exact rates vary by model size and type.\n\n\nREMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks." | |
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| { | |
| "title": "Together AI - Pricing", | |
| "url": "https://www.together.ai/pricing" | |
| }, | |
| { | |
| "title": "Fast, Reliable AI Inference at Scale | Together AI", | |
| "url": "https://www.together.ai/inference" | |
| }, | |
| { | |
| "title": "Products: Inference, Fine-Tuning, Training, and GPU Clusters | Together AI", | |
| "url": "https://www.together.ai/products" | |
| }, | |
| { | |
| "title": "Together AI | The AI Native Cloud", | |
| "url": "https://www.together.ai/" | |
| }, | |
| { | |
| "title": "A complete guide to Together AI pricing in 2025 - eesel AI", | |
| "url": "https://www.eesel.ai/blog/together-ai-pricing" | |
| }, | |
| { | |
| "title": "Pricing - Together.ai Docs", | |
| "url": "https://docs.together.ai/docs/fine-tuning-pricing" | |
| }, | |
| { | |
| "title": "Models: Build with 200+ open-source and specialized models | Together AI", | |
| "url": "https://www.together.ai/models" | |
| }, | |
| { | |
| "title": "Faster inference enables up to 5x price reduction on Together API", | |
| "url": "https://www.together.ai/blog/august-2023-pricing-update" | |
| }, | |
| { | |
| "title": "11 Best LLM API Providers: Compare Inferencing Performance & Pricing", | |
| "url": "https://www.helicone.ai/blog/llm-api-providers" | |
| }, | |
| { | |
| "title": "Together API", | |
| "url": "https://api.together.xyz/" | |
| } | |
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| "Based on my search, here's what I found about Together AI's inference API pricing models in 2025:\n\n## Together AI Inference API Pricing\n\n### Pricing Structure\n\nTogether AI offers a fast serverless API for 200+ models with pay-per-token pricing.(no content)They also provide customizable Dedicated Endpoints with per-minute billing.\n\n### Cost Comparison\n\nTogether Inference is 11x lower cost than GPT-4o when using Llama 3.3 70B and 9x lower cost than OpenAI o1 when using DeepSeek-R1.(no content)Their optimizations bring the best performance at the lowest cost.\n\n### Features & Performance\n\nYou can use their fast API to run inference on 200+ open-source models powered by the Together Inference Stack.(no content)Together AI offers high-performance inference for 200+ open-source LLMs with sub-100ms latency, automated optimization, and horizontal scaling - all at a lower cost than proprietary solutions.(no content)The service is optimized by the Together Inference Stack, which is 4x faster than vLLM.\n\n### Fine-Tuning Pricing\n\nFine-tuning price is based on the sum of tokens processed in the fine-tuning training dataset (training dataset size * number of epochs) plus any tokens in the optional evaluation dataset (validation dataset size * number of evaluations).(no content)There is no minimum price for fine-tuning jobs. You only pay for the tokens processed.\n\n### Deployment Options\n\nYou can reliably deploy models with unmatched price-performance at scale, benefiting from inference-focused innovations like the ATLAS speculator system and Together Inference Engine.\n\nFor specific per-token pricing for individual models, you would need to visit Together AI's pricing page directly at https://www.together.ai/pricing, as the exact rates vary by model size and type." | |
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| "content": "Web search results for query: \"Amazon Bedrock API gateway unified access pricing 2025\"\n\nLinks: [{\"title\":\"Amazon Bedrock AgentCore Pricing - AWS\",\"url\":\"https://aws.amazon.com/bedrock/agentcore/pricing/\"},{\"title\":\"Amazon Bedrock AgentCore Gateway: Securely connect tools and other resources to your Gateway - Amazon Bedrock AgentCore\",\"url\":\"https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/gateway.html\"},{\"title\":\"Amazon Bedrock Pricing β AWS\",\"url\":\"https://aws.amazon.com/bedrock/pricing/\"},{\"title\":\"Amazon Bedrock Pricing Explained: What You Need to Know\",\"url\":\"https://cloudchipr.com/blog/amazon-bedrock-pricing\"},{\"title\":\"API for the pricing of Bedrock Foundational models | AWS re:Post\",\"url\":\"https://repost.aws/questions/QU1IfSsHSsTbKfUtMlhvOHxw/api-for-the-pricing-of-bedrock-foundational-models\"},{\"title\":\"AWS Bedrock Pricing Breakdown: Avoiding Surprise Bills in GenAI Workloads\",\"url\":\"https://www.cloudexmachina.io/blog/bedrock-pricing\"},{\"title\":\"Comparing Cloud AI Platforms in 2025: Bedrock, Azure OpenAI, and Gemini - DEV Community\",\"url\":\"https://dev.to/swat_24/comparing-cloud-ai-platforms-in-2025-bedrock-azure-openai-and-gemini-4ij2\"},{\"title\":\"Amazon Bedrock pricing - Amazon Bedrock\",\"url\":\"https://docs.aws.amazon.com/bedrock/latest/userguide/bedrock-pricing.html\"},{\"title\":\"Amazon Bedrock β Build genAI applications and agents at production scale β AWS\",\"url\":\"https://aws.amazon.com/bedrock/\"},{\"title\":\"Introducing Amazon Bedrock AgentCore Gateway: Transforming enterprise AI agent tool development | Artificial Intelligence\",\"url\":\"https://aws.amazon.com/blogs/machine-learning/introducing-amazon-bedrock-agentcore-gateway-transforming-enterprise-ai-agent-tool-development/\"}]\n\nBased on my search results, here's information about Amazon Bedrock API Gateway unified access and pricing for 2025:\n\n## Amazon Bedrock AgentCore Gateway\n\nAmazon Bedrock AgentCore Gateway provides an easy and secure way for developers to build, deploy, discover, and connect to tools at scale.(no content)It enables agents to discover and use tools through a single, secure endpoint, combining multiple tool sourcesβfrom APIs to Lambda functionsβinto one unified interface.\n\n### Key Features\n- Developers can convert APIs, Lambda functions, and existing services into Model Context Protocol (MCP)-compatible tools and make them available to agents through Gateway endpoints with just a few lines of code.\n- Gateway supports OpenAPI, Smithy, and Lambda as input types, and provides both comprehensive ingress and egress authentication in a fully-managed service. It also provides 1-click integration with popular tools such as Salesforce, Slack, Jira, Asana, and Zendesk.\n\n### Pricing Structure\n\nAmazon Bedrock AgentCore offers flexible, consumption-based pricing with no upfront commitments or minimum fees. Each service and capabilityβRuntime, Gateway, Policy (Preview), Identity, Memory, Observability, Evaluations (Preview), Browser, and Code Interpreterβcan be used independently or together, and you pay only for what you use.\n\n**AgentCore Gateway Pricing:**\n- You pay only for the API calls your agents make through Gateway. You're charged based on the number of MCP operations (such as ListTools, CallTool, and Ping), search queries, and tools indexed for semantic search functionality.\n\n**Example Pricing (from AWS documentation):**\nSearchToolIndex charges: 200 tools Γ $0.02 per 100 tools = $0.04; Search API charges: 50M Γ $25/million = $1,250; InvokeTool API charges: 200M Γ $5/million = $1,000\n\n### Additional Bedrock Pricing Notes\n\nWith Amazon Bedrock, you pay to run inference on foundation models. Pricing is based on the volume of input tokens and output tokens, and on whether you have purchased Provisioned Throughput for the model.(no content)Automatic prompt routing selects the most cost-effective model for each request with potential 30% savings. Pricing snapshot for Claude 3.5 Sonnet: $3/million input tokens, $15/million output tokens.(no content)New AWS customers receive up to $200 in Free Tier credits.\n\n\nREMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks." | |
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| "title": "Amazon Bedrock AgentCore Pricing - AWS", | |
| "url": "https://aws.amazon.com/bedrock/agentcore/pricing/" | |
| }, | |
| { | |
| "title": "Amazon Bedrock AgentCore Gateway: Securely connect tools and other resources to your Gateway - Amazon Bedrock AgentCore", | |
| "url": "https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/gateway.html" | |
| }, | |
| { | |
| "title": "Amazon Bedrock Pricing β AWS", | |
| "url": "https://aws.amazon.com/bedrock/pricing/" | |
| }, | |
| { | |
| "title": "Amazon Bedrock Pricing Explained: What You Need to Know", | |
| "url": "https://cloudchipr.com/blog/amazon-bedrock-pricing" | |
| }, | |
| { | |
| "title": "API for the pricing of Bedrock Foundational models | AWS re:Post", | |
| "url": "https://repost.aws/questions/QU1IfSsHSsTbKfUtMlhvOHxw/api-for-the-pricing-of-bedrock-foundational-models" | |
| }, | |
| { | |
| "title": "AWS Bedrock Pricing Breakdown: Avoiding Surprise Bills in GenAI Workloads", | |
| "url": "https://www.cloudexmachina.io/blog/bedrock-pricing" | |
| }, | |
| { | |
| "title": "Comparing Cloud AI Platforms in 2025: Bedrock, Azure OpenAI, and Gemini - DEV Community", | |
| "url": "https://dev.to/swat_24/comparing-cloud-ai-platforms-in-2025-bedrock-azure-openai-and-gemini-4ij2" | |
| }, | |
| { | |
| "title": "Amazon Bedrock pricing - Amazon Bedrock", | |
| "url": "https://docs.aws.amazon.com/bedrock/latest/userguide/bedrock-pricing.html" | |
| }, | |
| { | |
| "title": "Amazon Bedrock β Build genAI applications and agents at production scale β AWS", | |
| "url": "https://aws.amazon.com/bedrock/" | |
| }, | |
| { | |
| "title": "Introducing Amazon Bedrock AgentCore Gateway: Transforming enterprise AI agent tool development | Artificial Intelligence", | |
| "url": "https://aws.amazon.com/blogs/machine-learning/introducing-amazon-bedrock-agentcore-gateway-transforming-enterprise-ai-agent-tool-development/" | |
| } | |
| ] | |
| }, | |
| "Based on my search results, here's information about Amazon Bedrock API Gateway unified access and pricing for 2025:\n\n## Amazon Bedrock AgentCore Gateway\n\nAmazon Bedrock AgentCore Gateway provides an easy and secure way for developers to build, deploy, discover, and connect to tools at scale.(no content)It enables agents to discover and use tools through a single, secure endpoint, combining multiple tool sourcesβfrom APIs to Lambda functionsβinto one unified interface.\n\n### Key Features\n- Developers can convert APIs, Lambda functions, and existing services into Model Context Protocol (MCP)-compatible tools and make them available to agents through Gateway endpoints with just a few lines of code.\n- Gateway supports OpenAPI, Smithy, and Lambda as input types, and provides both comprehensive ingress and egress authentication in a fully-managed service. It also provides 1-click integration with popular tools such as Salesforce, Slack, Jira, Asana, and Zendesk.\n\n### Pricing Structure\n\nAmazon Bedrock AgentCore offers flexible, consumption-based pricing with no upfront commitments or minimum fees. Each service and capabilityβRuntime, Gateway, Policy (Preview), Identity, Memory, Observability, Evaluations (Preview), Browser, and Code Interpreterβcan be used independently or together, and you pay only for what you use.\n\n**AgentCore Gateway Pricing:**\n- You pay only for the API calls your agents make through Gateway. You're charged based on the number of MCP operations (such as ListTools, CallTool, and Ping), search queries, and tools indexed for semantic search functionality.\n\n**Example Pricing (from AWS documentation):**\nSearchToolIndex charges: 200 tools Γ $0.02 per 100 tools = $0.04; Search API charges: 50M Γ $25/million = $1,250; InvokeTool API charges: 200M Γ $5/million = $1,000\n\n### Additional Bedrock Pricing Notes\n\nWith Amazon Bedrock, you pay to run inference on foundation models. Pricing is based on the volume of input tokens and output tokens, and on whether you have purchased Provisioned Throughput for the model.(no content)Automatic prompt routing selects the most cost-effective model for each request with potential 30% savings. Pricing snapshot for Claude 3.5 Sonnet: $3/million input tokens, $15/million output tokens.(no content)New AWS customers receive up to $200 in Free Tier credits." | |
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| "content": "Web search results for query: \"Martian AI model router pricing features 2025\"\n\nLinks: [{\"title\":\"Martian: Model Routing and AI Interpretability Tools\",\"url\":\"https://withmartian.com/\"},{\"title\":\"Martian: Increase AI performance and reduce cost with the LLM router\",\"url\":\"https://work.withmartian.com/\"},{\"title\":\"Martian's tool automatically switches between LLMs to reduce costs | TechCrunch\",\"url\":\"https://techcrunch.com/2023/11/15/martians-tool-automatically-switches-between-llms-to-reduce-costs/\"},{\"title\":\"Model routing: The secret weapon for maximizing AI efficiency in enterprises | VentureBeat\",\"url\":\"https://venturebeat.com/ai/why-accenture-and-martian-see-model-routing-as-key-to-enterprise-ai-success\"},{\"title\":\"Revolutionize AI with Martian's Model Router: Greater Uptime & Performance\",\"url\":\"https://route.withmartian.com/products/model-router\"},{\"title\":\"Martian model router jumpstarts AI cost optimization\",\"url\":\"https://diginomica.com/martian-model-router-jumpstarts-ai-cost-optimization\"},{\"title\":\"Martian | LinkedIn\",\"url\":\"https://www.linkedin.com/company/withmartian\"},{\"title\":\"Apart x Martian Mechanistic Router Interpretability Hackathon | Apart Research\",\"url\":\"https://apartresearch.com/sprints/apart-x-martian-mechanistic-router-interpretability-hackathon-2025-05-30-to-2025-06-01\"},{\"title\":\"Accenture Invests in Martian to Bring Dynamic Routing of Large Language Queries and More Effective AI Systems to Clients\",\"url\":\"https://newsroom.accenture.com/news/2024/accenture-invests-in-martian-to-bring-dynamic-routing-of-large-language-queries-and-more-effective-ai-systems-to-clients\"},{\"title\":\"Martian Emerges from Stealth with $9M Seed Funding to Bring Model Router Tech to Enterprises\",\"url\":\"https://www.maginative.com/article/martian-emerges-from-stealth-with-9m-seed-funding-to-bring-model-router-tech-to-enterprises/\"}]\n\nBased on my search, here's what I found about Martian AI model router pricing and features in 2025:\n\n## Martian AI Model Router Overview\n\n**What It Does:**\nMartian builds model routers that can dynamically select the best model to use for a given query.(no content)For any prompt, Martian's router will find and use the LLM that will give users the best result at the lowest cost.\n\n**Key Features:**\n\n1. **Dynamic Model Routing:** The approach allows Martian to select the single best model to run, optimizing for factors like cost, quality of output and latency. The Martian routing system can be integrated into applications that use language models, allowing it to dynamically choose the optimal model to use for each query.\n\n2. **Cost Reduction:** Martian claims to \"out-perform GPT-4 while reducing costs between 20%-96%.\"\n\n3. **Multi-Model Support:** They support dozens of models (e.g., OpenAI, Anthropic, Mistral, Llama) and use the OpenAI API format as a standard to make the router a drop-in replacement.\n\n4. **Automatic Failover:** If a company experiences an outage or high latency period, the system will automatically reroute to other providers so your customers never experience any issues.\n\n5. **Streaming Support:** They've introduced streaming, where the router runs your prompt on the best model for the lowest price, and now streams the output.\n\n6. **Compliance Feature (New in 2025):** The new compliance feature in Martian helps companies vet and approve AI models for use in their applications, allowing companies to automatically set up a set of policies for compliance.\n\n7. **Agentic AI Support:** With agentic AI workflows, Martian's routing helps ensure the best model is used for each step to maintain high accuracy. As Upadhyay said, \"Agents are like the killer use case for routing.\"\n\n**Pricing:**\nMartian offers an interactive cost calculator where you can determine how much you could save by inputting your number of users, tokens per session, sessions per month, and specify your cost/quality tradeoff.(no content)For developers, they also offer $50 in Martian API credits for hackathon participants.\n\n**Enterprise Adoption:**\nAccenture has invested in Martian through Accenture Ventures and plans to integrate Martian's advanced model router offering into its proprietary \"switchboard\" services.(no content)Engineers at 300+ companies, from Amazon to Zapier, have used Martian to achieve higher performance and lower costs, with greater security and reliability.\n\n**Technical Foundation:**\nTheir core technology uses a \"model mapping\" technique, making the model router the first commercial application of mechanistic interpretability.\n\nNote: Specific pricing tiers were not found in the search results. You may need to contact Martian directly or use their cost calculator on their website for detailed pricing information.\n\n\nREMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks." | |
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| { | |
| "title": "Martian: Model Routing and AI Interpretability Tools", | |
| "url": "https://withmartian.com/" | |
| }, | |
| { | |
| "title": "Martian: Increase AI performance and reduce cost with the LLM router", | |
| "url": "https://work.withmartian.com/" | |
| }, | |
| { | |
| "title": "Martian's tool automatically switches between LLMs to reduce costs | TechCrunch", | |
| "url": "https://techcrunch.com/2023/11/15/martians-tool-automatically-switches-between-llms-to-reduce-costs/" | |
| }, | |
| { | |
| "title": "Model routing: The secret weapon for maximizing AI efficiency in enterprises | VentureBeat", | |
| "url": "https://venturebeat.com/ai/why-accenture-and-martian-see-model-routing-as-key-to-enterprise-ai-success" | |
| }, | |
| { | |
| "title": "Revolutionize AI with Martian's Model Router: Greater Uptime & Performance", | |
| "url": "https://route.withmartian.com/products/model-router" | |
| }, | |
| { | |
| "title": "Martian model router jumpstarts AI cost optimization", | |
| "url": "https://diginomica.com/martian-model-router-jumpstarts-ai-cost-optimization" | |
| }, | |
| { | |
| "title": "Martian | LinkedIn", | |
| "url": "https://www.linkedin.com/company/withmartian" | |
| }, | |
| { | |
| "title": "Apart x Martian Mechanistic Router Interpretability Hackathon | Apart Research", | |
| "url": "https://apartresearch.com/sprints/apart-x-martian-mechanistic-router-interpretability-hackathon-2025-05-30-to-2025-06-01" | |
| }, | |
| { | |
| "title": "Accenture Invests in Martian to Bring Dynamic Routing of Large Language Queries and More Effective AI Systems to Clients", | |
| "url": "https://newsroom.accenture.com/news/2024/accenture-invests-in-martian-to-bring-dynamic-routing-of-large-language-queries-and-more-effective-ai-systems-to-clients" | |
| }, | |
| { | |
| "title": "Martian Emerges from Stealth with $9M Seed Funding to Bring Model Router Tech to Enterprises", | |
| "url": "https://www.maginative.com/article/martian-emerges-from-stealth-with-9m-seed-funding-to-bring-model-router-tech-to-enterprises/" | |
| } | |
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| }, | |
| "Based on my search, here's what I found about Martian AI model router pricing and features in 2025:\n\n## Martian AI Model Router Overview\n\n**What It Does:**\nMartian builds model routers that can dynamically select the best model to use for a given query.(no content)For any prompt, Martian's router will find and use the LLM that will give users the best result at the lowest cost.\n\n**Key Features:**\n\n1. **Dynamic Model Routing:** The approach allows Martian to select the single best model to run, optimizing for factors like cost, quality of output and latency. The Martian routing system can be integrated into applications that use language models, allowing it to dynamically choose the optimal model to use for each query.\n\n2. **Cost Reduction:** Martian claims to \"out-perform GPT-4 while reducing costs between 20%-96%.\"\n\n3. **Multi-Model Support:** They support dozens of models (e.g., OpenAI, Anthropic, Mistral, Llama) and use the OpenAI API format as a standard to make the router a drop-in replacement.\n\n4. **Automatic Failover:** If a company experiences an outage or high latency period, the system will automatically reroute to other providers so your customers never experience any issues.\n\n5. **Streaming Support:** They've introduced streaming, where the router runs your prompt on the best model for the lowest price, and now streams the output.\n\n6. **Compliance Feature (New in 2025):** The new compliance feature in Martian helps companies vet and approve AI models for use in their applications, allowing companies to automatically set up a set of policies for compliance.\n\n7. **Agentic AI Support:** With agentic AI workflows, Martian's routing helps ensure the best model is used for each step to maintain high accuracy. As Upadhyay said, \"Agents are like the killer use case for routing.\"\n\n**Pricing:**\nMartian offers an interactive cost calculator where you can determine how much you could save by inputting your number of users, tokens per session, sessions per month, and specify your cost/quality tradeoff.(no content)For developers, they also offer $50 in Martian API credits for hackathon participants.\n\n**Enterprise Adoption:**\nAccenture has invested in Martian through Accenture Ventures and plans to integrate Martian's advanced model router offering into its proprietary \"switchboard\" services.(no content)Engineers at 300+ companies, from Amazon to Zapier, have used Martian to achieve higher performance and lower costs, with greater security and reliability.\n\n**Technical Foundation:**\nTheir core technology uses a \"model mapping\" technique, making the model router the first commercial application of mechanistic interpretability.\n\nNote: Specific pricing tiers were not found in the search results. You may need to contact Martian directly or use their cost calculator on their website for detailed pricing information." | |
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| "content": "Web search results for query: \"Groq API cloud inference pricing LLM 2025\"\n\nLinks: [{\"title\":\"Groq is fast, low cost inference.\",\"url\":\"https://groq.com/\"},{\"title\":\"Groq On-Demand Pricing for Tokens-as-a-Service | Groq is fast, low cost inference.\",\"url\":\"https://groq.com/pricing\"},{\"title\":\"GroqCloud | Groq is fast, low cost inference.\",\"url\":\"https://groq.com/groqcloud\"},{\"title\":\"A complete guide to Groq pricing in 2025 - eesel AI\",\"url\":\"https://www.eesel.ai/blog/groq-pricing\"},{\"title\":\"Groq Pricing and Alternatives\",\"url\":\"https://blog.promptlayer.com/groq-pricing-and-alternatives/\"},{\"title\":\"What are the rate limits for the Groq API, for the Free and Dev tier plans? - FAQs - Groq Community\",\"url\":\"https://community.groq.com/t/what-are-the-rate-limits-for-the-groq-api-for-the-free-and-dev-tier-plans/42\"},{\"title\":\"What is Groq? Features, Pricing, and Use Cases\",\"url\":\"https://www.walturn.com/insights/what-is-groq-features-pricing-and-use-cases\"},{\"title\":\"A Comprehensive Comparison of Inference Providers\",\"url\":\"https://www.cloudrift.ai/blog/choosing-your-llm-powerhouse-a-comprehensive-comparison-of-inference-providers\"},{\"title\":\"GroqCloud Developer Tier: Fast, Affordable API Access for Devs | Groq is fast, low cost inference.\",\"url\":\"https://groq.com/blog/developer-tier-now-available-on-groqcloud\"},{\"title\":\"Groq Llama 3.1 Pricing Guide 2025\",\"url\":\"https://www.byteplus.com/en/topic/448470\"}]\n\nHere's what I found about Groq API cloud inference pricing for LLMs in 2025:\n\n## Groq API Pricing Overview\n\nGroq pricing is linear and predictable, with no hidden costs or idle infrastructure.(no content)Groq's approach to pricing is straightforward: you pay for what you use, measured in tokens processed.\n\n### Pricing Structure\n\nGroq's pricing structure is built around performance-based value and predictability. The platform charges per million tokens for LLM inference and per hour for on-demand GPU-equivalent compute. Specific pricing varies by model and context length.\n\n**Token Pricing Examples:**\n- Smaller models (17B parameters): As low as $0.11 per million input tokens\n- Large context or specialized models (e.g., DeepSeek R1 Distill): Up to $0.99 per million output tokens\n\n### Service Tiers\n\nGroq offers a generous Free Tier, a Developer Tier for higher token consumption, and Enterprise plans for dedicated or multi-tenant instances.\n\n**Batch API Discount:**\nThe Batch API offers efficient parallel processing for high-volume workloads β submit 1000s of API requests per batch with guaranteed 24-hour processing time at a 25% cost discount compared to synchronous APIs.\n\n### Platform Options\n\nGroqCloud is available in public, private, or co-cloud instances. It takes advantage of fast AI inference performance, powered by their purpose-built LPU, for leading GenAI models across text, audio, and vision modalities with support for LLMs, STT, TTS, and image-to-text models.\n\n### Performance & Value\n\nGroq's LPUs deliver deterministic, high-speed inference tailored for generative AI, supporting up to 1,200 tokens/sec for lightweight models, ideal for live AI applications.(no content)With a $6.9 billion valuation and over 2 million developers using its platform, Groq has positioned itself at the forefront of the inference revolution.\n\nFor detailed current pricing on specific models, you can visit [Groq's pricing page](https://groq.com/pricing) or the [GroqCloud platform](https://groq.com/groqcloud).\n\n\nREMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks." | |
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| { | |
| "title": "Groq is fast, low cost inference.", | |
| "url": "https://groq.com/" | |
| }, | |
| { | |
| "title": "Groq On-Demand Pricing for Tokens-as-a-Service | Groq is fast, low cost inference.", | |
| "url": "https://groq.com/pricing" | |
| }, | |
| { | |
| "title": "GroqCloud | Groq is fast, low cost inference.", | |
| "url": "https://groq.com/groqcloud" | |
| }, | |
| { | |
| "title": "A complete guide to Groq pricing in 2025 - eesel AI", | |
| "url": "https://www.eesel.ai/blog/groq-pricing" | |
| }, | |
| { | |
| "title": "Groq Pricing and Alternatives", | |
| "url": "https://blog.promptlayer.com/groq-pricing-and-alternatives/" | |
| }, | |
| { | |
| "title": "What are the rate limits for the Groq API, for the Free and Dev tier plans? - FAQs - Groq Community", | |
| "url": "https://community.groq.com/t/what-are-the-rate-limits-for-the-groq-api-for-the-free-and-dev-tier-plans/42" | |
| }, | |
| { | |
| "title": "What is Groq? Features, Pricing, and Use Cases", | |
| "url": "https://www.walturn.com/insights/what-is-groq-features-pricing-and-use-cases" | |
| }, | |
| { | |
| "title": "A Comprehensive Comparison of Inference Providers", | |
| "url": "https://www.cloudrift.ai/blog/choosing-your-llm-powerhouse-a-comprehensive-comparison-of-inference-providers" | |
| }, | |
| { | |
| "title": "GroqCloud Developer Tier: Fast, Affordable API Access for Devs | Groq is fast, low cost inference.", | |
| "url": "https://groq.com/blog/developer-tier-now-available-on-groqcloud" | |
| }, | |
| { | |
| "title": "Groq Llama 3.1 Pricing Guide 2025", | |
| "url": "https://www.byteplus.com/en/topic/448470" | |
| } | |
| ] | |
| }, | |
| "Here's what I found about Groq API cloud inference pricing for LLMs in 2025:\n\n## Groq API Pricing Overview\n\nGroq pricing is linear and predictable, with no hidden costs or idle infrastructure.(no content)Groq's approach to pricing is straightforward: you pay for what you use, measured in tokens processed.\n\n### Pricing Structure\n\nGroq's pricing structure is built around performance-based value and predictability. The platform charges per million tokens for LLM inference and per hour for on-demand GPU-equivalent compute. Specific pricing varies by model and context length.\n\n**Token Pricing Examples:**\n- Smaller models (17B parameters): As low as $0.11 per million input tokens\n- Large context or specialized models (e.g., DeepSeek R1 Distill): Up to $0.99 per million output tokens\n\n### Service Tiers\n\nGroq offers a generous Free Tier, a Developer Tier for higher token consumption, and Enterprise plans for dedicated or multi-tenant instances.\n\n**Batch API Discount:**\nThe Batch API offers efficient parallel processing for high-volume workloads β submit 1000s of API requests per batch with guaranteed 24-hour processing time at a 25% cost discount compared to synchronous APIs.\n\n### Platform Options\n\nGroqCloud is available in public, private, or co-cloud instances. It takes advantage of fast AI inference performance, powered by their purpose-built LPU, for leading GenAI models across text, audio, and vision modalities with support for LLMs, STT, TTS, and image-to-text models.\n\n### Performance & Value\n\nGroq's LPUs deliver deterministic, high-speed inference tailored for generative AI, supporting up to 1,200 tokens/sec for lightweight models, ideal for live AI applications.(no content)With a $6.9 billion valuation and over 2 million developers using its platform, Groq has positioned itself at the forefront of the inference revolution.\n\nFor detailed current pricing on specific models, you can visit [Groq's pricing page](https://groq.com/pricing) or the [GroqCloud platform](https://groq.com/groqcloud)." | |
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| "content": "Web search results for query: \"Vercel AI Gateway pricing features 2025\"\n\nLinks: [{\"title\":\"Pricing\",\"url\":\"https://vercel.com/docs/ai-gateway/pricing\"},{\"title\":\"AI Gateway β Vercel\",\"url\":\"https://vercel.com/ai-gateway\"},{\"title\":\"AI Gateway\",\"url\":\"https://vercel.com/docs/ai-gateway\"},{\"title\":\"Vercel Pricing: Hobby, Pro, and Enterprise plans β Vercel\",\"url\":\"https://vercel.com/pricing\"},{\"title\":\"Vercel\",\"url\":\"https://vercel.com/docs/ai-gateway/pricing.md\"},{\"title\":\"Browse AI Gateway Models β Vercel\",\"url\":\"https://vercel.com/ai-gateway/models\"},{\"title\":\"Pricing on Vercel\",\"url\":\"https://vercel.com/docs/pricing\"},{\"title\":\"AI Gateway is now generally available - Vercel\",\"url\":\"https://vercel.com/changelog/ai-gateway-is-now-generally-available\"},{\"title\":\"Introducing the AI Gateway - Vercel\",\"url\":\"https://vercel.com/blog/ai-gateway\"},{\"title\":\"Models & Providers\",\"url\":\"https://vercel.com/docs/ai-gateway/models-and-providers\"}]\n\nHere's the information about Vercel AI Gateway pricing and features in 2025:\n\n## Pricing\n\nThere are no markups to use the AI Gateway, so you're only charged for what your AI providers would bill you if you were using the provider directly.(no content)Charges are automatically deducted from your AI Gateway Credits balance and you can top up the balance at any time.\n\n### Free Tier\nEvery Vercel team account includes $5 of free usage per month, giving you the opportunity to explore the AI Gateway without any upfront costs.(no content)You'll receive $5 AI Gateway Credits every 30 days after you make your first AI Gateway request, and your free credits work across the entire model catalog.\n\n### Paid Tier\nYou can purchase AI Gateway Credits and move to a paid account, enabling you to run larger workloads. Once you purchase AI Gateway Credits, your account transitions to a pay-as-you-go model with no lock-in.(no content)Once you create a paid account, you will not receive $5 of AI Gateway Credits per month.\n\n### Bring Your Own Key\nVercel offers tokens at list price from upstream providers with no markup. If you bring your own key, they will not add any markup to your token price (0%).(no content)You are responsible for any payment processing fees.\n\n## Key Features\n\nAI Gateway became generally available on August 21, 2025, providing a single unified API to access hundreds of AI models with transparent pricing and built-in observability.(no content)The Gateway delivers sub-20ms latency routing across multiple inference providers with transparent pricing, automatic failover for higher availability, high rate limits, and detailed cost and usage analytics.(no content)It gives you the ability to set budgets, monitor usage, load-balance requests, and manage fallbacks. The design allows it to work seamlessly with AI SDK 5, OpenAI SDK, or your preferred framework.(no content)While upstream providers may have limits, Vercel doesn't place any rate limits on your queries.(no content)The AI Gateway's unified API is built to be flexible, allowing you to switch between different AI models and providers without rewriting parts of your application, which is useful for testing different models or changing the underlying AI provider for cost or performance reasons.(no content)Supported models include Grok, GPT-5, and Claude Sonnet 4, with providers including xAI, OpenAI, and Anthropic.\n\n\nREMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks." | |
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| { | |
| "title": "AI Gateway β Vercel", | |
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| "title": "Vercel Pricing: Hobby, Pro, and Enterprise plans β Vercel", | |
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| { | |
| "title": "Vercel", | |
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| "title": "Browse AI Gateway Models β Vercel", | |
| "url": "https://vercel.com/ai-gateway/models" | |
| }, | |
| { | |
| "title": "Pricing on Vercel", | |
| "url": "https://vercel.com/docs/pricing" | |
| }, | |
| { | |
| "title": "AI Gateway is now generally available - Vercel", | |
| "url": "https://vercel.com/changelog/ai-gateway-is-now-generally-available" | |
| }, | |
| { | |
| "title": "Introducing the AI Gateway - Vercel", | |
| "url": "https://vercel.com/blog/ai-gateway" | |
| }, | |
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| "title": "Models & Providers", | |
| "url": "https://vercel.com/docs/ai-gateway/models-and-providers" | |
| } | |
| ] | |
| }, | |
| "Here's the information about Vercel AI Gateway pricing and features in 2025:\n\n## Pricing\n\nThere are no markups to use the AI Gateway, so you're only charged for what your AI providers would bill you if you were using the provider directly.(no content)Charges are automatically deducted from your AI Gateway Credits balance and you can top up the balance at any time.\n\n### Free Tier\nEvery Vercel team account includes $5 of free usage per month, giving you the opportunity to explore the AI Gateway without any upfront costs.(no content)You'll receive $5 AI Gateway Credits every 30 days after you make your first AI Gateway request, and your free credits work across the entire model catalog.\n\n### Paid Tier\nYou can purchase AI Gateway Credits and move to a paid account, enabling you to run larger workloads. Once you purchase AI Gateway Credits, your account transitions to a pay-as-you-go model with no lock-in.(no content)Once you create a paid account, you will not receive $5 of AI Gateway Credits per month.\n\n### Bring Your Own Key\nVercel offers tokens at list price from upstream providers with no markup. If you bring your own key, they will not add any markup to your token price (0%).(no content)You are responsible for any payment processing fees.\n\n## Key Features\n\nAI Gateway became generally available on August 21, 2025, providing a single unified API to access hundreds of AI models with transparent pricing and built-in observability.(no content)The Gateway delivers sub-20ms latency routing across multiple inference providers with transparent pricing, automatic failover for higher availability, high rate limits, and detailed cost and usage analytics.(no content)It gives you the ability to set budgets, monitor usage, load-balance requests, and manage fallbacks. The design allows it to work seamlessly with AI SDK 5, OpenAI SDK, or your preferred framework.(no content)While upstream providers may have limits, Vercel doesn't place any rate limits on your queries.(no content)The AI Gateway's unified API is built to be flexible, allowing you to switch between different AI models and providers without rewriting parts of your application, which is useful for testing different models or changing the underlying AI provider for cost or performance reasons.(no content)Supported models include Grok, GPT-5, and Claude Sonnet 4, with providers including xAI, OpenAI, and Anthropic." | |
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| "content": "Web search results for query: \"Azure OpenAI API gateway multi-model pricing 2025\"\n\nLinks: [{\"title\":\"Azure OpenAI Service - Pricing | Microsoft Azure\",\"url\":\"https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/\"},{\"title\":\"Azure AI Foundry Models Pricing | Microsoft Azure\",\"url\":\"https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/aoai/\"},{\"title\":\"Microsoft Foundry - Pricing | Microsoft Azure\",\"url\":\"https://azure.microsoft.com/en-us/pricing/details/ai-foundry/\"},{\"title\":\"Calculating OpenAI and Azure OpenAI Service Model Usage Costs | Blog | DevRain\",\"url\":\"https://devrain.com/blog/calculating-openai-and-azure-openai-service-model-usage-costs\"},{\"title\":\"o-series Updates: New o3 pricing and o3-pro in Azure AI Foundry | Microsoft Foundry Blog\",\"url\":\"https://devblogs.microsoft.com/foundry/azure-openai-o3-pro-ai-foundry/\"},{\"title\":\"Plan to manage costs for Azure OpenAI in Azure AI ...\",\"url\":\"https://learn.microsoft.com/en-us/azure/ai-foundry/openai/how-to/manage-costs\"},{\"title\":\"Everything you wanted to know about Azure OpenAI Pricing - ECF Data\",\"url\":\"https://www.ecfdata.com/everything-you-wanted-to-know-about-azure-openai-pricing/\"},{\"title\":\"Pricing - Foundry Tools | Microsoft Azure\",\"url\":\"https://azure.microsoft.com/en-us/pricing/details/cognitive-services/\"},{\"title\":\"Cost rates and historical cost of Azure openAI models - Microsoft Q&A\",\"url\":\"https://learn.microsoft.com/en-us/answers/questions/2107857/cost-rates-and-historical-cost-of-azure-openai-mod\"},{\"title\":\"Azure OpenAI Cost Calculator | Calculate AI Costs for LLM Model | Microsoft\",\"url\":\"https://www.clearpeople.com/en/atlas-features/ai-cost-calculator\"}]\n\nBased on the search results, here's what I found about Azure OpenAI API gateway and multi-model pricing in 2025:\n\n## Azure OpenAI Service Pricing Overview\n\n### Pricing Models Available\n\nAzure OpenAI offers several pricing options:\n- **Standard (On-Demand)**: Pay-as-you-go for input and output tokens\n- **Provisioned (PTUs)**: Allocate throughput with predictable costs, with monthly and annual reservations available to reduce overall spend\n- **Batch API**: Available for global deployments and three regions, returning completions within 24 hours for a 50% discount on Global Standard Pricing\n\n### Multi-Model Support\n\nAzure AI Foundry Models includes models from OpenAI, DeepSeek, xAI's Grok, Meta's Llama, Mistral AI, FLUX by Black Forest Labs, and more. These models are fully hosted and managed on Azure, available through both pay-as-you-go and provisioned throughput options. With Provisioned Throughput, you can flex capacity across multiple models, such as OpenAI and DeepSeek, for greater efficiency and control.(no content)Azure AI Foundry is a unified platform to design, customize, manage, and support AI applications and agents with a choice of over 11,000+ models covering foundation models, reasoning models, multimodal models, industry models, and domain-specific models.\n\n### Specific Model Pricing (2025)\n\nStarting June 1st, 2025, Azure OpenAI adjusted its charges on the o3 model to the new price of $2/$8 per million input/output tokens. The new pricing will be reflected in customers' July invoices.(no content)For GPT-4o models in East US: Global Deployment costs $5 per 1,000,000 tokens for input and $15 per 1,000,000 tokens for output. Regional API has the same pricing: $5 per 1,000,000 tokens for input and $15 per 1,000,000 tokens for output.\n\n### Token-Based Billing\n\nCosts per token vary depending on which model series you choose, but all models deployed in Azure AI Foundry are charged per 1,000 tokens. For most models, pricing is now listed in terms of 1 million tokens.(no content)Models sold directly by Azure (including Azure OpenAI) are charged directly and appear as billing meters under each Azure AI Foundry resource. When you inspect your bill, you see billing meters that account for inputs and outputs for each consumed model.\n\nFor the most current and detailed pricing information, you can visit the official [Azure OpenAI Service pricing page](https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/) or the [Azure AI Foundry Models pricing page](https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/aoai/).\n\n\nREMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks." | |
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| }, | |
| { | |
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| }, | |
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| "url": "https://azure.microsoft.com/en-us/pricing/details/cognitive-services/" | |
| }, | |
| { | |
| "title": "Cost rates and historical cost of Azure openAI models - Microsoft Q&A", | |
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| { | |
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| "url": "https://www.clearpeople.com/en/atlas-features/ai-cost-calculator" | |
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| "Based on the search results, here's what I found about Azure OpenAI API gateway and multi-model pricing in 2025:\n\n## Azure OpenAI Service Pricing Overview\n\n### Pricing Models Available\n\nAzure OpenAI offers several pricing options:\n- **Standard (On-Demand)**: Pay-as-you-go for input and output tokens\n- **Provisioned (PTUs)**: Allocate throughput with predictable costs, with monthly and annual reservations available to reduce overall spend\n- **Batch API**: Available for global deployments and three regions, returning completions within 24 hours for a 50% discount on Global Standard Pricing\n\n### Multi-Model Support\n\nAzure AI Foundry Models includes models from OpenAI, DeepSeek, xAI's Grok, Meta's Llama, Mistral AI, FLUX by Black Forest Labs, and more. These models are fully hosted and managed on Azure, available through both pay-as-you-go and provisioned throughput options. With Provisioned Throughput, you can flex capacity across multiple models, such as OpenAI and DeepSeek, for greater efficiency and control.(no content)Azure AI Foundry is a unified platform to design, customize, manage, and support AI applications and agents with a choice of over 11,000+ models covering foundation models, reasoning models, multimodal models, industry models, and domain-specific models.\n\n### Specific Model Pricing (2025)\n\nStarting June 1st, 2025, Azure OpenAI adjusted its charges on the o3 model to the new price of $2/$8 per million input/output tokens. The new pricing will be reflected in customers' July invoices.(no content)For GPT-4o models in East US: Global Deployment costs $5 per 1,000,000 tokens for input and $15 per 1,000,000 tokens for output. Regional API has the same pricing: $5 per 1,000,000 tokens for input and $15 per 1,000,000 tokens for output.\n\n### Token-Based Billing\n\nCosts per token vary depending on which model series you choose, but all models deployed in Azure AI Foundry are charged per 1,000 tokens. For most models, pricing is now listed in terms of 1 million tokens.(no content)Models sold directly by Azure (including Azure OpenAI) are charged directly and appear as billing meters under each Azure AI Foundry resource. When you inspect your bill, you see billing meters that account for inputs and outputs for each consumed model.\n\nFor the most current and detailed pricing information, you can visit the official [Azure OpenAI Service pricing page](https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/) or the [Azure AI Foundry Models pricing page](https://azure.microsoft.com/en-us/pricing/details/ai-foundry-models/aoai/)." | |
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| "content": "Web search results for query: \"Fireworks AI inference API pricing 2025\"\n\nLinks: [{\"title\":\"Fireworks - Pricing\",\"url\":\"https://fireworks.ai/pricing\"},{\"title\":\"11 Best LLM API Providers: Compare Inferencing Performance & Pricing\",\"url\":\"https://www.helicone.ai/blog/llm-api-providers\"},{\"title\":\"What is Fireworks AI? Features, Pricing, and Use Cases\",\"url\":\"https://www.walturn.com/insights/what-is-fireworks-ai-features-pricing-and-use-cases\"},{\"title\":\"What is Fireworks AI? A complete guide to its features and pricing - eesel AI\",\"url\":\"https://www.eesel.ai/blog/fireworks-ai-pricing\"},{\"title\":\"A Deep Dive into AI Inference Platforms - Part 1\",\"url\":\"https://procurefyi.substack.com/p/a-deep-dive-into-ai-inference-platforms\"},{\"title\":\"Cost structure - Fireworks AI Docs\",\"url\":\"https://docs.fireworks.ai/faq/billing-pricing-usage/pricing/cost-structure\"},{\"title\":\"Compare 11 LLM API Providers 2025: Pricing, Speed, Context\",\"url\":\"https://futureagi.com/blogs/top-11-llm-api-providers-2025\"},{\"title\":\"Top 10 AI Inference Platforms in 2025 - DEV Community\",\"url\":\"https://dev.to/lina_lam_9ee459f98b67e9d5/top-10-ai-inference-platforms-in-2025-56kd\"},{\"title\":\"Fireworks AI revenue, valuation & funding | Sacra\",\"url\":\"https://sacra.com/c/fireworks-ai/\"},{\"title\":\"Fireworks Platform Spring 2024 Updates\",\"url\":\"https://fireworks.ai/blog/spring-update-faster-models-dedicated-deployments-postpaid-pricing\"}]\n\nBased on my search, here's what I found about Fireworks AI inference API pricing in 2025:\n\n## Fireworks AI Pricing Overview (2025)\n\n### Pricing Model\nFireworks AI operates on a pay-as-you-go model for all non-Enterprise usage, and new users automatically receive free credits.\n\n### Cost Structure\nYou pay based on:\n- Per token for serverless inference\n- Per GPU usage time for on-demand deployments\n- Per token of training data for fine-tuning\n\n### Batch Inference\nBatch inference is priced at 50% of their serverless pricing for both input and output tokens.\n\n### Image Models\nAll models besides the Flux Kontext models are charged by the number of inference steps (denoising iterations).\n\n### Fine-tuned Models\nDeploying fine-tuned models to serverless infrastructure is free.\n\n### New User Credits\nAll services are pay-as-you-go, with $1 in Fireworks AI free credits available for new users to test the platform.\n\n### Platform Features & Performance\nFireworks AI has one of the fastest model APIs. It uses its proprietary optimized FireAttention inference engine to power text, image, and audio inferencing, all while prioritizing data privacy with HIPAA and SOC2 compliance.(no content)Results vary by use case, but Fireworks often observes improvements like ~250% higher throughput and 50% faster speed compared to open source inference engines.\n\n### Company Growth\nIn October 2025, Fireworks AI raised a $254M Series C at a $4B valuation, bringing total funding to $331M.\n\nFor the most up-to-date specific per-token prices for different models, you would need to visit [Fireworks AI's pricing page](https://fireworks.ai/pricing) directly, as the specific token rates vary by model.\n\n\nREMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks." | |
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| "query": "Fireworks AI inference API pricing 2025", | |
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| { | |
| "title": "Fireworks - Pricing", | |
| "url": "https://fireworks.ai/pricing" | |
| }, | |
| { | |
| "title": "11 Best LLM API Providers: Compare Inferencing Performance & Pricing", | |
| "url": "https://www.helicone.ai/blog/llm-api-providers" | |
| }, | |
| { | |
| "title": "What is Fireworks AI? Features, Pricing, and Use Cases", | |
| "url": "https://www.walturn.com/insights/what-is-fireworks-ai-features-pricing-and-use-cases" | |
| }, | |
| { | |
| "title": "What is Fireworks AI? A complete guide to its features and pricing - eesel AI", | |
| "url": "https://www.eesel.ai/blog/fireworks-ai-pricing" | |
| }, | |
| { | |
| "title": "A Deep Dive into AI Inference Platforms - Part 1", | |
| "url": "https://procurefyi.substack.com/p/a-deep-dive-into-ai-inference-platforms" | |
| }, | |
| { | |
| "title": "Cost structure - Fireworks AI Docs", | |
| "url": "https://docs.fireworks.ai/faq/billing-pricing-usage/pricing/cost-structure" | |
| }, | |
| { | |
| "title": "Compare 11 LLM API Providers 2025: Pricing, Speed, Context", | |
| "url": "https://futureagi.com/blogs/top-11-llm-api-providers-2025" | |
| }, | |
| { | |
| "title": "Top 10 AI Inference Platforms in 2025 - DEV Community", | |
| "url": "https://dev.to/lina_lam_9ee459f98b67e9d5/top-10-ai-inference-platforms-in-2025-56kd" | |
| }, | |
| { | |
| "title": "Fireworks AI revenue, valuation & funding | Sacra", | |
| "url": "https://sacra.com/c/fireworks-ai/" | |
| }, | |
| { | |
| "title": "Fireworks Platform Spring 2024 Updates", | |
| "url": "https://fireworks.ai/blog/spring-update-faster-models-dedicated-deployments-postpaid-pricing" | |
| } | |
| ] | |
| }, | |
| "Based on my search, here's what I found about Fireworks AI inference API pricing in 2025:\n\n## Fireworks AI Pricing Overview (2025)\n\n### Pricing Model\nFireworks AI operates on a pay-as-you-go model for all non-Enterprise usage, and new users automatically receive free credits.\n\n### Cost Structure\nYou pay based on:\n- Per token for serverless inference\n- Per GPU usage time for on-demand deployments\n- Per token of training data for fine-tuning\n\n### Batch Inference\nBatch inference is priced at 50% of their serverless pricing for both input and output tokens.\n\n### Image Models\nAll models besides the Flux Kontext models are charged by the number of inference steps (denoising iterations).\n\n### Fine-tuned Models\nDeploying fine-tuned models to serverless infrastructure is free.\n\n### New User Credits\nAll services are pay-as-you-go, with $1 in Fireworks AI free credits available for new users to test the platform.\n\n### Platform Features & Performance\nFireworks AI has one of the fastest model APIs. It uses its proprietary optimized FireAttention inference engine to power text, image, and audio inferencing, all while prioritizing data privacy with HIPAA and SOC2 compliance.(no content)Results vary by use case, but Fireworks often observes improvements like ~250% higher throughput and 50% faster speed compared to open source inference engines.\n\n### Company Growth\nIn October 2025, Fireworks AI raised a $254M Series C at a $4B valuation, bringing total funding to $331M.\n\nFor the most up-to-date specific per-token prices for different models, you would need to visit [Fireworks AI's pricing page](https://fireworks.ai/pricing) directly, as the specific token rates vary by model." | |
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| "content": "Web search results for query: \"Kong AI Gateway features open source 2025\"\n\nLinks: [{\"title\":\"GitHub - Kong/kong: π¦ The Cloud-Native Gateway for APIs & AI\",\"url\":\"https://github.com/Kong/kong\"},{\"title\":\"Announcing Kongβs New Open Source AI Gateway | Kong Inc.\",\"url\":\"https://konghq.com/blog/product-releases/announcing-kong-ai-gateway\"},{\"title\":\"Unlocking the Power of Kong AI Gateway: A Comprehensive Guide\",\"url\":\"https://apipark.com/techblog/en/unlocking-the-power-of-kong-ai-gateway-a-comprehensive-guide/\"},{\"title\":\"Kong's new open source AI Gateway makes building multi-LLM apps easier | TechCrunch\",\"url\":\"https://techcrunch.com/2024/02/15/kongs-new-open-source-ai-gateway-makes-building-multi-llm-apps-easier/\"},{\"title\":\"Kong Open Sources Its AI Gateway for Democratizing Multi-LLM Use | TDWI\",\"url\":\"https://tdwi.org/articles/2024/02/15/kong-open-sources-ai-gateway.aspx\"},{\"title\":\"Kong AI Gateway Adds Enterprise Capabilities | TDWI\",\"url\":\"https://tdwi.org/articles/2024/05/30/kong-ai-gateway-update.aspx\"},{\"title\":\"Kong AI Gateway | Kong Docs\",\"url\":\"https://developer.konghq.com/ai-gateway/\"},{\"title\":\"Kong Open Sources New AI Gateway to Help Developers Easily Build Multi-LLM Apps\",\"url\":\"https://www.prnewswire.com/news-releases/kong-open-sources-new-ai-gateway-to-help-developers-easily-build-multi-llm-apps-302062656.html\"},{\"title\":\"Mastering Kong AI Gateway: Boost Your AI Performance\",\"url\":\"https://apipark.com/techblog/en/mastering-kong-ai-gateway-boost-your-ai-performance/\"},{\"title\":\"Kongβs AI Gateway Aims To Make Building With AI Easier - The New Stack\",\"url\":\"https://thenewstack.io/kongs-ai-gateway-aims-to-make-building-with-ai-easier/\"}]\n\nHere are the key findings about Kong AI Gateway features and open source in 2025:\n\n## Kong AI Gateway Overview\n\nKong is described as \"The Cloud-Native Gateway for APIs & AI.\"(no content)Kong announced its open source AI Gateway with multi-LLM support, no-code AI plugins, advanced prompt engineering, and more. The AI Gateway functionality is available today and free and open source for everyone.\n\n## Key Features\n\n### Multi-LLM Support\nKong provides a Universal LLM API to route across multiple providers like OpenAI, Anthropic, GCP Gemini, AWS Bedrock, Azure AI, Databricks, Mistral, Huggingface and more.(no content)The platform includes 60+ AI features like AI observability, semantic security and caching, semantic routing and more.\n\n### MCP (Model Context Protocol) Support\nKong offers MCP traffic governance, MCP security and MCP observability in addition to MCP autogeneration from any RESTful API.\n\n### AI Plugins Suite\nKong AI Gateway offers a suite of plugins including data governance (controlling how sensitive information is handled), prompt engineering (customizing and optimizing prompts), guardrails and content safety, automated RAG injection, load balancing, and LLM cost control.\n\n### Load Balancing\nAI Gateway's load balancer routes requests across AI models to optimize for speed, cost, and reliability. It supports algorithms like consistent hashing, lowest-latency, usage-based, round-robin, and semantic matching, with built-in retries and fallback for resilience.\n\n### Observability\nUsers can track token usage, latency, and costs through audit logs and metrics exporters, and instrument request flows with OpenTelemetry to trace prompts and responses across infrastructure.\n\n## Latest Version (2025)\nAI Gateway is an open source plugin for Kong's API Gateway aimed at making it easier for devs to build with AI. Kong introduced AI Gateway as a beta offering in February 2024 and rolled out enhancements in September at its API Summit. AI Gateway 3.10 went into general availability.(no content)Among AI Gateway's features are automated retrieval-augmented generation (RAG) pipelines, aimed to help reduce hallucinations by providing updated new context continuously.\n\n## Licensing\nKong is licensed under the Apache License, Version 2.0.(no content)Developers can build plugins in Lua, Go or JavaScript.\n\n\nREMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks." | |
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| { | |
| "title": "GitHub - Kong/kong: π¦ The Cloud-Native Gateway for APIs & AI", | |
| "url": "https://github.com/Kong/kong" | |
| }, | |
| { | |
| "title": "Announcing Kongβs New Open Source AI Gateway | Kong Inc.", | |
| "url": "https://konghq.com/blog/product-releases/announcing-kong-ai-gateway" | |
| }, | |
| { | |
| "title": "Unlocking the Power of Kong AI Gateway: A Comprehensive Guide", | |
| "url": "https://apipark.com/techblog/en/unlocking-the-power-of-kong-ai-gateway-a-comprehensive-guide/" | |
| }, | |
| { | |
| "title": "Kong's new open source AI Gateway makes building multi-LLM apps easier | TechCrunch", | |
| "url": "https://techcrunch.com/2024/02/15/kongs-new-open-source-ai-gateway-makes-building-multi-llm-apps-easier/" | |
| }, | |
| { | |
| "title": "Kong Open Sources Its AI Gateway for Democratizing Multi-LLM Use | TDWI", | |
| "url": "https://tdwi.org/articles/2024/02/15/kong-open-sources-ai-gateway.aspx" | |
| }, | |
| { | |
| "title": "Kong AI Gateway Adds Enterprise Capabilities | TDWI", | |
| "url": "https://tdwi.org/articles/2024/05/30/kong-ai-gateway-update.aspx" | |
| }, | |
| { | |
| "title": "Kong AI Gateway | Kong Docs", | |
| "url": "https://developer.konghq.com/ai-gateway/" | |
| }, | |
| { | |
| "title": "Kong Open Sources New AI Gateway to Help Developers Easily Build Multi-LLM Apps", | |
| "url": "https://www.prnewswire.com/news-releases/kong-open-sources-new-ai-gateway-to-help-developers-easily-build-multi-llm-apps-302062656.html" | |
| }, | |
| { | |
| "title": "Mastering Kong AI Gateway: Boost Your AI Performance", | |
| "url": "https://apipark.com/techblog/en/mastering-kong-ai-gateway-boost-your-ai-performance/" | |
| }, | |
| { | |
| "title": "Kongβs AI Gateway Aims To Make Building With AI Easier - The New Stack", | |
| "url": "https://thenewstack.io/kongs-ai-gateway-aims-to-make-building-with-ai-easier/" | |
| } | |
| ] | |
| }, | |
| "Here are the key findings about Kong AI Gateway features and open source in 2025:\n\n## Kong AI Gateway Overview\n\nKong is described as \"The Cloud-Native Gateway for APIs & AI.\"(no content)Kong announced its open source AI Gateway with multi-LLM support, no-code AI plugins, advanced prompt engineering, and more. The AI Gateway functionality is available today and free and open source for everyone.\n\n## Key Features\n\n### Multi-LLM Support\nKong provides a Universal LLM API to route across multiple providers like OpenAI, Anthropic, GCP Gemini, AWS Bedrock, Azure AI, Databricks, Mistral, Huggingface and more.(no content)The platform includes 60+ AI features like AI observability, semantic security and caching, semantic routing and more.\n\n### MCP (Model Context Protocol) Support\nKong offers MCP traffic governance, MCP security and MCP observability in addition to MCP autogeneration from any RESTful API.\n\n### AI Plugins Suite\nKong AI Gateway offers a suite of plugins including data governance (controlling how sensitive information is handled), prompt engineering (customizing and optimizing prompts), guardrails and content safety, automated RAG injection, load balancing, and LLM cost control.\n\n### Load Balancing\nAI Gateway's load balancer routes requests across AI models to optimize for speed, cost, and reliability. It supports algorithms like consistent hashing, lowest-latency, usage-based, round-robin, and semantic matching, with built-in retries and fallback for resilience.\n\n### Observability\nUsers can track token usage, latency, and costs through audit logs and metrics exporters, and instrument request flows with OpenTelemetry to trace prompts and responses across infrastructure.\n\n## Latest Version (2025)\nAI Gateway is an open source plugin for Kong's API Gateway aimed at making it easier for devs to build with AI. Kong introduced AI Gateway as a beta offering in February 2024 and rolled out enhancements in September at its API Summit. AI Gateway 3.10 went into general availability.(no content)Among AI Gateway's features are automated retrieval-augmented generation (RAG) pipelines, aimed to help reduce hallucinations by providing updated new context continuously.\n\n## Licensing\nKong is licensed under the Apache License, Version 2.0.(no content)Developers can build plugins in Lua, Go or JavaScript." | |
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| "content": "Web search results for query: \"DeepInfra API inference pricing models 2025\"\n\nLinks: [{\"title\":\"Simple Pricing | Machine Learning Infrastructure | Deep Infra\",\"url\":\"https://deepinfra.com/pricing\"},{\"title\":\"DeepInfra - the inference partner that meets your needs\",\"url\":\"https://deepinfra.com/\"},{\"title\":\"Models | Machine Learning Inference | Deep Infra\",\"url\":\"https://deepinfra.com/models\"},{\"title\":\"DeepSeek AI Model APIs via DeepInfra\",\"url\":\"https://deepinfra.ai/deepseek\"},{\"title\":\"Llama AI Model APIs via DeepInfra\",\"url\":\"https://deepinfra.com/llama\"},{\"title\":\"DeepInfra | OpenRouter\",\"url\":\"https://openrouter.ai/provider/deepinfra\"},{\"title\":\"API Reference | AI Inference Platform | Deep Infra\",\"url\":\"https://deepinfra.com/docs/api-reference\"},{\"title\":\"The Token Arbitrage: Groq vs. DeepInfra vs. Cerebras vs Fireworks vs Hyperbolic (2025 Benchmark) | by Aparna Pradhan | Dec, 2025 | GoPenAI\",\"url\":\"https://blog.gopenai.com/the-token-arbitrage-groq-vs-deepinfra-vs-cerebras-vs-fireworks-vs-hyperbolic-2025-benchmark-ccd3c2720cc8\"},{\"title\":\"DeepInfra API | AI Inference Platform | Deep Infra\",\"url\":\"https://deepinfra.com/docs/deep_infra_api\"},{\"title\":\"Nemotron AI Model APIs via DeepInfra\",\"url\":\"https://deepinfra.com/nemotron\"}]\n\nBased on my search results, here's information about DeepInfra's API inference pricing models for 2025:\n\n## DeepInfra API Inference Pricing Models (2025)\n\n### Pricing Structure\n\nDeepInfra has different pricing models depending on the model used. Some of their language models offer per-token pricing, while most other models are billed for inference execution time. With this pricing model, you only pay for what you use.(no content)They provide only pay-what-you-use pricing with no long-term contracts or upfront costs for their machine learning models and infrastructure.\n\n### Infrastructure\n\nAll models run on H100 or A100 GPUs, optimized for inference performance and low latency. The system automatically scales to more hardware based on user needs. Each account is limited to 200 concurrent requests.\n\n### Example Model Pricing (2025)\n\nHere are some specific pricing examples:\n\n| Model | Input Tokens (per 1M) | Output Tokens (per 1M) |\n|-------|----------------------|------------------------|\n| DeepSeek-V3.2-Exp | $0.27 | $0.40 |\n| Llama 4 Scout (17B, 16 experts) | $0.08 | $0.30 |\n| NVIDIA Nemotron 3 Nano | $0.06 | $0.24 |\n| Meta-Llama-3.1-8B-Instruct | $0.03 | $0.05 |\n\n### Available Models\n\nDeepInfra provides 100+ models to cover various needs. These include:\n- Llama 4 collection - natively multimodal AI models that enable text and multimodal experiences\n- Claude models by Anthropic - highly performant, trustworthy AI models built for complex reasoning, advanced coding, and nuanced language understanding\n- Qwen series - a comprehensive suite of dense and mixture-of-experts models\n- Mistral AI models - open-source AI models built for multilingual excellence, advanced reasoning, and cost-effective performance\n\n### Billing Tiers\n\nEvery user is part of a usage tier. As usage and spending increases, users are automatically moved to the next usage tier. Every tier has an invoicing threshold, and once reached, an invoice is automatically generated.(no content)An invoice is always generated at the beginning of the month, and also throughout the month if users hit their tier invoicing threshold. Users can also set a spending limit to avoid surprises.\n\n\nREMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks." | |
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| "title": "Simple Pricing | Machine Learning Infrastructure | Deep Infra", | |
| "url": "https://deepinfra.com/pricing" | |
| }, | |
| { | |
| "title": "DeepInfra - the inference partner that meets your needs", | |
| "url": "https://deepinfra.com/" | |
| }, | |
| { | |
| "title": "Models | Machine Learning Inference | Deep Infra", | |
| "url": "https://deepinfra.com/models" | |
| }, | |
| { | |
| "title": "DeepSeek AI Model APIs via DeepInfra", | |
| "url": "https://deepinfra.ai/deepseek" | |
| }, | |
| { | |
| "title": "Llama AI Model APIs via DeepInfra", | |
| "url": "https://deepinfra.com/llama" | |
| }, | |
| { | |
| "title": "DeepInfra | OpenRouter", | |
| "url": "https://openrouter.ai/provider/deepinfra" | |
| }, | |
| { | |
| "title": "API Reference | AI Inference Platform | Deep Infra", | |
| "url": "https://deepinfra.com/docs/api-reference" | |
| }, | |
| { | |
| "title": "The Token Arbitrage: Groq vs. DeepInfra vs. Cerebras vs Fireworks vs Hyperbolic (2025 Benchmark) | by Aparna Pradhan | Dec, 2025 | GoPenAI", | |
| "url": "https://blog.gopenai.com/the-token-arbitrage-groq-vs-deepinfra-vs-cerebras-vs-fireworks-vs-hyperbolic-2025-benchmark-ccd3c2720cc8" | |
| }, | |
| { | |
| "title": "DeepInfra API | AI Inference Platform | Deep Infra", | |
| "url": "https://deepinfra.com/docs/deep_infra_api" | |
| }, | |
| { | |
| "title": "Nemotron AI Model APIs via DeepInfra", | |
| "url": "https://deepinfra.com/nemotron" | |
| } | |
| ] | |
| }, | |
| "Based on my search results, here's information about DeepInfra's API inference pricing models for 2025:\n\n## DeepInfra API Inference Pricing Models (2025)\n\n### Pricing Structure\n\nDeepInfra has different pricing models depending on the model used. Some of their language models offer per-token pricing, while most other models are billed for inference execution time. With this pricing model, you only pay for what you use.(no content)They provide only pay-what-you-use pricing with no long-term contracts or upfront costs for their machine learning models and infrastructure.\n\n### Infrastructure\n\nAll models run on H100 or A100 GPUs, optimized for inference performance and low latency. The system automatically scales to more hardware based on user needs. Each account is limited to 200 concurrent requests.\n\n### Example Model Pricing (2025)\n\nHere are some specific pricing examples:\n\n| Model | Input Tokens (per 1M) | Output Tokens (per 1M) |\n|-------|----------------------|------------------------|\n| DeepSeek-V3.2-Exp | $0.27 | $0.40 |\n| Llama 4 Scout (17B, 16 experts) | $0.08 | $0.30 |\n| NVIDIA Nemotron 3 Nano | $0.06 | $0.24 |\n| Meta-Llama-3.1-8B-Instruct | $0.03 | $0.05 |\n\n### Available Models\n\nDeepInfra provides 100+ models to cover various needs. These include:\n- Llama 4 collection - natively multimodal AI models that enable text and multimodal experiences\n- Claude models by Anthropic - highly performant, trustworthy AI models built for complex reasoning, advanced coding, and nuanced language understanding\n- Qwen series - a comprehensive suite of dense and mixture-of-experts models\n- Mistral AI models - open-source AI models built for multilingual excellence, advanced reasoning, and cost-effective performance\n\n### Billing Tiers\n\nEvery user is part of a usage tier. As usage and spending increases, users are automatically moved to the next usage tier. Every tier has an invoicing threshold, and once reached, an invoice is automatically generated.(no content)An invoice is always generated at the beginning of the month, and also throughout the month if users hit their tier invoicing threshold. Users can also set a spending limit to avoid surprises." | |
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| "content": "Web search results for query: \"Unify AI model gateway pricing features 2025\"\n\nLinks: [{\"title\":\"AI Gateway now gives you access to your favorite AI models, dynamic routing and more β through just one endpoint\",\"url\":\"https://blog.cloudflare.com/ai-gateway-aug-2025-refresh/\"},{\"title\":\"Unify Reviews 2025: Details, Pricing, & Features | G2\",\"url\":\"https://www.g2.com/products/unify-ai-unify/reviews\"},{\"title\":\"UnifyGTM Pricing: Is It Worth It in 2025?\",\"url\":\"https://www.warmly.ai/p/blog/unifygtm-pricing\"},{\"title\":\"Enterprise-grade AI Gateway | Portkey\",\"url\":\"https://portkey.ai/features/ai-gateway\"},{\"title\":\"UnifyGTM Overview (2025) β Features, Pros, Cons & Pricing\",\"url\":\"https://www.salesforge.ai/directory/sales-tools/unifygtm\"},{\"title\":\"Unify AI Alternatives 2025: 7 Best Picks vs ShareAI\",\"url\":\"https://shareai.now/blog/alternatives/unify-ai-alternatives/\"},{\"title\":\"AI Gateway\",\"url\":\"https://vercel.com/docs/ai-gateway\"},{\"title\":\"Unify GTM Reviews 2025: Pricing, Features & More\",\"url\":\"https://www.selecthub.com/p/ai-sales-agent-tools/unify-gtm/\"},{\"title\":\"Top 5 LLM Gateways in 2025: The Complete Guide to Choosing the Best AI Gateway\",\"url\":\"https://www.helicone.ai/blog/top-llm-gateways-comparison-2025\"},{\"title\":\"Unify Review 2025 | Sales & Revenue Operations Tool - Pricing & Features\",\"url\":\"https://aiagentslist.com/agents/unify\"}]\n\nBased on my search results, I found information about **Unify AI** (unify.ai) as an AI model gateway/LLM routing platform. Here's what I found:\n\n## Unify AI - Model Gateway Overview\n\nUnify is the central platform for optimized LLM deployment. With a single API key and unified prompting syntax, Unify lets you call and benchmark all third-party LLM endpoint providers; find the endpoints that match your speed, latency and cost requirements; and automatically route any prompt to the best LLM using a global mixture-of-experts that's better, faster and cheaper than any individual model.\n\n### Key Features\n\nUnify.AI is a highly customizable LLMOps platform that prioritizes simplicity and customization over complexity. It's designed for developers who want to build custom interfaces for logging, evaluations, guardrails, and other LLM operations without the overhead of advanced features.(no content)Key features include: Simple Interface (clean UI for basic routing needs), Provider-Level Routing (route between different AI providers), and Basic Caching (simple response caching to reduce costs). It's best for small projects or teams with basic routing needs who only need to switch between providers, not specific models.(no content)Unify AI focuses on performance-oriented routing and evaluation: benchmark models on your prompts, then steer traffic to candidates expected to produce higher-quality outputs. That's valuable when you have measurable task quality and want repeatable improvements over time.\n\n### Positioning in the Market\n\nWhat Unify isn't: a transparent provider marketplace that foregrounds per-provider price, latency, uptime, and availability before you route; nor is it primarily about multi-provider failover with user-visible provider stats.\n\n---\n\n**Note:** The search results also returned information about **UnifyGTM**, which is a different product - a go-to-market/sales platform, not an AI model gateway. That product has a Growth plan starting at $700/month.\n\nFor specific pricing details on Unify AI (the model gateway at unify.ai), the search results did not provide explicit pricing information. You may need to visit their website directly at unify.ai for current pricing details.\n\n\nREMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks." | |
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| "title": "AI Gateway now gives you access to your favorite AI models, dynamic routing and more β through just one endpoint", | |
| "url": "https://blog.cloudflare.com/ai-gateway-aug-2025-refresh/" | |
| }, | |
| { | |
| "title": "Unify Reviews 2025: Details, Pricing, & Features | G2", | |
| "url": "https://www.g2.com/products/unify-ai-unify/reviews" | |
| }, | |
| { | |
| "title": "UnifyGTM Pricing: Is It Worth It in 2025?", | |
| "url": "https://www.warmly.ai/p/blog/unifygtm-pricing" | |
| }, | |
| { | |
| "title": "Enterprise-grade AI Gateway | Portkey", | |
| "url": "https://portkey.ai/features/ai-gateway" | |
| }, | |
| { | |
| "title": "UnifyGTM Overview (2025) β Features, Pros, Cons & Pricing", | |
| "url": "https://www.salesforge.ai/directory/sales-tools/unifygtm" | |
| }, | |
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| "title": "Unify AI Alternatives 2025: 7 Best Picks vs ShareAI", | |
| "url": "https://shareai.now/blog/alternatives/unify-ai-alternatives/" | |
| }, | |
| { | |
| "title": "AI Gateway", | |
| "url": "https://vercel.com/docs/ai-gateway" | |
| }, | |
| { | |
| "title": "Unify GTM Reviews 2025: Pricing, Features & More", | |
| "url": "https://www.selecthub.com/p/ai-sales-agent-tools/unify-gtm/" | |
| }, | |
| { | |
| "title": "Top 5 LLM Gateways in 2025: The Complete Guide to Choosing the Best AI Gateway", | |
| "url": "https://www.helicone.ai/blog/top-llm-gateways-comparison-2025" | |
| }, | |
| { | |
| "title": "Unify Review 2025 | Sales & Revenue Operations Tool - Pricing & Features", | |
| "url": "https://aiagentslist.com/agents/unify" | |
| } | |
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| "Based on my search results, I found information about **Unify AI** (unify.ai) as an AI model gateway/LLM routing platform. Here's what I found:\n\n## Unify AI - Model Gateway Overview\n\nUnify is the central platform for optimized LLM deployment. With a single API key and unified prompting syntax, Unify lets you call and benchmark all third-party LLM endpoint providers; find the endpoints that match your speed, latency and cost requirements; and automatically route any prompt to the best LLM using a global mixture-of-experts that's better, faster and cheaper than any individual model.\n\n### Key Features\n\nUnify.AI is a highly customizable LLMOps platform that prioritizes simplicity and customization over complexity. It's designed for developers who want to build custom interfaces for logging, evaluations, guardrails, and other LLM operations without the overhead of advanced features.(no content)Key features include: Simple Interface (clean UI for basic routing needs), Provider-Level Routing (route between different AI providers), and Basic Caching (simple response caching to reduce costs). It's best for small projects or teams with basic routing needs who only need to switch between providers, not specific models.(no content)Unify AI focuses on performance-oriented routing and evaluation: benchmark models on your prompts, then steer traffic to candidates expected to produce higher-quality outputs. That's valuable when you have measurable task quality and want repeatable improvements over time.\n\n### Positioning in the Market\n\nWhat Unify isn't: a transparent provider marketplace that foregrounds per-provider price, latency, uptime, and availability before you route; nor is it primarily about multi-provider failover with user-visible provider stats.\n\n---\n\n**Note:** The search results also returned information about **UnifyGTM**, which is a different product - a go-to-market/sales platform, not an AI model gateway. That product has a Growth plan starting at $700/month.\n\nFor specific pricing details on Unify AI (the model gateway at unify.ai), the search results did not provide explicit pricing information. You may need to visit their website directly at unify.ai for current pricing details." | |
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| "content": "Web search results for query: \"Novita AI API inference pricing 2025\"\n\nLinks: [{\"title\":\"Pricing | Novita AI\",\"url\":\"https://novita.ai/pricing\"},{\"title\":\"Novita AI β Model Libraries & GPU Cloud - Deploy, Scale & Innovate\",\"url\":\"https://novita.ai\"},{\"title\":\"GPT OSS on Novita AI: Access OpenAIβs Open-Source Models via API | by Novita AI | Medium\",\"url\":\"https://medium.com/@marketing_novita.ai/gpt-oss-on-novita-ai-access-openais-open-source-models-via-api-b62c87f378a0\"},{\"title\":\"Novita | Review, Pricing & Alternatives\",\"url\":\"https://getdeploying.com/novita-ai\"},{\"title\":\"Novita AI: The Developer's Secret Weapon for 2025?\",\"url\":\"https://skywork.ai/skypage/en/Novita-AI-The-Developer's-Secret-Weapon-for-2025/1972874757982056448\"},{\"title\":\"Qwen3-Next-80B-A3B API Provider: Choose Smarter for Better AI - Novita\",\"url\":\"https://blogs.novita.ai/qwen3-next-80b-a3b-api-provider-choose-smarter-for-better-ai/\"},{\"title\":\"Top 10 AI Inference Providers in 2025 - Novita\",\"url\":\"https://blogs.novita.ai/top-10-ai-inference-providers-in-2025/\"},{\"title\":\"Top 10 AI Inference Providers in 2025 | by Novita AI | Medium\",\"url\":\"https://medium.com/@marketing_novita.ai/top-10-ai-inference-providers-in-2025-d990ba259b58\"},{\"title\":\"Novita AI LLM Inference API - Novita AI LLM Chat APIs empower your conversations on any topic of your choiceοΌCost-Effective: Transparent, low-cost pricing: $0.20 per million tokens, with no hidden fees or escalating costs. - Auto Scaling:fast scaling infrastructure. Updating models and Scaling datas can be performed offline. - Stable and Reliable: Maintain low latency in less than 2 seconds, Fast network with private information protected.\",\"url\":\"https://devhunt.org/tool/novita\"},{\"title\":\"Novita\",\"url\":\"https://huggingface.co/docs/inference-providers/en/providers/novita\"}]\n\nBased on my search results, here's what I found about Novita AI API inference pricing in 2025:\n\n## Novita AI API Inference Pricing (2025)\n\n### Pricing Model\nNovita AI uses a transparent, flexible pricing model. For its Model APIs, it's a Pay-As-You-Go system, where you're billed per API call or, for LLMs, per million tokens (e.g., ~$0.27/M input tokens for some models).\n\n### Current Promotions\nNovita AI currently offers up to 20% OFF during their \"Build Month\" with limited-time discounts on Models, GPUs, and Sandbox.(no content)Batch inference is available at an introductory 50% discount on input and output tokens for supported models.\n\n### Specific Model Pricing Examples\n\n**GPT OSS Models:**\nNovita AI is offering the GPT OSS at the following pricing:\n- gpt-oss-120b: $0.10 input / $0.50 output per million tokens\n- gpt-oss-20b: $0.05 input / $0.20 output per million tokens\n\n### Platform Features\nNovita AI provides pricing for 200+ AI models, GPU instances, and agent sandboxes. The platform is developer-focused with startup-friendly rates and no hidden fees.(no content)GPUs are ideal for training, finetuning, and high-throughput inference, available on-demand or spot at 50% off. Agent sandboxes run autonomous agents in isolated containers with ~200 ms startups, billed per-second for CPU/RAM.\n\n### Image/Video Pricing\nPricing may vary based on image dimensions, inference steps, and upscaling factors. For video, pricing may vary based on the number of frames, chosen model, and inference steps. Users can use the Pricing Calculator for estimates.\n\n### Platform Positioning\nNovita is described as \"the go-to inference platform for AI developers seeking a low-cost, reliable, and simple solution for shipping AI models,\" offering 200+ APIs (LLMs, image, video, audio) with fully managed deployment β enterprise-grade, scalable, and maintenance-free.\n\nFor the most accurate and up-to-date pricing details, you can visit their official pricing page at [novita.ai/pricing](https://novita.ai/pricing).\n\n\nREMINDER: You MUST include the sources above in your response to the user using markdown hyperlinks." | |
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| "title": "Novita AI β Model Libraries & GPU Cloud - Deploy, Scale & Innovate", | |
| "url": "https://novita.ai" | |
| }, | |
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| "title": "GPT OSS on Novita AI: Access OpenAIβs Open-Source Models via API | by Novita AI | Medium", | |
| "url": "https://medium.com/@marketing_novita.ai/gpt-oss-on-novita-ai-access-openais-open-source-models-via-api-b62c87f378a0" | |
| }, | |
| { | |
| "title": "Novita | Review, Pricing & Alternatives", | |
| "url": "https://getdeploying.com/novita-ai" | |
| }, | |
| { | |
| "title": "Novita AI: The Developer's Secret Weapon for 2025?", | |
| "url": "https://skywork.ai/skypage/en/Novita-AI-The-Developer's-Secret-Weapon-for-2025/1972874757982056448" | |
| }, | |
| { | |
| "title": "Qwen3-Next-80B-A3B API Provider: Choose Smarter for Better AI - Novita", | |
| "url": "https://blogs.novita.ai/qwen3-next-80b-a3b-api-provider-choose-smarter-for-better-ai/" | |
| }, | |
| { | |
| "title": "Top 10 AI Inference Providers in 2025 - Novita", | |
| "url": "https://blogs.novita.ai/top-10-ai-inference-providers-in-2025/" | |
| }, | |
| { | |
| "title": "Top 10 AI Inference Providers in 2025 | by Novita AI | Medium", | |
| "url": "https://medium.com/@marketing_novita.ai/top-10-ai-inference-providers-in-2025-d990ba259b58" | |
| }, | |
| { | |
| "title": "Novita AI LLM Inference API - Novita AI LLM Chat APIs empower your conversations on any topic of your choiceοΌCost-Effective: Transparent, low-cost pricing: $0.20 per million tokens, with no hidden fees or escalating costs. - Auto Scaling:fast scaling infrastructure. Updating models and Scaling datas can be performed offline. - Stable and Reliable: Maintain low latency in less than 2 seconds, Fast network with private information protected.", | |
| "url": "https://devhunt.org/tool/novita" | |
| }, | |
| { | |
| "title": "Novita", | |
| "url": "https://huggingface.co/docs/inference-providers/en/providers/novita" | |
| } | |
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| "Based on my search results, here's what I found about Novita AI API inference pricing in 2025:\n\n## Novita AI API Inference Pricing (2025)\n\n### Pricing Model\nNovita AI uses a transparent, flexible pricing model. For its Model APIs, it's a Pay-As-You-Go system, where you're billed per API call or, for LLMs, per million tokens (e.g., ~$0.27/M input tokens for some models).\n\n### Current Promotions\nNovita AI currently offers up to 20% OFF during their \"Build Month\" with limited-time discounts on Models, GPUs, and Sandbox.(no content)Batch inference is available at an introductory 50% discount on input and output tokens for supported models.\n\n### Specific Model Pricing Examples\n\n**GPT OSS Models:**\nNovita AI is offering the GPT OSS at the following pricing:\n- gpt-oss-120b: $0.10 input / $0.50 output per million tokens\n- gpt-oss-20b: $0.05 input / $0.20 output per million tokens\n\n### Platform Features\nNovita AI provides pricing for 200+ AI models, GPU instances, and agent sandboxes. The platform is developer-focused with startup-friendly rates and no hidden fees.(no content)GPUs are ideal for training, finetuning, and high-throughput inference, available on-demand or spot at 50% off. Agent sandboxes run autonomous agents in isolated containers with ~200 ms startups, billed per-second for CPU/RAM.\n\n### Image/Video Pricing\nPricing may vary based on image dimensions, inference steps, and upscaling factors. For video, pricing may vary based on the number of frames, chosen model, and inference steps. Users can use the Pricing Calculator for estimates.\n\n### Platform Positioning\nNovita is described as \"the go-to inference platform for AI developers seeking a low-cost, reliable, and simple solution for shipping AI models,\" offering 200+ APIs (LLMs, image, video, audio) with fully managed deployment β enterprise-grade, scalable, and maintenance-free.\n\nFor the most accurate and up-to-date pricing details, you can visit their official pricing page at [novita.ai/pricing](https://novita.ai/pricing)." | |
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| "text": "Now I have gathered substantial research. Let me update the todos and start creating the documents:" | |
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| [2025-12-28T03:08:23.831Z] [INFO] { | |
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| { | |
| "content": "Update PR description and mark as ready for review", | |
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| [2025-12-28T03:11:21.895Z] [INFO] {"type":"assistant","message":{"model":"claude-opus-4-5-20251101","id":"msg_012iiWVEfCz4FPAMaXepzJHY","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01H4AvbiSTwguBbHkUoeoqQ7","name":"Write","input":{"file_path":"/tmp/gh-issue-solver-1766891018916/ai-aggregator-api-gateways.md","content":"# AI Aggregator API Gateways: A Comprehensive Guide\n\nThis guide provides a comprehensive comparison of AI aggregator API gatewaysβservices that provide unified API access to multiple AI providers (OpenAI, Anthropic, Google, and more) through a single interface. These platforms eliminate the need to manage separate integrations, billing, and API keys for each AI provider. Below, we evaluate leading solutionsβOpenRouter, LiteLLM, Portkey, Helicone, Cloudflare AI Gateway, Vercel AI Gateway, Kong AI Gateway, Amazon Bedrock, Together AI, Groq, Martian, DeepInfra, Fireworks AI, Eden AI, and Novita AIβfocusing on their model access, pricing, and key features. The analysis prioritizes fair pricing and open-source options where possible, ensuring you have the information needed to make an informed decision.\n\n### Key Points (Updated December 2025)\n- **OpenRouter** is the leading model aggregator with 500+ models from 60+ providers, offering a unified API with no pricing markup and a 5.5% credit purchase fee.\n- **LiteLLM** is the most popular open-source AI gateway with 100+ model support, self-hostable with MIT license, and 8ms P95 latency at 1k RPS.\n- **Portkey** provides enterprise-grade governance with 1,600+ LLM connections, SOC 2/ISO 27001 compliance, and 10K+ GitHub stars.\n- **Helicone** offers zero-markup pricing with built-in observability, written in Rust for ultra-fast performance (8ms P50 latency).\n- **Cloudflare AI Gateway** features unified billing with 20+ provider support and global edge caching at no base cost.\n- **Vercel AI Gateway** became generally available in August 2025 with sub-20ms latency routing and $5 free monthly credits.\n- **Kong AI Gateway** is open-source (Apache 2.0) with 60+ AI features and MCP traffic governance.\n- **Amazon Bedrock** provides enterprise AWS integration with 11,000+ models through Azure AI Foundry and AgentCore Gateway.\n- **Together AI** offers 200+ open-source models with inference 11x lower cost than GPT-4o using Llama 3.3 70B.\n- **Groq** delivers ultra-fast inference (up to 1,200 tokens/sec) powered by purpose-built LPU hardware.\n\n### Why Choose an AI Aggregator API Gateway?\nManaging multiple AI provider accounts, billing systems, and API keys creates operational overhead and complexity. AI aggregator gateways solve this by offering:\n- **Single API**: One endpoint to access hundreds of AI models from different providers\n- **Unified Billing**: One consolidated invoice instead of tracking multiple vendor bills\n- **Automatic Failover**: If one provider fails, requests automatically route to another\n- **Model Flexibility**: Switch between models without changing your code\n- **Reduced Vendor Lock-in**: Abstract away providers so you can easily migrate\n- **Cost Optimization**: Compare pricing across providers and route to the most cost-effective option\n\nAccording to the 2025 Gartner Hype Cycle for Generative AI, AI Gateways are no longer optionalβthey've become a critical part of the AI stack.\n\n### Top Solutions at a Glance\n- **OpenRouter**: Best for easy multi-model access with no markup on provider pricing\n- **LiteLLM**: Best open-source self-hosted solution with maximum flexibility\n- **Portkey**: Ideal for enterprises requiring governance, compliance, and advanced access controls\n- **Helicone**: Best for observability-focused teams wanting zero markup and Rust-based performance\n- **Cloudflare AI Gateway**: Perfect for developers already in the Cloudflare ecosystem\n- **Vercel AI Gateway**: Optimal for Vercel users and AI SDK integration\n- **Kong AI Gateway**: Best for organizations wanting open-source with enterprise plugin ecosystem\n- **Amazon Bedrock**: Ideal for AWS-integrated enterprise deployments\n- **Together AI**: Best for open-source model inference at scale\n- **Groq**: Best for latency-sensitive applications requiring ultra-fast inference\n\n### How to Choose\n- **If you want simple multi-model access**: OpenRouter provides the easiest path with 500+ models\n- **If you prefer self-hosted**: LiteLLM or Kong AI Gateway offer full control with open-source licenses\n- **If you need enterprise governance**: Portkey provides comprehensive compliance and access controls\n- **If observability is critical**: Helicone offers built-in analytics with zero markup\n- **If you're in the AWS ecosystem**: Amazon Bedrock provides native integration\n- **If you need fastest inference**: Groq's LPU hardware delivers up to 1,200 tokens/sec\n- **If budget is a concern**: LiteLLM, Kong, and Helicone offer free open-source options\n\n---\n\n# Comprehensive Analysis of AI Aggregator API Gateways (Updated December 2025)\n\nThis comprehensive analysis evaluates AI aggregator API gateways, focusing on the most popular and capable platforms available as of December 2025. These services enable developers to access multiple AI providers through a unified API, simplifying integration, billing, and operations. The report assesses their model support, pricing, features, and suitability for different use cases. It emphasizes fair pricing and open-source options, providing a detailed guide for developers and enterprises.\n\n## Background and Context\nAI aggregator API gateways have become essential infrastructure for modern AI applications. As the AI landscape fragments with new models from OpenAI, Anthropic, Google, xAI, Meta, Mistral, and dozens of other providers, managing separate integrations becomes increasingly complex. These gateways provide a unified interface to route requests, debug problems, analyze performance, and optimize costs across all providers.\n\nThe market has matured significantly in 2025, with clear leaders emerging in different categories: pure aggregators like OpenRouter for easy access, open-source solutions like LiteLLM for flexibility, and enterprise platforms like Portkey for governance. AI Gateways now appear in the Gartner Hype Cycle for Generative AI, 2025, reflecting their critical role in production AI systems.\n\n### Model Availability Summary (December 2025)\n- **OpenAI**: GPT-5, GPT-5.1, GPT-5.2-Codex, o3, o3-mini, GPT-4o\n- **Anthropic**: Claude Opus 4.5, Opus 4, Sonnet 4.5, Sonnet 4, Haiku 4.5\n- **Google**: Gemini 3 Flash/Pro, Gemini 2.5 Pro/Flash\n- **xAI**: Grok 4, Grok 3\n- **Meta**: Llama 4, Llama 3.3 70B, Llama 3.1 405B\n- **Open Source**: DeepSeek-V3, Qwen3-Coder, Mistral Large, NVIDIA Nemotron\n\n## Methodology\nThe research involved extensive web searches to verify the features, supported models, pricing, and capabilities of each AI aggregator gateway. Official documentation, blogs, GitHub repositories, and community discussions were cross-referenced to ensure accuracy. GitHub star counts, pricing pages, and feature announcements were verified directly from source.\n\n## Detailed Analysis of AI Aggregator API Gateways\n\n### OpenRouter\n- **Description**: OpenRouter is the leading model aggregator providing a single, standardized API to access 500+ models from 60+ providers. It's fully OpenAI compatibleβdevelopers can switch by just changing the endpoint URL. [Source](https://openrouter.ai/)\n- **Model Support**: Access to 500+ models including GPT-5, Claude Opus 4.5, Gemini 3, Grok 4, Llama 4, DeepSeek-V3, and more. New models are added continuously.\n- **Key Features**:\n - OpenAI-compatible API format for drop-in replacement\n - Automatic fallback when routing is enabled (billed only for successful runs)\n - Privacy filters and content moderation options\n - Multimodal inputs including audio and PDF (August 2025)\n - Models API for free access to model metadata\n - RSS feed for new model updates\n- **Pricing**: No markup on provider pricingβyou pay exactly what providers charge. Credit purchase fees: 5.5% via card (minimum $0.80), 5% via crypto (no minimum). Enterprise pricing available with volume discounts, prepayment credits, and annual commits. [Source](https://openrouter.ai/pricing)\n- **Usage Limits**: Pay-as-you-go with automatic or manual top-up. Enterprise invoicing available.\n- **Why It Fits**: Best for developers wanting easy multi-model access without markup. The most comprehensive model catalog with straightforward pricing.\n\n### LiteLLM\n- **Description**: LiteLLM is an open-source (MIT license) proxy server that unifies access to 100+ LLMs through a single, OpenAI-compatible API. It provides unified model access, authentication, load balancing, fallbacks, and spend tracking. [Source](https://github.com/BerriAI/litellm)\n- **Model Support**: 100+ providers including OpenAI, Anthropic, Azure OpenAI, VertexAI, NVIDIA, HuggingFace, Bedrock, Ollama, OpenRouter, and more.\n- **Key Features**:\n - OpenAI-format API compatibility for all providers\n - Cost attribution and reporting with Postgres integration\n - Budgets and rate limits per user/team\n - Guardrails for content safety\n - Fallback logic for automatic provider switching\n - 8ms P95 latency at 1k RPS performance\n - Observability integrations: Lunary, MLflow, Langfuse, Helicone, Promptlayer\n - Stable releases with 12-hour load tests\n- **Pricing**: Free and open-source to self-host. Enterprise edition available with SSO/JWT, audit logs, and support. [Source](https://www.litellm.ai/)\n- **Usage Limits**: Self-hosted with no limits. Enterprise plans available.\n- **Why It Fits**: Best open-source solution for teams wanting full control, transparency, and customization without vendor lock-in.\n\n### Portkey\n- **Description**: Portkey is an enterprise-grade AI gateway providing 1,600+ LLM connections with comprehensive governance, observability, guardrails, and prompt management. Has 10,000+ GitHub stars for its open-source gateway. [Source](https://portkey.ai/)\n- **Model Support**: 1,600+ LLMs and providers across different modalities including text, audio, and vision.\n- **Key Features**:\n - Dynamic model switching with configurable rules\n - Virtual keys and budget management per team\n - Role-based access control and audit logging\n - 20-40ms latency overhead on edge workers\n - 99.99% uptime with millions of requests per minute\n - ISO 27001, SOC 2 certified; GDPR and HIPAA compliant\n - Private cloud deployment, VPC hosting options\n- **Pricing**: Free tier (10,000 requests/month) for prototyping. Production tier starts at $49/month. Enterprise tier for complex compliance needs. [Source](https://portkey.ai/pricing)\n- **Usage Limits**: Free tier limited to 10K requests/month. Paid tiers scale based on needs.\n- **Why It Fits**: Ideal for enterprises requiring comprehensive governance, compliance, and sophisticated access controls across multiple teams.\n\n### Helicone AI Gateway\n- **Description**: Helicone is an open-source gateway and observability platform written in Rust for ultra-fast performance. Provides a single API to connect to 100+ LLMs with built-in analytics. Y Combinator W23 company. [Source](https://github.com/Helicone/helicone)\n- **Model Support**: 100+ LLMs across major providers including OpenAI, Anthropic, Google, and more.\n- **Key Features**:\n - Zero markup pricingβpay exactly what providers charge\n - 8ms P50 latency with Rust-based router\n - Health-aware routing with circuit breaking\n - Automatic provider failovers\n - Built-in observability: cost tracking, latency metrics, error monitoring\n - SOC 2 and GDPR compliant\n - VPC deployment via Docker or Kubernetes\n - Single binary deployment for any infrastructure\n- **Pricing**: Free tier with 10K requests/month. Zero markup on model costs. Paid tiers for teams and enterprises. Student/educator discounts available. [Source](https://www.helicone.ai/pricing)\n- **Usage Limits**: Generous free tier. Usage-based pricing for higher volumes.\n- **Why It Fits**: Best for teams prioritizing observability and performance with zero markup. The Rust-based architecture provides exceptional speed.\n\n### Cloudflare AI Gateway\n- **Description**: Cloudflare AI Gateway provides visibility and control over AI apps with analytics, logging, caching, rate limiting, and now unified billing. Available on all Cloudflare plans. [Source](https://developers.cloudflare.com/ai-gateway/)\n- **Model Support**: 20+ providers including OpenAI, Anthropic, Google AI Studio, Groq, Mistral, Cohere, Perplexity, xAI, DeepSeek, Cerebras, and Workers AI.\n- **Key Features**:\n - Unified billing (new in 2025)βsingle Cloudflare bill for all providers\n - Global edge caching reducing latency by up to 90%\n - Rate limiting with sliding/fixed window techniques\n - Token-based authentication\n - Custom costs for negotiated rates\n - Dynamic routing based on user segments, geography, or A/B testing\n - Comprehensive analytics for requests, tokens, costs, errors\n - Logpush for log export and compliance\n- **Pricing**: AI Gateway is free on all plans. Unified billing charges at provider list prices plus transaction fee when loading credits. Persistent logs have free allocation with overage charges. [Source](https://developers.cloudflare.com/ai-gateway/reference/pricing/)\n- **Usage Limits**: Spend limits available (daily, weekly, monthly) for budget control.\n- **Why It Fits**: Perfect for developers already using Cloudflare, offering seamless integration with global edge performance and unified billing.\n\n### Vercel AI Gateway\n- **Description**: Vercel AI Gateway provides a unified API to access hundreds of AI models with transparent pricing, automatic failover, and built-in observability. Generally available since August 21, 2025. [Source](https://vercel.com/ai-gateway)\n- **Model Support**: Hundreds of models from OpenAI, Anthropic, xAI, Google, and more including GPT-5, Claude Sonnet 4, and Grok.\n- **Key Features**:\n - Sub-20ms latency routing across providers\n - Zero markupβpay provider list prices only\n - $5 free credits per month for every team\n - Automatic failover for higher availability\n - No rate limits from Vercel\n - Budget setting and usage monitoring\n - Seamless integration with AI SDK 5 and OpenAI SDK\n - Load balancing and fallback management\n- **Pricing**: No markups on token prices. $5 free monthly credits. Pay-as-you-go with AI Gateway Credits. BYOK supported with 0% markup. [Source](https://vercel.com/docs/ai-gateway/pricing)\n- **Usage Limits**: No rate limits imposed by Vercel. Upstream provider limits apply.\n- **Why It Fits**: Optimal for Vercel users and teams using AI SDK, offering seamless integration with excellent free tier and no markup.\n\n### Kong AI Gateway\n- **Description**: Kong AI Gateway is an open-source (Apache 2.0) plugin for Kong's API Gateway, providing 60+ AI features including multi-LLM support, semantic security, and MCP traffic governance. [Source](https://github.com/Kong/kong)\n- **Model Support**: Universal LLM API routing across OpenAI, Anthropic, GCP Gemini, AWS Bedrock, Azure AI, Databricks, Mistral, Huggingface, and more.\n- **Key Features**:\n - MCP (Model Context Protocol) support with autogeneration from REST APIs\n - Data governance plugins for sensitive information\n - Prompt engineering and guardrails\n - Automated RAG pipelines to reduce hallucinations\n - Load balancing: consistent hashing, lowest-latency, round-robin, semantic matching\n - OpenTelemetry for tracing prompts and responses\n - AI observability with token usage, latency, and cost tracking\n - Plugins in Lua, Go, or JavaScript\n- **Pricing**: Free and open-source (Apache 2.0). Enterprise features available through Kong Inc. [Source](https://github.com/Kong/kong)\n- **Usage Limits**: Self-hosted with no limits. Enterprise support available.\n- **Why It Fits**: Best for organizations wanting open-source flexibility with enterprise plugin ecosystem and existing Kong API infrastructure.\n\n### Amazon Bedrock\n- **Description**: Amazon Bedrock is AWS's fully managed service for accessing foundation models through a unified API. Includes Bedrock AgentCore Gateway for tool and agent integration. [Source](https://aws.amazon.com/bedrock/)\n- **Model Support**: 11,000+ models through Azure AI Foundry including OpenAI, Anthropic Claude, Meta Llama, Mistral, Stability AI, Amazon Titan, and more.\n- **Key Features**:\n - AgentCore Gateway for MCP-compatible tool integration\n - Automatic prompt routing with ~30% cost savings\n - Provisioned throughput for predictable costs\n - Batch API with 50% discount on Global Standard pricing\n - Native AWS service integration\n - 1-click integration with Salesforce, Slack, Jira, Asana\n - Fine-tuning and model customization\n- **Pricing**: Pay-per-token with no upfront commitments. Claude 3.5 Sonnet: $3/$15 per million input/output tokens. Provisioned throughput for reserved capacity. $200 free tier credits for new AWS customers. [Source](https://aws.amazon.com/bedrock/pricing/)\n- **Usage Limits**: Based on usage tier and provisioned throughput.\n- **Why It Fits**: Ideal for enterprises with AWS infrastructure requiring native cloud integration, compliance, and managed services.\n\n### Together AI\n- **Description**: Together AI provides fast serverless inference for 200+ open-source models with pay-per-token pricing, powered by their proprietary Together Inference Stack. [Source](https://www.together.ai/)\n- **Model Support**: 200+ open-source models including Llama 4, Llama 3.3, DeepSeek, Qwen, Mistral, and more.\n- **Key Features**:\n - 11x lower cost than GPT-4o using Llama 3.3 70B\n - 9x lower cost than OpenAI o1 using DeepSeek-R1\n - 4x faster than vLLM with Together Inference Stack\n - ATLAS speculator system for optimized inference\n - Fine-tuning with pay-per-token (no minimums)\n - Dedicated endpoints with per-minute billing\n - Sub-100ms latency with automated optimization\n- **Pricing**: Pay-per-token pricing varying by model. Fine-tuning priced per tokens processed. Dedicated endpoints available. [Source](https://www.together.ai/pricing)\n- **Usage Limits**: No minimum usage. Pay-as-you-go.\n- **Why It Fits**: Best for teams focused on open-source models seeking the best price-performance ratio.\n\n### Groq\n- **Description**: Groq provides ultra-fast, low-cost inference powered by purpose-built LPU (Language Processing Unit) hardware. Supports 2+ million developers with $6.9 billion valuation. [Source](https://groq.com/)\n- **Model Support**: Leading GenAI models across text, audio, and vision including Llama, DeepSeek, Mistral, and more.\n- **Key Features**:\n - Up to 1,200 tokens/sec for lightweight models\n - Deterministic, high-speed inference\n - Batch API with 25% discount (24-hour processing)\n - Public, private, or co-cloud GroqCloud instances\n - STT, TTS, and image-to-text support\n - Linear, predictable pricing\n- **Pricing**: Free tier available. Developer tier for higher consumption. Enterprise plans for dedicated instances. Token pricing from $0.11/million input tokens for smaller models. [Source](https://groq.com/pricing)\n- **Usage Limits**: Tier-based rate limits. Free tier and Developer tier available.\n- **Why It Fits**: Best for latency-sensitive applications and real-time AI experiences requiring the fastest inference speeds.\n\n### Martian\n- **Description**: Martian builds intelligent model routers that dynamically select the best LLM for each query, optimizing for cost, quality, and latency. Used by 300+ companies including Amazon and Zapier. Backed by Accenture Ventures. [Source](https://withmartian.com/)\n- **Model Support**: Dozens of models from OpenAI, Anthropic, Mistral, Meta Llama, and more.\n- **Key Features**:\n - Dynamic model routing per query\n - Claims to outperform GPT-4 while reducing costs 20%-96%\n - Automatic failover during outages\n - Streaming support\n - Compliance feature for model approval policies (new in 2025)\n - Drop-in replacement with OpenAI API format\n - Mechanistic interpretability technology\n- **Pricing**: Usage-based with interactive cost calculator. $50 API credits available for hackathon participants. [Source](https://route.withmartian.com/products/model-router)\n- **Usage Limits**: Based on usage.\n- **Why It Fits**: Best for teams wanting intelligent cost optimization through dynamic routing without managing multiple integrations.\n\n### DeepInfra\n- **Description**: DeepInfra provides fast, cost-effective inference for 100+ models running on H100 and A100 GPUs with automatic scaling. [Source](https://deepinfra.com/)\n- **Model Support**: 100+ models including Llama 4, Claude by Anthropic, DeepSeek-V3, Qwen, Mistral, and NVIDIA Nemotron.\n- **Key Features**:\n - Per-token or per-execution-time pricing\n - H100/A100 GPU infrastructure\n - Automatic scaling (200 concurrent request limit)\n - Usage tier system with automatic upgrades\n - Spending limits to prevent surprises\n - OpenAI-compatible API\n- **Pricing**: Pay-per-token. Examples: DeepSeek-V3.2-Exp at $0.27/$0.40 per million I/O tokens; Llama 4 Scout at $0.08/$0.30; Meta-Llama-3.1-8B at $0.03/$0.05. [Source](https://deepinfra.com/pricing)\n- **Usage Limits**: 200 concurrent requests. Usage tier-based invoicing.\n- **Why It Fits**: Best for developers wanting simple, cost-effective access to open-source models with straightforward pricing.\n\n### Fireworks AI\n- **Description**: Fireworks AI provides one of the fastest model APIs using its proprietary FireAttention inference engine for text, image, and audio inference. Raised $254M Series C in October 2025 at $4B valuation. [Source](https://fireworks.ai/)\n- **Model Support**: Wide range of models for text, image, and audio generation.\n- **Key Features**:\n - ~250% higher throughput vs open-source engines\n - 50% faster speed than alternatives\n - Batch inference at 50% of serverless pricing\n - Free fine-tuned model deployment to serverless\n - HIPAA and SOC2 compliant\n - $1 free credits for new users\n- **Pricing**: Pay-per-token for serverless. Per GPU-time for on-demand deployments. Batch at 50% discount. [Source](https://fireworks.ai/pricing)\n- **Usage Limits**: Pay-as-you-go with free starter credits.\n- **Why It Fits**: Best for teams needing high-performance inference with strong compliance requirements.\n\n### Eden AI\n- **Description**: Eden AI unifies 100+ AI engines beyond just LLMsβincluding image generation, translation, speech-to-text, and moreβthrough a single API. [Source](https://www.edenai.co/)\n- **Model Support**: 100+ AI models across multiple modalities from various providers.\n- **Key Features**:\n - Unified API for LLMs plus image, audio, video, and NLP services\n - Cost management and performance monitoring\n - Zapier, Make, Bubble, Microsoft plugins\n - Bring Your Own Account (BYOA) support\n - Custom chatbot builder (RAG)\n - Workflow automation\n- **Pricing**: Start plan free ($10 credit, 60 calls/min). Personal at $29/month (300 calls/min). Advanced/Enterprise with custom pricing. Pay only for API calls made. [Source](https://www.edenai.co/pricing)\n- **Usage Limits**: Rate limits vary by plan. BYOA for vendor discounts.\n- **Why It Fits**: Best for developers building applications requiring multiple AI functionalities beyond just LLMs.\n\n### Novita AI\n- **Description**: Novita AI provides 200+ AI model APIs with developer-focused, startup-friendly rates. Offers LLMs, image, video, and audio models with fully managed deployment. [Source](https://novita.ai/)\n- **Model Support**: 200+ models including GPT OSS, Llama, DeepSeek, Qwen, and image/video/audio models.\n- **Key Features**:\n - GPT OSS models at low cost ($0.05-$0.10/million input tokens)\n - Batch inference at 50% discount\n - GPU instances for training and fine-tuning\n - Agent sandboxes with ~200ms startups\n - Per-second billing for CPU/RAM\n - No hidden fees\n- **Pricing**: Pay-as-you-go. GPT OSS 120B at $0.10/$0.50 per million I/O tokens. GPT OSS 20B at $0.05/$0.20. Up to 20% off during promotions. [Source](https://novita.ai/pricing)\n- **Usage Limits**: Based on usage tier.\n- **Why It Fits**: Best for startups and developers wanting low-cost access to a wide variety of models including GPT OSS.\n\n## Comparison Table\n\n| **Gateway** | **Open-Source** | **Models/Providers** | **Pricing** | **Free Tier** | **Key Strengths** | **Best For** |\n|-------------|-----------------|---------------------|-------------|---------------|-------------------|--------------|\n| **OpenRouter** | No | 500+ models, 60+ providers | No markup, 5.5% credit fee | No | Largest catalog, OpenAI compatible | Easy multi-model access |\n| **LiteLLM** | Yes (MIT) | 100+ providers | Free self-host, Enterprise available | Yes | 8ms latency, full control | Self-hosted, customization |\n| **Portkey** | Partial | 1,600+ LLMs | Free 10K/mo, $49+/mo | Yes (10K req) | Enterprise governance, SOC 2/ISO 27001 | Enterprise compliance |\n| **Helicone** | Yes | 100+ LLMs | Zero markup, free 10K/mo | Yes (10K req) | Rust performance, observability | Observability-focused teams |\n| **Cloudflare AI Gateway** | No | 20+ providers | Free base, unified billing | Yes | Edge caching, global performance | Cloudflare users |\n| **Vercel AI Gateway** | No | Hundreds of models | No markup, $5 free/mo | Yes ($5/mo) | Sub-20ms routing, AI SDK integration | Vercel/AI SDK users |\n| **Kong AI Gateway** | Yes (Apache 2.0) | 60+ AI features | Free, Enterprise available | Yes | MCP support, plugin ecosystem | Open-source with plugins |\n| **Amazon Bedrock** | No | 11,000+ via AI Foundry | Pay-per-token, $200 free | Yes ($200) | AWS integration, AgentCore | AWS enterprises |\n| **Together AI** | No | 200+ open-source | Pay-per-token | No | 11x cheaper than GPT-4o | Open-source inference |\n| * | |
| [2025-12-28T03:11:21.904Z] [INFO] *Groq** | No | Text/audio/vision | Free tier, per-token | Yes | 1,200 tokens/sec, LPU hardware | Ultra-fast inference |\n| **Martian** | No | Dozens of models | Usage-based | No | Dynamic routing, 20-96% savings | Cost optimization |\n| **DeepInfra** | No | 100+ models | Pay-per-token | No | H100/A100 GPUs, simple pricing | Cost-effective open models |\n| **Fireworks AI** | No | Text/image/audio | Pay-per-token, $1 free | Yes ($1) | Fastest API, SOC2/HIPAA | High-performance inference |\n| **Eden AI** | No | 100+ multi-modal | Free $10, $29+/mo | Yes ($10) | Beyond LLMs, workflow automation | Multi-modal applications |\n| **Novita AI** | No | 200+ models | Pay-as-you-go | Promotions | GPT OSS, startup-friendly | Startups, low-cost access |\n\n## Analysis and Recommendations\n\nBased on the evidence gathered in December 2025, the AI aggregator gateway market has matured significantly with clear leaders in different categories. The choice depends on your specific needs around open-source requirements, enterprise governance, performance, and budget.\n\n**Recommendations**:\n- **For easy multi-model access**: Choose **OpenRouter** for the largest model catalog with no markup on provider pricing.\n- **For self-hosted flexibility**: Choose **LiteLLM** as the leading open-source solution with full transparency and control.\n- **For enterprise governance**: Choose **Portkey** for comprehensive compliance, access controls, and SOC 2/ISO 27001 certification.\n- **For observability focus**: Choose **Helicone** for zero-markup pricing with built-in analytics and Rust-based performance.\n- **For Cloudflare users**: Choose **Cloudflare AI Gateway** for seamless integration with edge caching and unified billing.\n- **For Vercel/AI SDK users**: Choose **Vercel AI Gateway** for native integration with $5 monthly free credits.\n- **For open-source with plugins**: Choose **Kong AI Gateway** for Apache 2.0 license with extensive plugin ecosystem.\n- **For AWS enterprises**: Choose **Amazon Bedrock** for native AWS integration and managed services.\n- **For open-source model inference**: Choose **Together AI** for best price-performance on open models.\n- **For fastest inference**: Choose **Groq** for LPU-powered speeds up to 1,200 tokens/sec.\n- **For dynamic cost optimization**: Choose **Martian** for intelligent routing that reduces costs 20-96%.\n- **For multi-modal applications**: Choose **Eden AI** for unified access to LLMs, image, audio, and video services.\n\n## References\n\nFor further details, explore the official documentation:\n- [OpenRouter](https://openrouter.ai/) | [Pricing](https://openrouter.ai/pricing)\n- [LiteLLM](https://github.com/BerriAI/litellm) | [Documentation](https://www.litellm.ai/)\n- [Portkey](https://portkey.ai/) | [Pricing](https://portkey.ai/pricing)\n- [Helicone](https://github.com/Helicone/helicone) | [Pricing](https://www.helicone.ai/pricing)\n- [Cloudflare AI Gateway](https://developers.cloudflare.com/ai-gateway/) | [Pricing](https://developers.cloudflare.com/ai-gateway/reference/pricing/)\n- [Vercel AI Gateway](https://vercel.com/ai-gateway) | [Pricing](https://vercel.com/docs/ai-gateway/pricing)\n- [Kong AI Gateway](https://github.com/Kong/kong) | [Documentation](https://developer.konghq.com/ai-gateway/)\n- [Amazon Bedrock](https://aws.amazon.com/bedrock/) | [Pricing](https://aws.amazon.com/bedrock/pricing/)\n- [Together AI](https://www.together.ai/) | [Pricing](https://www.together.ai/pricing)\n- [Groq](https://groq.com/) | [Pricing](https://groq.com/pricing)\n- [Martian](https://withmartian.com/) | [Model Router](https://route.withmartian.com/products/model-router)\n- [DeepInfra](https://deepinfra.com/) | [Pricing](https://deepinfra.com/pricing)\n- [Fireworks AI](https://fireworks.ai/) | [Pricing](https://fireworks.ai/pricing)\n- [Eden AI](https://www.edenai.co/) | [Pricing](https://www.edenai.co/pricing)\n- [Novita AI](https://novita.ai/) | [Pricing](https://novita.ai/pricing)\n\n### Additional Sources\n- [OpenRouter Alternatives - Helicone](https://www.helicone.ai/blog/openrouter-alternatives)\n- [Top 5 LLM Gateways in 2025 - Helicone](https://www.helicone.ai/blog/top-llm-gateways-comparison-2025)\n- [How to Choose an AI Gateway in 2025 - Portkey](https://portkey.ai/blog/how-to-choose-an-ai-gateway-in-2025/)\n- [AI Gateway August 2025 Refresh - Cloudflare Blog](https://blog.cloudflare.com/ai-gateway-aug-2025-refresh/)\n- [Vercel AI Gateway GA Announcement](https://vercel.com/changelog/ai-gateway-is-now-generally-available)\n- [Kong AI Gateway Announcement](https://konghq.com/blog/product-releases/announcing-kong-ai-gateway)\n- [LiteLLM Guide - DataCamp](https://www.datacamp.com/tutorial/litellm)\n- [Gartner Hype Cycle for Generative AI 2025](https://www.gartner.com/)\n"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":1339,"cache_read_input_tokens":70368,"cache_creation":{"ephemeral_5m_input_tokens":1339,"ephemeral_1h_input_tokens":0},"output_tokens":8496,"service_tier":"standard"},"context_management":null},"parent_tool_use_id":null,"session_id":"37701ccf-99c0-4955-a30f-f61eb4145748","uuid":"20bf48d7-39c3-4d2b-bce9-a59ff51fd099"} | |
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| "content": "# AI Aggregator API Gateways: A Comprehensive Guide\n\nThis guide provides a comprehensive comparison of AI aggregator API gatewaysβservices that provide unified API access to multiple AI providers (OpenAI, Anthropic, Google, and more) through a single interface. These platforms eliminate the need to manage separate integrations, billing, and API keys for each AI provider. Below, we evaluate leading solutionsβOpenRouter, LiteLLM, Portkey, Helicone, Cloudflare AI Gateway, Vercel AI Gateway, Kong AI Gateway, Amazon Bedrock, Together AI, Groq, Martian, DeepInfra, Fireworks AI, Eden AI, and Novita AIβfocusing on their model access, pricing, and key features. The analysis prioritizes fair pricing and open-source options where possible, ensuring you have the information needed to make an informed decision.\n\n### Key Points (Updated December 2025)\n- **OpenRouter** is the leading model aggregator with 500+ models from 60+ providers, offering a unified API with no pricing markup and a 5.5% credit purchase fee.\n- **LiteLLM** is the most popular open-source AI gateway with 100+ model support, self-hostable with MIT license, and 8ms P95 latency at 1k RPS.\n- **Portkey** provides enterprise-grade governance with 1,600+ LLM connections, SOC 2/ISO 27001 compliance, and 10K+ GitHub stars.\n- **Helicone** offers zero-markup pricing with built-in observability, written in Rust for ultra-fast performance (8ms P50 latency).\n- **Cloudflare AI Gateway** features unified billing with 20+ provider support and global edge caching at no base cost.\n- **Vercel AI Gateway** became generally available in August 2025 with sub-20ms latency routing and $5 free monthly credits.\n- **Kong AI Gateway** is open-source (Apache 2.0) with 60+ AI features and MCP traffic governance.\n- **Amazon Bedrock** provides enterprise AWS integration with 11,000+ models through Azure AI Foundry and AgentCore Gateway.\n- **Together AI** offers 200+ open-source models with inference 11x lower cost than GPT-4o using Llama 3.3 70B.\n- **Groq** delivers ultra-fast inference (up to 1,200 tokens/sec) powered by purpose-built LPU hardware.\n\n### Why Choose an AI Aggregator API Gateway?\nManaging multiple AI provider accounts, billing systems, and API keys creates operational overhead and complexity. AI aggregator gateways solve this by offering:\n- **Single API**: One endpoint to access hundreds of AI models from different providers\n- **Unified Billing**: One consolidated invoice instead of tracking multiple vendor bills\n- **Automatic Failover**: If one provider fails, requests automatically route to another\n- **Model Flexibility**: Switch between models without changing your code\n- **Reduced Vendor Lock-in**: Abstract away providers so you can easily migrate\n- **Cost Optimization**: Compare pricing across providers and route to the most cost-effective option\n\nAccording to the 2025 Gartner Hype Cycle for Generative AI, AI Gateways are no longer optionalβthey've become a critical part of the AI stack.\n\n### Top Solutions at a Glance\n- **OpenRouter**: Best for easy multi-model access with no markup on provider pricing\n- **LiteLLM**: Best open-source self-hosted solution with maximum flexibility\n- **Portkey**: Ideal for enterprises requiring governance, compliance, and advanced access controls\n- **Helicone**: Best for observability-focused teams wanting zero markup and Rust-based performance\n- **Cloudflare AI Gateway**: Perfect for developers already in the Cloudflare ecosystem\n- **Vercel AI Gateway**: Optimal for Vercel users and AI SDK integration\n- **Kong AI Gateway**: Best for organizations wanting open-source with enterprise plugin ecosystem\n- **Amazon Bedrock**: Ideal for AWS-integrated enterprise deployments\n- **Together AI**: Best for open-source model inference at scale\n- **Groq**: Best for latency-sensitive applications requiring ultra-fast inference\n\n### How to Choose\n- **If you want simple multi-model access**: OpenRouter provides the easiest path with 500+ models\n- **If you prefer self-hosted**: LiteLLM or Kong AI Gateway offer full control with open-source licenses\n- **If you need enterprise governance**: Portkey provides comprehensive compliance and access controls\n- **If observability is critical**: Helicone offers built-in analytics with zero markup\n- **If you're in the AWS ecosystem**: Amazon Bedrock provides native integration\n- **If you need fastest inference**: Groq's LPU hardware delivers up to 1,200 tokens/sec\n- **If budget is a concern**: LiteLLM, Kong, and Helicone offer free open-source options\n\n---\n\n# Comprehensive Analysis of AI Aggregator API Gateways (Updated December 2025)\n\nThis comprehensive analysis evaluates AI aggregator API gateways, focusing on the most popular and capable platforms available as of December 2025. These services enable developers to access multiple AI providers through a unified API, simplifying integration, billing, and operations. The report assesses their model support, pricing, features, and suitability for different use cases. It emphasizes fair pricing and open-source options, providing a detailed guide for developers and enterprises.\n\n## Background and Context\nAI aggregator API gateways have become essential infrastructure for modern AI applications. As the AI landscape fragments with new models from OpenAI, Anthropic, Google, xAI, Meta, Mistral, and dozens of other providers, managing separate integrations becomes increasingly complex. These gateways provide a unified interface to route requests, debug problems, analyze performance, and optimize costs across all providers.\n\nThe market has matured significantly in 2025, with clear leaders emerging in different categories: pure aggregators like OpenRouter for easy access, open-source solutions like LiteLLM for flexibility, and enterprise platforms like Portkey for governance. AI Gateways now appear in the Gartner Hype Cycle for Generative AI, 2025, reflecting their critical role in production AI systems.\n\n### Model Availability Summary (December 2025)\n- **OpenAI**: GPT-5, GPT-5.1, GPT-5.2-Codex, o3, o3-mini, GPT-4o\n- **Anthropic**: Claude Opus 4.5, Opus 4, Sonnet 4.5, Sonnet 4, Haiku 4.5\n- **Google**: Gemini 3 Flash/Pro, Gemini 2.5 Pro/Flash\n- **xAI**: Grok 4, Grok 3\n- **Meta**: Llama 4, Llama 3.3 70B, Llama 3.1 405B\n- **Open Source**: DeepSeek-V3, Qwen3-Coder, Mistral Large, NVIDIA Nemotron\n\n## Methodology\nThe research involved extensive web searches to verify the features, supported models, pricing, and capabilities of each AI aggregator gateway. Official documentation, blogs, GitHub repositories, and community discussions were cross-referenced to ensure accuracy. GitHub star counts, pricing pages, and feature announcements were verified directly from source.\n\n## Detailed Analysis of AI Aggregator API Gateways\n\n### OpenRouter\n- **Description**: OpenRouter is the leading model aggregator providing a single, standardized API to access 500+ models from 60+ providers. It's fully OpenAI compatibleβdevelopers can switch by just changing the endpoint URL. [Source](https://openrouter.ai/)\n- **Model Support**: Access to 500+ models including GPT-5, Claude Opus 4.5, Gemini 3, Grok 4, Llama 4, DeepSeek-V3, and more. New models are added continuously.\n- **Key Features**:\n - OpenAI-compatible API format for drop-in replacement\n - Automatic fallback when routing is enabled (billed only for successful runs)\n - Privacy filters and content moderation options\n - Multimodal inputs including audio and PDF (August 2025)\n - Models API for free access to model metadata\n - RSS feed for new model updates\n- **Pricing**: No markup on provider pricingβyou pay exactly what providers charge. Credit purchase fees: 5.5% via card (minimum $0.80), 5% via crypto (no minimum). Enterprise pricing available with volume discounts, prepayment credits, and annual commits. [Source](https://openrouter.ai/pricing)\n- **Usage Limits**: Pay-as-you-go with automatic or manual top-up. Enterprise invoicing available.\n- **Why It Fits**: Best for developers wanting easy multi-model access without markup. The most comprehensive model catalog with straightforward pricing.\n\n### LiteLLM\n- **Description**: LiteLLM is an open-source (MIT license) proxy server that unifies access to 100+ LLMs through a single, OpenAI-compatible API. It provides unified model access, authentication, load balancing, fallbacks, and spend tracking. [Source](https://github.com/BerriAI/litellm)\n- **Model Support**: 100+ providers including OpenAI, Anthropic, Azure OpenAI, VertexAI, NVIDIA, HuggingFace, Bedrock, Ollama, OpenRouter, and more.\n- **Key Features**:\n - OpenAI-format API compatibility for all providers\n - Cost attribution and reporting with Postgres integration\n - Budgets and rate limits per user/team\n - Guardrails for content safety\n - Fallback logic for automatic provider switching\n - 8ms P95 latency at 1k RPS performance\n - Observability integrations: Lunary, MLflow, Langfuse, Helicone, Promptlayer\n - Stable releases with 12-hour load tests\n- **Pricing**: Free and open-source to self-host. Enterprise edition available with SSO/JWT, audit logs, and support. [Source](https://www.litellm.ai/)\n- **Usage Limits**: Self-hosted with no limits. Enterprise plans available.\n- **Why It Fits**: Best open-source solution for teams wanting full control, transparency, and customization without vendor lock-in.\n\n### Portkey\n- **Description**: Portkey is an enterprise-grade AI gateway providing 1,600+ LLM connections with comprehensive governance, observability, guardrails, and prompt management. Has 10,000+ GitHub stars for its open-source gateway. [Source](https://portkey.ai/)\n- **Model Support**: 1,600+ LLMs and providers across different modalities including text, audio, and vision.\n- **Key Features**:\n - Dynamic model switching with configurable rules\n - Virtual keys and budget management per team\n - Role-based access control and audit logging\n - 20-40ms latency overhead on edge workers\n - 99.99% uptime with millions of requests per minute\n - ISO 27001, SOC 2 certified; GDPR and HIPAA compliant\n - Private cloud deployment, VPC hosting options\n- **Pricing**: Free tier (10,000 requests/month) for prototyping. Production tier starts at $49/month. Enterprise tier for complex compliance needs. [Source](https://portkey.ai/pricing)\n- **Usage Limits**: Free tier limited to 10K requests/month. Paid tiers scale based on needs.\n- **Why It Fits**: Ideal for enterprises requiring comprehensive governance, compliance, and sophisticated access controls across multiple teams.\n\n### Helicone AI Gateway\n- **Description**: Helicone is an open-source gateway and observability platform written in Rust for ultra-fast performance. Provides a single API to connect to 100+ LLMs with built-in analytics. Y Combinator W23 company. [Source](https://github.com/Helicone/helicone)\n- **Model Support**: 100+ LLMs across major providers including OpenAI, Anthropic, Google, and more.\n- **Key Features**:\n - Zero markup pricingβpay exactly what providers charge\n - 8ms P50 latency with Rust-based router\n - Health-aware routing with circuit breaking\n - Automatic provider failovers\n - Built-in observability: cost tracking, latency metrics, error monitoring\n - SOC 2 and GDPR compliant\n - VPC deployment via Docker or Kubernetes\n - Single binary deployment for any infrastructure\n- **Pricing**: Free tier with 10K requests/month. Zero markup on model costs. Paid tiers for teams and enterprises. Student/educator discounts available. [Source](https://www.helicone.ai/pricing)\n- **Usage Limits**: Generous free tier. Usage-based pricing for higher volumes.\n- **Why It Fits**: Best for teams prioritizing observability and performance with zero markup. The Rust-based architecture provides exceptional speed.\n\n### Cloudflare AI Gateway\n- **Description**: Cloudflare AI Gateway provides visibility and control over AI apps with analytics, logging, caching, rate limiting, and now unified billing. Available on all Cloudflare plans. [Source](https://developers.cloudflare.com/ai-gateway/)\n- **Model Support**: 20+ providers including OpenAI, Anthropic, Google AI Studio, Groq, Mistral, Cohere, Perplexity, xAI, DeepSeek, Cerebras, and Workers AI.\n- **Key Features**:\n - Unified billing (new in 2025)βsingle Cloudflare bill for all providers\n - Global edge caching reducing latency by up to 90%\n - Rate limiting with sliding/fixed window techniques\n - Token-based authentication\n - Custom costs for negotiated rates\n - Dynamic routing based on user segments, geography, or A/B testing\n - Comprehensive analytics for requests, tokens, costs, errors\n - Logpush for log export and compliance\n- **Pricing**: AI Gateway is free on all plans. Unified billing charges at provider list prices plus transaction fee when loading credits. Persistent logs have free allocation with overage charges. [Source](https://developers.cloudflare.com/ai-gateway/reference/pricing/)\n- **Usage Limits**: Spend limits available (daily, weekly, monthly) for budget control.\n- **Why It Fits**: Perfect for developers already using Cloudflare, offering seamless integration with global edge performance and unified billing.\n\n### Vercel AI Gateway\n- **Description**: Vercel AI Gateway provides a unified API to access hundreds of AI models with transparent pricing, automatic failover, and built-in observability. Generally available since August 21, 2025. [Source](https://vercel.com/ai-gateway)\n- **Model Support**: Hundreds of models from OpenAI, Anthropic, xAI, Google, and more including GPT-5, Claude Sonnet 4, and Grok.\n- **Key Features**:\n - Sub-20ms latency routing across providers\n - Zero markupβpay provider list prices only\n - $5 free credits per month for every team\n - Automatic failover for higher availability\n - No rate limits from Vercel\n - Budget setting and usage monitoring\n - Seamless integration with AI SDK 5 and OpenAI SDK\n - Load balancing and fallback management\n- **Pricing**: No markups on token prices. $5 free monthly credits. Pay-as-you-go with AI Gateway Credits. BYOK supported with 0% markup. [Source](https://vercel.com/docs/ai-gateway/pricing)\n- **Usage Limits**: No rate limits imposed by Vercel. Upstream provider limits apply.\n- **Why It Fits**: Optimal for Vercel users and teams using AI SDK, offering seamless integration with excellent free tier and no markup.\n\n### Kong AI Gateway\n- **Description**: Kong AI Gateway is an open-source (Apache 2.0) plugin for Kong's API Gateway, providing 60+ AI features including multi-LLM support, semantic security, and MCP traffic governance. [Source](https://github.com/Kong/kong)\n- **Model Support**: Universal LLM API routing across OpenAI, Anthropic, GCP Gemini, AWS Bedrock, Azure AI, Databricks, Mistral, Huggingface, and more.\n- **Key Features**:\n - MCP (Model Context Protocol) support with autogeneration from REST APIs\n - Data governance plugins for sensitive information\n - Prompt engineering and guardrails\n - Automated RAG pipelines to reduce hallucinations\n - Load balancing: consistent hashing, lowest-latency, round-robin, semantic matching\n - OpenTelemetry for tracing prompts and responses\n - AI observability with token usage, latency, and cost tracking\n - Plugins in Lua, Go, or JavaScript\n- **Pricing**: Free and open-source (Apache 2.0). Enterprise features available through Kong Inc. [Source](https://github.com/Kong/kong)\n- **Usage Limits**: Self-hosted with no limits. Enterprise support available.\n- **Why It Fits**: Best for organizations wanting open-source flexibility with enterprise plugin ecosystem and existing Kong API infrastructure.\n\n### Amazon Bedrock\n- **Description**: Amazon Bedrock is AWS's fully managed service for accessing foundation models through a unified API. Includes Bedrock AgentCore Gateway for tool and agent integration. [Source](https://aws.amazon.com/bedrock/)\n- **Model Support**: 11,000+ models through Azure AI Foundry including OpenAI, Anthropic Claude, Meta Llama, Mistral, Stability AI, Amazon Titan, and more.\n- **Key Features**:\n - AgentCore Gateway for MCP-compatible tool integration\n - Automatic prompt routing with ~30% cost savings\n - Provisioned throughput for predictable costs\n - Batch API with 50% discount on Global Standard pricing\n - Native AWS service integration\n - 1-click integration with Salesforce, Slack, Jira, Asana\n - Fine-tuning and model customization\n- **Pricing**: Pay-per-token with no upfront commitments. Claude 3.5 Sonnet: $3/$15 per million input/output tokens. Provisioned throughput for reserved capacity. $200 free tier credits for new AWS customers. [Source](https://aws.amazon.com/bedrock/pricing/)\n- **Usage Limits**: Based on usage tier and provisioned throughput.\n- **Why It Fits**: Ideal for enterprises with AWS infrastructure requiring native cloud integration, compliance, and managed services.\n\n### Together AI\n- **Description**: Together AI provides fast serverless inference for 200+ open-source models with pay-per-token pricing, powered by their proprietary Together Inference Stack. [Source](https://www.together.ai/)\n- **Model Support**: 200+ open-source models including Llama 4, Llama 3.3, DeepSeek, Qwen, Mistral, and more.\n- **Key Features**:\n - 11x lower cost than GPT-4o using Llama 3.3 70B\n - 9x lower cost than OpenAI o1 using DeepSeek-R1\n - 4x faster than vLLM with Together Inference Stack\n - ATLAS speculator system for optimized inference\n - Fine-tuning with pay-per-token (no minimums)\n - Dedicated endpoints with per-minute billing\n - Sub-100ms latency with automated optimization\n- **Pricing**: Pay-per-token pricing varying by model. Fine-tuning priced per tokens processed. Dedicated endpoints available. [Source](https://www.together.ai/pricing)\n- **Usage Limits**: No minimum usage. Pay-as-you-go.\n- **Why It Fits**: Best for teams focused on open-source models seeking the best price-performance ratio.\n\n### Groq\n- **Description**: Groq provides ultra-fast, low-cost inference powered by purpose-built LPU (Language Processing Unit) hardware. Supports 2+ million developers with $6.9 billion valuation. [Source](https://groq.com/)\n- **Model Support**: Leading GenAI models across text, audio, and vision including Llama, DeepSeek, Mistral, and more.\n- **Key Features**:\n - Up to 1,200 tokens/sec for lightweight models\n - Deterministic, high-speed inference\n - Batch API with 25% discount (24-hour processing)\n - Public, private, or co-cloud GroqCloud instances\n - STT, TTS, and image-to-text support\n - Linear, predictable pricing\n- **Pricing**: Free tier available. Developer tier for higher consumption. Enterprise plans for dedicated instances. Token pricing from $0.11/million input tokens for smaller models. [Source](https://groq.com/pricing)\n- **Usage Limits**: Tier-based rate limits. Free tier and Developer tier available.\n- **Why It Fits**: Best for latency-sensitive applications and real-time AI experiences requiring the fastest inference speeds.\n\n### Martian\n- **Description**: Martian builds intelligent model routers that dynamically select the best LLM for each query, optimizing for cost, quality, and latency. Used by 300+ companies including Amazon and Zapier. Backed by Accenture Ventures. [Source](https://withmartian.com/)\n- **Model Support**: Dozens of models from OpenAI, Anthropic, Mistral, Meta Llama, and more.\n- **Key Features**:\n - Dynamic model routing per query\n - Claims to outperform GPT-4 while reducing costs 20%-96%\n - Automatic failover during outages\n - Streaming support\n - Compliance feature for model approval policies (new in 2025)\n - Drop-in replacement with OpenAI API format\n - Mechanistic interpretability technology\n- **Pricing**: Usage-based with interactive cost calculator. $50 API credits available for hackathon participants. [Source](https://route.withmartian.com/products/model-router)\n- **Usage Limits**: Based on usage.\n- **Why It Fits**: Best for teams wanting intelligent cost optimization through dynamic routing without managing multiple integrations.\n\n### DeepInfra\n- **Description**: DeepInfra provides fast, cost-effective inference for 100+ models running on H100 and A100 GPUs with automatic scaling. [Source](https://deepinfra.com/)\n- **Model Support**: 100+ models including Llama 4, Claude by Anthropic, DeepSeek-V3, Qwen, Mistral, and NVIDIA Nemotron.\n- **Key Features**:\n - Per-token or per-execution-time pricing\n - H100/A100 GPU infrastructure\n - Automatic scaling (200 concurrent request limit)\n - Usage tier system with automatic upgrades\n - Spending limits to prevent surprises\n - OpenAI-compatible API\n- **Pricing**: Pay-per-token. Examples: DeepSeek-V3.2-Exp at $0.27/$0.40 per million I/O tokens; Llama 4 Scout at $0.08/$0.30; Meta-Llama-3.1-8B at $0.03/$0.05. [Source](https://deepinfra.com/pricing)\n- **Usage Limits**: 200 concurrent requests. Usage tier-based invoicing.\n- **Why It Fits**: Best for developers wanting simple, cost-effective access to open-source models with straightforward pricing.\n\n### Fireworks AI\n- **Description**: Fireworks AI provides one of the fastest model APIs using its proprietary FireAttention inference engine for text, image, and audio inference. Raised $254M Series C in October 2025 at $4B valuation. [Source](https://fireworks.ai/)\n- **Model Support**: Wide range of models for text, image, and audio generation.\n- **Key Features**:\n - ~250% higher throughput vs open-source engines\n - 50% faster speed than alternatives\n - Batch inference at 50% of serverless pricing\n - Free fine-tuned model deployment to serverless\n - HIPAA and SOC2 compliant\n - $1 free credits for new users\n- **Pricing**: Pay-per-token for serverless. Per GPU-time for on-demand deployments. Batch at 50% discount. [Source](https://fireworks.ai/pricing)\n- **Usage Limits**: Pay-as-you-go with free starter credits.\n- **Why It Fits**: Best for teams needing high-performance inference with strong compliance requirements.\n\n### Eden AI\n- **Description**: Eden AI unifies 100+ AI engines beyond just LLMsβincluding image generation, translation, speech-to-text, and moreβthrough a single API. [Source](https://www.edenai.co/)\n- **Model Support**: 100+ AI models across multiple modalities from various providers.\n- **Key Features**:\n - Unified API for LLMs plus image, audio, video, and NLP services\n - Cost management and performance monitoring\n - Zapier, Make, Bubble, Microsoft plugins\n - Bring Your Own Account (BYOA) support\n - Custom chatbot builder (RAG)\n - Workflow automation\n- **Pricing**: Start plan free ($10 credit, 60 calls/min). Personal at $29/month (300 calls/min). Advanced/Enterprise with custom pricing. Pay only for API calls made. [Source](https://www.edenai.co/pricing)\n- **Usage Limits**: Rate limits vary by plan. BYOA for vendor discounts.\n- **Why It Fits**: Best for developers building applications requiring multiple AI functionalities beyond just LLMs.\n\n### Novita AI\n- **Description**: Novita AI provides 200+ AI model APIs with developer-focused, startup-friendly rates. Offers LLMs, image, video, and audio models with fully managed deployment. [Source](https://novita.ai/)\n- **Model Support**: 200+ models including GPT OSS, Llama, DeepSeek, Qwen, and image/video/audio models.\n- **Key Features**:\n - GPT OSS models at low cost ($0.05-$0.10/million input tokens)\n - Batch inference at 50% discount\n - GPU instances for training and fine-tuning\n - Agent sandboxes with ~200ms startups\n - Per-second billing for CPU/RAM\n - No hidden fees\n- **Pricing**: Pay-as-you-go. GPT OSS 120B at $0.10/$0.50 per million I/O tokens. GPT OSS 20B at $0.05/$0.20. Up to 20% off during promotions. [Source](https://novita.ai/pricing)\n- **Usage Limits**: Based on usage tier.\n- **Why It Fits**: Best for startups and developers wanting low-cost access to a wide variety of models including GPT OSS.\n\n## Comparison Table\n\n| **Gateway** | **Open-Source** | **Models/Providers** | **Pricing** | **Free Tier** | **Key Strengths** | **Best For** |\n|-------------|-----------------|---------------------|-------------|---------------|-------------------|--------------|\n| **OpenRouter** | No | 500+ models, 60+ providers | No markup, 5.5% credit fee | No | Largest catalog, OpenAI compatible | Easy multi-model access |\n| **LiteLLM** | Yes (MIT) | 100+ providers | Free self-host, Enterprise available | Yes | 8ms latency, full control | Self-hosted, customization |\n| **Portkey** | Partial | 1,600+ LLMs | Free 10K/mo, $49+/mo | Yes (10K req) | Enterprise governance, SOC 2/ISO 27001 | Enterprise compliance |\n| **Helicone** | Yes | 100+ LLMs | Zero markup, free 10K/mo | Yes (10K req) | Rust performance, observability | Observability-focused teams |\n| **Cloudflare AI Gateway** | No | 20+ providers | Free base, unified billing | Yes | Edge caching, global performance | Cloudflare users |\n| **Vercel AI Gateway** | No | Hundreds of models | No markup, $5 free/mo | Yes ($5/mo) | Sub-20ms routing, AI SDK integration | Vercel/AI SDK users |\n| **Kong AI Gateway** | Yes (Apache 2.0) | 60+ AI features | Free, Enterprise available | Yes | MCP support, plugin ecosystem | Open-source with plugins |\n| **Amazon Bedrock** | No | 11,000+ via AI Foundry | Pay-per-token, $200 free | Yes ($200) | AWS integration, AgentCore | AWS enterprises |\n| **Together AI** | No | 200+ open-source | Pay-per-token | No | 11x cheaper than GPT-4o | Open-source inference |\n| **Groq** | No | Text/audio/vision | Free tier, per-token | Yes | 1,200 tokens/sec, LPU hardware | Ultra-fast inference |\n| **Martian** | No | Dozens of models | Usage-based | No | Dynamic routing, 20-96% savings | Cost optimization |\n| **DeepInfra** | No | 100+ models | Pay-per-token | No | H100/A100 GPUs, simple pricing | Cost-effective open models |\n| **Fireworks AI** | No | Text/image/audio | Pay-per-token, $1 free | Yes ($1) | Fastest API, SOC2/HIPAA | High-performance inference |\n| **Eden AI** | No | 100+ multi-modal | Free $10, $29+/mo | Yes ($10) | Beyond LLMs, workflow automation | Multi-modal applications |\n| **Novita AI** | No | 200+ models | Pay-as-you-go | Promotions | GPT OSS, startup-friendly | Startups, low-cost access |\n\n## Analysis and Recommendations\n\nBased on the evidence gathered in December 2025, the AI aggregator gateway market has matured significantly with clear leaders in different categories. The choice depends on your specific needs around open-source requirements, enterprise governance, performance, and budget.\n\n**Recommendations**:\n- **For easy multi-model access**: Choose **OpenRouter** for the largest model catalog with no markup on provider pricing.\n- **For self-hosted flexibility**: Choose **LiteLLM** as the leading open-source solution with full transparency and control.\n- **For enterprise governance**: Choose **Portkey** for comprehensive compliance, access controls, and SOC 2/ISO 27001 certification.\n- **For observability focus**: Choose **Helicone** for zero-markup pricing with built-in analytics and Rust-based performance.\n- **For Cloudflare users**: Choose **Cloudflare AI Gateway** for seamless integration with edge caching and unified billing.\n- **For Vercel/AI SDK users**: Choose **Vercel AI Gateway** for native integration with $5 monthly free credits.\n- **For open-source with plugins**: Choose **Kong AI Gateway** for Apache 2.0 license with extensive plugin ecosystem.\n- **For AWS enterprises**: Choose **Amazon Bedrock** for native AWS integration and managed services.\n- **For open-source model inference**: Choose **Together AI** for best price-performance on open models.\n- **For fastest inference**: Choose **Groq** for LPU-powered speeds up to 1,200 tokens/sec.\n- **For dynamic cost optimization**: Choose **Martian** for intelligent routing that reduces costs 20-96%.\n- **For multi-modal applications**: Choose **Eden AI** for unified access to LLMs, image, audio, and video services.\n\n## References\n\nFor further details, explore the official documentation:\n- [OpenRouter](https://openrouter.ai/) | [Pricing](https://openrouter.ai/pricing)\n- [LiteLLM](https://github.com/BerriAI/litellm) | [Documentation](https://www.litellm.ai/)\n- [Portkey](https://portkey.ai/) | [Pricing](https://portkey.ai/pricing)\n- [Helicone](https://github.com/Helicone/helicone) | [Pricing](https://www.helicone.ai/pricing)\n- [Cloudflare AI Gateway](https://developers.cloudflare.com/ai-gateway/) | [Pricing](https://developers.cloudflare.com/ai-gateway/reference/pricing/)\n- [Vercel AI Gateway](https://vercel.com/ai-gateway) | [Pricing](https://vercel.com/docs/ai-gateway/pricing)\n- [Kong AI Gateway](https://github.com/Kong/kong) | [Documentation](https://developer.konghq.com/ai-gateway/)\n- [Amazon Bedrock](https://aws.amazon.com/bedrock/) | [Pricing](https://aws.amazon.com/bedrock/pricing/)\n- [Together AI](https://www.together.ai/) | [Pricing](https://www.together.ai/pricing)\n- [Groq](https://groq.com/) | [Pricing](https://groq.com/pricing)\n- [Martian](https://withmartian.com/) | [Model Router](https://route.withmartian.com/products/model-router)\n- [DeepInfra](https://deepinfra.com/) | [Pricing](https://deepinfra.com/pricing)\n- [Fireworks AI](https://fireworks.ai/) | [Pricing](https://fireworks.ai/pricing)\n- [Eden AI](https://www.edenai.co/) | [Pricing](https://www.edenai.co/pricing)\n- [Novita AI](https://novita.ai/) | [Pricing](https://novita.ai/pricing)\n\n### Additional Sources\n- [OpenRouter Alternatives - Helicone](https://www.helicone.ai/blog/openrouter-alternatives)\n- [Top 5 LLM Gateways in 2025 - Helicone](https://www.helicone.ai/blog/top-llm-gateways-comparison-2025)\n- [How to Choose an AI Gateway in 2025 - Portkey](https://portkey.ai/blog/how-to-choose-an-ai-gateway-in-2025/)\n- [AI Gateway August 2025 Refresh - Cloudflare Blog](https://blog.cloudflare.com/ai-gateway-aug-2025-refresh/)\n- [Vercel AI Gateway GA Announcement](https://vercel.com/changelog/ai-gateway-is-now-generally-available)\n- [Kong AI Gateway Announcement](https://konghq.com/blog/product-releases/announcing-kong-ai-gateway)\n- [LiteLLM Guide - DataCamp](https://www.datacamp.com/tutorial/litellm)\n- [Gartner Hype Cycle for Generative AI 2025](https://www.gartner.com/)\n", | |
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| [2025-12-28T03:13:44.369Z] [INFO] {"type":"assistant","message":{"model":"claude-opus-4-5-20251101","id":"msg_01PbxepVLkMFJEokajz9jEvn","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01AKv1BVMKDoYMAiQks7FuMW","name":"Write","input":{"file_path":"/tmp/gh-issue-solver-1766891018916/ai-aggregator-api-gateways-features.md","content":"# AI Aggregator API Gateways: Features Comparison (December 2025)\n\nThis document provides a detailed feature-by-feature comparison of AI aggregator API gateways, helping you choose the right solution based on specific capabilities. The comparison covers model access, routing features, observability, security, pricing models, and specialized capabilities.\n\n---\n\n## 1. Model Access & Provider Support\n\n| **Gateway** | **Total Models** | **OpenAI** | **Anthropic** | **Google** | **xAI** | **Meta Llama** | **Open-Source** | **Self-Hosted/Local** |\n|-------------|------------------|------------|---------------|------------|---------|----------------|-----------------|----------------------|\n| **OpenRouter** | 500+ | β GPT-5, o3 | β Claude Opus 4.5 | β Gemini 3 | β Grok 4 | β Llama 4 | β DeepSeek, Mistral | β |\n| **LiteLLM** | 100+ | β | β | β | β | β | β | β Ollama |\n| **Portkey** | 1,600+ | β | β | β | β | β | β | β |\n| **Helicone** | 100+ | β | β | β | β | β | β | β |\n| **Cloudflare AI Gateway** | 20+ providers | β | β | β | β DeepSeek | β | β Workers AI | β |\n| **Vercel AI Gateway** | Hundreds | β GPT-5 | β Sonnet 4 | β | β Grok | β | β | β |\n| **Kong AI Gateway** | 60+ features | β | β | β GCP Gemini | β | β | β | β |\n| **Amazon Bedrock** | 11,000+ | β via Foundry | β Claude | β | β | β | β | β |\n| **Together AI** | 200+ | β | β | β | β | β Llama 4 | β Full focus | β |\n| **Groq** | Multiple | β | β | β | β | β | β | β |\n| **Martian** | Dozens | β | β | β | β | β | β Mistral | β |\n| **DeepInfra** | 100+ | β | β Claude | β | β | β Llama 4 | β | β |\n| **Fireworks AI** | Multiple | β | β | β | β | β | β | β |\n| **Eden AI** | 100+ | β | β | β | β | β | β | β |\n| **Novita AI** | 200+ | β GPT OSS | β | β | β | β | β | β |\n\n**Key Insights**:\n- **OpenRouter** offers the largest model catalog with 500+ models from 60+ providers\n- **Portkey** supports the most LLM connections at 1,600+\n- **Amazon Bedrock** provides access to 11,000+ models through AI Foundry\n- **LiteLLM**, **Kong**, and **Helicone** support self-hosted/local models via Ollama\n\n---\n\n## 2. API Compatibility & Integration\n\n| **Gateway** | **OpenAI-Compatible API** | **SDK Support** | **BYOK (Bring Your Own Key)** | **MCP Support** | **Webhook/Streaming** |\n|-------------|---------------------------|-----------------|-------------------------------|-----------------|----------------------|\n| **OpenRouter** | β Drop-in replacement | REST API | β | β | β Streaming |\n| **LiteLLM** | β Full compatibility | Python SDK | β | β | β |\n| **Portkey** | β | Python, Node.js | β Virtual keys | β | β |\n| **Helicone** | β | Multiple SDKs | β | β | β |\n| **Cloudflare AI Gateway** | β Unified API | REST, Workers | β Store in vault | β | β |\n| **Vercel AI Gateway** | β | AI SDK 5, OpenAI SDK | β 0% markup | β | β |\n| **Kong AI Gateway** | β Universal LLM API | Lua, Go, JS plugins | β | β MCP governance | β |\n| **Amazon Bedrock** | Partial | AWS SDKs | N/A (AWS native) | β AgentCore | β |\n| **Together AI** | β | REST API | N/A | β | β |\n| **Groq** | β | REST API | N/A | β | β |\n| **Martian** | β Drop-in replacement | REST API | β | β | β |\n| **DeepInfra** | β | REST API | N/A | β | β |\n| **Fireworks AI** | β | REST API | N/A | β | β |\n| **Eden AI** | β | REST API, Plugins | β BYOA | β | β |\n| **Novita AI** | β | REST API | N/A | β | β |\n\n**Key Insights**:\n- All gateways support OpenAI-compatible API format for easy migration\n- **Kong AI Gateway** leads in MCP (Model Context Protocol) support with full governance\n- **Vercel AI Gateway** offers seamless AI SDK 5 integration with 0% BYOK markup\n- **Portkey** provides virtual keys for secure credential management\n\n---\n\n## 3. Routing & Load Balancing\n\n| **Gateway** | **Automatic Failover** | **Load Balancing** | **Dynamic Routing** | **A/B Testing** | **Semantic Routing** | **Cost-Based Routing** |\n|-------------|------------------------|-------------------|---------------------|-----------------|---------------------|----------------------|\n| **OpenRouter** | β | Basic | β | β | β | β |\n| **LiteLLM** | β Fallback logic | β | β | β | β | β |\n| **Portkey** | β | β Configurable | β Rules-based | β | β | β |\n| **Helicone** | β Circuit breaking | β Health-aware | β | β | β | β |\n| **Cloudflare AI Gateway** | β | β | β Visual interface | β | β | β |\n| **Vercel AI Gateway** | β | β | β | β | β | β |\n| **Kong AI Gateway** | β Retries | β Multiple algorithms | β | β | β Semantic matching | β |\n| **Amazon Bedrock** | β | β | β Prompt routing | β | β | β ~30% savings |\n| **Together AI** | β | β | β | β | β | β |\n| **Groq** | β | β | β | β | β | β |\n| **Martian** | β Automatic | β | β Per-query | β | β | β 20-96% savings |\n| **DeepInfra** | β | β Auto-scaling | β | β | β | β |\n| **Fireworks AI** | β | β | β | β | β | β |\n| **Eden AI** | β | β | β | β | β | β |\n| **Novita AI** | β | β | β | β | β | β |\n\n**Key Insights**:\n- **Kong AI Gateway** offers the most advanced routing with semantic matching and multiple algorithms\n- **Martian** specializes in cost-based dynamic routing with claimed 20-96% savings\n- **Amazon Bedrock** provides automatic prompt routing for ~30% cost savings\n- **Cloudflare AI Gateway** enables A/B testing through a visual interface\n\n---\n\n## 4. Observability & Analytics\n\n| **Gateway** | **Cost Tracking** | **Latency Metrics** | **Token Usage** | **Error Monitoring** | **Custom Dashboards** | **Log Export** |\n|-------------|-------------------|--------------------|-----------------|--------------------|----------------------|----------------|\n| **OpenRouter** | β Per-model | Basic | β | Basic | β | β |\n| **LiteLLM** | β Full attribution | β | β | β | β Postgres | β Multiple integrations |\n| **Portkey** | β | β | β | β | β | β Audit logs |\n| **Helicone** | β Real-time | β 8ms P50 | β | β | β | β |\n| **Cloudflare AI Gateway** | β Custom costs | β | β | β | β | β Logpush |\n| **Vercel AI Gateway** | β | β | β | β | β | β |\n| **Kong AI Gateway** | β LLM cost control | β | β | β | β Metrics export | β OpenTelemetry |\n| **Amazon Bedrock** | β | β | β | β | β CloudWatch | β |\n| **Together AI** | β | β | β | Basic | β | β |\n| **Groq** | β | β | β | Basic | β | β |\n| **Martian** | β Cost calculator | Basic | β | Basic | β | β |\n| **DeepInfra** | β Spending limits | β | β | Basic | β | β |\n| **Fireworks AI** | β | β | β | Basic | β | β |\n| **Eden AI** | β | β | β | β | β | β |\n| **Novita AI** | β | β | β | Basic | β | β |\n\n**Key Insights**:\n- **Helicone** is built specifically for observability with Rust-based performance\n- **LiteLLM** integrates with multiple observability platforms (Lunary, MLflow, Langfuse, etc.)\n- **Kong AI Gateway** supports OpenTelemetry for distributed tracing\n- **Cloudflare AI Gateway** allows custom cost configuration for negotiated rates\n\n---\n\n## 5. Security & Compliance\n\n| **Gateway** | **SOC 2** | **GDPR** | **HIPAA** | **ISO 27001** | **Data Retention Control** | **VPC/On-Prem** |\n|-------------|-----------|----------|-----------|---------------|---------------------------|-----------------|\n| **OpenRouter** | β | β Privacy filters | β | β | β | β |\n| **LiteLLM** | Enterprise | β | Enterprise | β | β Self-hosted | β Full control |\n| **Portkey** | β Type 2 | β | β | β | β ZDR available | β Private cloud |\n| **Helicone** | β | β | β | β | β | β VPC |\n| **Cloudflare AI Gateway** | β | β | β | β | β Logpush | β |\n| **Vercel AI Gateway** | β | β | β | β | β | β |\n| **Kong AI Gateway** | Enterprise | β | Enterprise | Enterprise | β Self-hosted | β Full control |\n| **Amazon Bedrock** | β | β | β | β | β | β AWS VPC |\n| **Together AI** | β | β | β | β | β | β |\n| **Groq** | β | β | β | β | β | β Private cloud |\n| **Martian** | β | β | β | β | β | β |\n| **DeepInfra** | β | β | β | β | β | β |\n| **Fireworks AI** | β | β | β | β | β | β |\n| **Eden AI** | β | β | β | β | β | Enterprise |\n| **Novita AI** | β | β | β | β | β | β |\n\n**Key Insights**:\n- **Portkey** offers the most comprehensive compliance: SOC 2 Type 2, GDPR, HIPAA, and ISO 27001\n- **Amazon Bedrock** provides full AWS-grade security and compliance\n- **LiteLLM** and **Kong** offer complete control through self-hosting\n- **Fireworks AI** is one of few inference providers with SOC2 and HIPAA compliance\n\n---\n\n## 6. Caching & Performance Optimization\n\n| **Gateway** | **Response Caching** | **Semantic Caching** | **Edge Deployment** | **Latency Overhead** | **Rate Limiting** |\n|-------------|---------------------|---------------------|--------------------|--------------------|-------------------|\n| **OpenRouter** | β | β | β | Variable | Provider-based |\n| **LiteLLM** | β | β | β | 8ms P95 | β Configurable |\n| **Portkey** | β | β | β Edge workers | 20-40ms | β |\n| **Helicone** | β | β | β | 8ms P50 | β |\n| **Cloudflare AI Gateway** | β 90% latency reduction | β | β Global edge | Minimal | β Flexible |\n| **Vercel AI Gateway** | β | β | β Edge | Sub-20ms | β (no limits) |\n| **Kong AI Gateway** | β | β Semantic | β | Minimal | β |\n| **Amazon Bedrock** | β | β | β AWS regions | Variable | β |\n| **Together AI** | β | β | β | Sub-100ms | API-based |\n| **Groq** | β | β | β | Ultra-low | Tier-based |\n| **Martian** | β | β | β | Variable | API-based |\n| **DeepInfra** | β | β | β | Low | 200 concurrent |\n| **Fireworks AI** | β | β | β | Ultra-low | API-based |\n| **Eden AI** | β Personal+ | β | β | Variable | Plan-based |\n| **Novita AI** | β | β | β | Low | API-based |\n\n**Key Insights**:\n- **Cloudflare AI Gateway** offers the best caching with up to 90% latency reduction\n- **Kong AI Gateway** uniquely offers semantic caching\n- **Groq** and **Fireworks AI** focus on ultra-low latency inference\n- **Vercel AI Gateway** imposes no rate limits from their side\n\n---\n\n## 7. Pricing Models & Free Tiers\n\n| **Gateway** | **Pricing Model** | **Markup** | **Free Tier** | **Entry Price** | **Enterprise** |\n|-------------|-------------------|------------|---------------|-----------------|----------------|\n| **OpenRouter** | Pay-as-you-go | 0% + 5.5% credit fee | β | Credit purchase | β Volume discounts |\n| **LiteLLM** | Self-host or Enterprise | 0% (self-host) | β Self-host | Free | β SSO, audit logs |\n| **Portkey** | Usage-based | Varies | β 10K req/mo | $49/month | β Custom |\n| **Helicone** | Usage-based | 0% | β 10K req/mo | Team pricing | β Custom |\n| **Cloudflare AI Gateway** | Usage-based | 0% + transaction fee | β Free base | Per-log charges | β |\n| **Vercel AI Gateway** | Pay-as-you-go | 0% | β $5/month | Credit-based | β |\n| **Kong AI Gateway** | Self-host or Enterprise | 0% (self-host) | β Self-host | Free | β Kong Inc. |\n| **Amazon Bedrock** | Pay-per-token | 0% | β $200 credits | Token-based | β Provisioned |\n| **Together AI** | Pay-per-token | N/A | β | Token-based | β Dedicated |\n| **Groq** | Pay-per-token | N/A | β Free tier | $0.11/M input | β Dedicated |\n| **Martian** | Usage-based | Savings model | β | Contact | β |\n| **DeepInfra** | Pay-per-token | N/A | β | $0.03/M input | β |\n| **Fireworks AI** | Pay-per-token | N/A | β $1 credits | Token-based | β |\n| **Eden AI** | Pay-per-call | 0% | β $10 credits | $29/month | β Custom |\n| **Novita AI** | Pay-as-you-go | N/A | Promotions | $0.05/M input | β |\n\n**Key Insights**:\n- **OpenRouter**, **Helicone**, **Cloudflare**, and **Vercel** charge zero markup on model pricing\n- **LiteLLM** and **Kong** are completely free when self-hosted\n- **Vercel AI Gateway** provides the most generous recurring free tier at $5/month\n- **Amazon Bedrock** offers $200 in free credits for new AWS customers\n\n---\n\n## 8. Specialized Capabilities\n\n| **Gateway** | **Guardrails** | **Prompt Templates** | **RAG Integration** | **Fine-Tuning** | **Multi-Modal** | **Batch Processing** |\n|-------------|----------------|---------------------|--------------------|-----------------|-----------------|--------------------|\n| **OpenRouter** | β Privacy filters | β | β | β | β Audio, PDF | β |\n| **LiteLLM** | β | β | β | β | β | β |\n| **Portkey** | β 50+ guardrails | β | β | β | β | β |\n| **Helicone** | β | β | β | β | β | β |\n| **Cloudflare AI Gateway** | β | β | β | β | β | β |\n| **Vercel AI Gateway** | β | β | β | β | β | β |\n| **Kong AI Gateway** | β Content safety | β | β Automated | β | β | β |\n| **Amazon Bedrock** | β | β | β | β | β | β 50% discount |\n| **Together AI** | β | β | β | β Pay-per-token | β | β |\n| **Groq** | β | β | β | β | β STT, TTS | β 25% discount |\n| **Martian** | β Compliance | β | β | β | β | β |\n| **DeepInfra** | β | β | β | β | β | β |\n| **Fireworks AI** | β | β | β | β Free deploy | β Image, audio | β 50% discount |\n| **Eden AI** | β | β Workflows | β Chatbot builder | β | β Full stack | β |\n| **Novita AI** | β | β | β | β | β Image, video | β 50% discount |\n\n**Key Insights**:\n- **Portkey** offers 50+ AI guardrails for enterprise content safety\n- **Kong AI Gateway** provides automated RAG pipelines to reduce hallucinations\n- **Amazon Bedrock** and **Fireworks AI** offer batch processing with significant discounts\n- **Eden AI** goes beyond LLMs with full multi-modal AI stack (image, audio, video, NLP)\n\n---\n\n## 9. Open-Source & Licensing\n\n| **Gateway** | **Open Source** | **License** | **GitHub Stars** | **Self-Host** | **Commercial Use** |\n|-------------|-----------------|-------------|------------------|---------------|-------------------|\n| **OpenRouter** | β | Proprietary | N/A | β | β |\n| **LiteLLM** | β | MIT | High | β | β |\n| **Portkey** | Partial | Apache 2.0 (gateway) | 10K+ | β | β |\n| **Helic | |
| [2025-12-28T03:13:44.379Z] [INFO] one** | β | Open source | Growing | β | β |\n| **Cloudflare AI Gateway** | β | Proprietary | N/A | β | β |\n| **Vercel AI Gateway** | β | Proprietary | N/A | β | β |\n| **Kong AI Gateway** | β | Apache 2.0 | 40K+ (Kong) | β | β |\n| **Amazon Bedrock** | β | AWS | N/A | β | β |\n| **Together AI** | β | Proprietary | N/A | β | β |\n| **Groq** | β | Proprietary | N/A | β | β |\n| **Martian** | β | Proprietary | N/A | β | β |\n| **DeepInfra** | β | Proprietary | N/A | β | β |\n| **Fireworks AI** | β | Proprietary | N/A | β | β |\n| **Eden AI** | β | Proprietary | N/A | Enterprise | β |\n| **Novita AI** | β | Proprietary | N/A | β | β |\n\n**Key Insights**:\n- **LiteLLM** (MIT) and **Kong** (Apache 2.0) offer the most permissive open-source licenses\n- **Portkey**'s gateway is open-source (10K+ stars) while the full platform is commercial\n- **Kong** has the largest open-source community with 40K+ GitHub stars\n\n---\n\n## 10. Quick Feature Summary by Use Case\n\n### For Startups & Individual Developers\n| Priority | Recommended Gateway | Why |\n|----------|-------------------|-----|\n| **Lowest cost** | LiteLLM (self-hosted) | Free, full control |\n| **Easiest setup** | OpenRouter | Largest catalog, simple API |\n| **Best free tier** | Vercel AI Gateway | $5 monthly credits, no markup |\n| **Fastest inference** | Groq | Free tier, ultra-low latency |\n\n### For Enterprise & Teams\n| Priority | Recommended Gateway | Why |\n|----------|-------------------|-----|\n| **Governance & compliance** | Portkey | SOC 2, ISO 27001, HIPAA |\n| **AWS integration** | Amazon Bedrock | Native AWS, 11K+ models |\n| **Self-hosted control** | LiteLLM or Kong | MIT/Apache 2.0 licenses |\n| **Observability focus** | Helicone | Zero markup, Rust performance |\n\n### For Specific Workloads\n| Workload | Recommended Gateway | Why |\n|----------|-------------------|-----|\n| **Multi-modal apps** | Eden AI | Full AI stack beyond LLMs |\n| **Open-source models** | Together AI | 200+ models, best price-performance |\n| **Real-time/low latency** | Groq | LPU hardware, 1,200 tokens/sec |\n| **Cost optimization** | Martian | Dynamic routing, 20-96% savings |\n| **Batch processing** | Amazon Bedrock or Fireworks | 50% discount on batch |\n\n---\n\n## 11. Integration Ecosystem\n\n| **Gateway** | **IDE Plugins** | **CI/CD** | **Zapier/Make** | **Slack** | **Jira** | **GitHub** |\n|-------------|-----------------|-----------|-----------------|-----------|----------|------------|\n| **OpenRouter** | β | β | β | β | β | β |\n| **LiteLLM** | β | β | β | β | β | β |\n| **Portkey** | β | β | β | β | β | β |\n| **Helicone** | β | β | β | β | β | β |\n| **Cloudflare AI Gateway** | β | β Workers | β | β | β | β |\n| **Vercel AI Gateway** | β | β | β | β | β | β |\n| **Kong AI Gateway** | β | β | β | β | β | β |\n| **Amazon Bedrock** | β AWS Toolkit | β | β | β 1-click | β 1-click | β |\n| **Together AI** | β | β | β | β | β | β |\n| **Groq** | β | β | β | β | β | β |\n| **Martian** | β | β | β | β | β | β |\n| **DeepInfra** | β | β | β | β | β | β |\n| **Fireworks AI** | β | β | β | β | β | β |\n| **Eden AI** | β | β | β Zapier, Make | β | β | β |\n| **Novita AI** | β | β | β | β | β | β |\n\n**Key Insights**:\n- **Amazon Bedrock** offers the richest integration ecosystem with 1-click connections\n- **Eden AI** provides no-code integrations via Zapier and Make\n- Most gateways focus on API-first approach with CI/CD compatibility\n\n---\n\n## 12. Decision Matrix\n\nUse this matrix to quickly identify the best gateway for your needs:\n\n| **If you need...** | **Choose...** |\n|--------------------|---------------|\n| Largest model selection | OpenRouter (500+ models) |\n| Complete open-source control | LiteLLM (MIT license) |\n| Enterprise governance | Portkey (SOC 2/ISO 27001) |\n| Best observability | Helicone (built-in, zero markup) |\n| Cloudflare integration | Cloudflare AI Gateway |\n| Vercel/AI SDK users | Vercel AI Gateway |\n| Plugin extensibility | Kong AI Gateway (Apache 2.0) |\n| AWS ecosystem | Amazon Bedrock |\n| Open-source model focus | Together AI (200+ models) |\n| Fastest inference | Groq (LPU, 1,200 tok/sec) |\n| Dynamic cost optimization | Martian (20-96% savings) |\n| Simple open-source access | DeepInfra (100+ models) |\n| High-performance inference | Fireworks AI (SOC2/HIPAA) |\n| Multi-modal beyond LLMs | Eden AI (image/audio/video) |\n| Budget-friendly startup | Novita AI (GPT OSS) |\n\n---\n\n## References\n\n- [OpenRouter Documentation](https://openrouter.ai/)\n- [LiteLLM GitHub](https://github.com/BerriAI/litellm)\n- [Portkey AI Gateway](https://portkey.ai/features/ai-gateway)\n- [Helicone AI Gateway Guide](https://www.helicone.ai/blog/how-to-gateway)\n- [Cloudflare AI Gateway Docs](https://developers.cloudflare.com/ai-gateway/)\n- [Vercel AI Gateway Docs](https://vercel.com/docs/ai-gateway)\n- [Kong AI Gateway](https://developer.konghq.com/ai-gateway/)\n- [Amazon Bedrock](https://aws.amazon.com/bedrock/)\n- [Together AI Products](https://www.together.ai/products)\n- [Groq Cloud](https://groq.com/groqcloud)\n- [Martian Model Router](https://route.withmartian.com/products/model-router)\n- [DeepInfra Pricing](https://deepinfra.com/pricing)\n- [Fireworks AI](https://fireworks.ai/)\n- [Eden AI Platform](https://www.edenai.co/)\n- [Novita AI](https://novita.ai/)\n"}}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":333,"cache_read_input_tokens":80247,"cache_creation":{"ephemeral_5m_input_tokens":333,"ephemeral_1h_input_tokens":0},"output_tokens":8761,"service_tier":"standard"},"context_management":null},"parent_tool_use_id":null,"session_id":"37701ccf-99c0-4955-a30f-f61eb4145748","uuid":"fc1dd015-41f2-422f-a145-f4c08253be41"} | |
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| "content": "# AI Aggregator API Gateways: Features Comparison (December 2025)\n\nThis document provides a detailed feature-by-feature comparison of AI aggregator API gateways, helping you choose the right solution based on specific capabilities. The comparison covers model access, routing features, observability, security, pricing models, and specialized capabilities.\n\n---\n\n## 1. Model Access & Provider Support\n\n| **Gateway** | **Total Models** | **OpenAI** | **Anthropic** | **Google** | **xAI** | **Meta Llama** | **Open-Source** | **Self-Hosted/Local** |\n|-------------|------------------|------------|---------------|------------|---------|----------------|-----------------|----------------------|\n| **OpenRouter** | 500+ | β GPT-5, o3 | β Claude Opus 4.5 | β Gemini 3 | β Grok 4 | β Llama 4 | β DeepSeek, Mistral | β |\n| **LiteLLM** | 100+ | β | β | β | β | β | β | β Ollama |\n| **Portkey** | 1,600+ | β | β | β | β | β | β | β |\n| **Helicone** | 100+ | β | β | β | β | β | β | β |\n| **Cloudflare AI Gateway** | 20+ providers | β | β | β | β DeepSeek | β | β Workers AI | β |\n| **Vercel AI Gateway** | Hundreds | β GPT-5 | β Sonnet 4 | β | β Grok | β | β | β |\n| **Kong AI Gateway** | 60+ features | β | β | β GCP Gemini | β | β | β | β |\n| **Amazon Bedrock** | 11,000+ | β via Foundry | β Claude | β | β | β | β | β |\n| **Together AI** | 200+ | β | β | β | β | β Llama 4 | β Full focus | β |\n| **Groq** | Multiple | β | β | β | β | β | β | β |\n| **Martian** | Dozens | β | β | β | β | β | β Mistral | β |\n| **DeepInfra** | 100+ | β | β Claude | β | β | β Llama 4 | β | β |\n| **Fireworks AI** | Multiple | β | β | β | β | β | β | β |\n| **Eden AI** | 100+ | β | β | β | β | β | β | β |\n| **Novita AI** | 200+ | β GPT OSS | β | β | β | β | β | β |\n\n**Key Insights**:\n- **OpenRouter** offers the largest model catalog with 500+ models from 60+ providers\n- **Portkey** supports the most LLM connections at 1,600+\n- **Amazon Bedrock** provides access to 11,000+ models through AI Foundry\n- **LiteLLM**, **Kong**, and **Helicone** support self-hosted/local models via Ollama\n\n---\n\n## 2. API Compatibility & Integration\n\n| **Gateway** | **OpenAI-Compatible API** | **SDK Support** | **BYOK (Bring Your Own Key)** | **MCP Support** | **Webhook/Streaming** |\n|-------------|---------------------------|-----------------|-------------------------------|-----------------|----------------------|\n| **OpenRouter** | β Drop-in replacement | REST API | β | β | β Streaming |\n| **LiteLLM** | β Full compatibility | Python SDK | β | β | β |\n| **Portkey** | β | Python, Node.js | β Virtual keys | β | β |\n| **Helicone** | β | Multiple SDKs | β | β | β |\n| **Cloudflare AI Gateway** | β Unified API | REST, Workers | β Store in vault | β | β |\n| **Vercel AI Gateway** | β | AI SDK 5, OpenAI SDK | β 0% markup | β | β |\n| **Kong AI Gateway** | β Universal LLM API | Lua, Go, JS plugins | β | β MCP governance | β |\n| **Amazon Bedrock** | Partial | AWS SDKs | N/A (AWS native) | β AgentCore | β |\n| **Together AI** | β | REST API | N/A | β | β |\n| **Groq** | β | REST API | N/A | β | β |\n| **Martian** | β Drop-in replacement | REST API | β | β | β |\n| **DeepInfra** | β | REST API | N/A | β | β |\n| **Fireworks AI** | β | REST API | N/A | β | β |\n| **Eden AI** | β | REST API, Plugins | β BYOA | β | β |\n| **Novita AI** | β | REST API | N/A | β | β |\n\n**Key Insights**:\n- All gateways support OpenAI-compatible API format for easy migration\n- **Kong AI Gateway** leads in MCP (Model Context Protocol) support with full governance\n- **Vercel AI Gateway** offers seamless AI SDK 5 integration with 0% BYOK markup\n- **Portkey** provides virtual keys for secure credential management\n\n---\n\n## 3. Routing & Load Balancing\n\n| **Gateway** | **Automatic Failover** | **Load Balancing** | **Dynamic Routing** | **A/B Testing** | **Semantic Routing** | **Cost-Based Routing** |\n|-------------|------------------------|-------------------|---------------------|-----------------|---------------------|----------------------|\n| **OpenRouter** | β | Basic | β | β | β | β |\n| **LiteLLM** | β Fallback logic | β | β | β | β | β |\n| **Portkey** | β | β Configurable | β Rules-based | β | β | β |\n| **Helicone** | β Circuit breaking | β Health-aware | β | β | β | β |\n| **Cloudflare AI Gateway** | β | β | β Visual interface | β | β | β |\n| **Vercel AI Gateway** | β | β | β | β | β | β |\n| **Kong AI Gateway** | β Retries | β Multiple algorithms | β | β | β Semantic matching | β |\n| **Amazon Bedrock** | β | β | β Prompt routing | β | β | β ~30% savings |\n| **Together AI** | β | β | β | β | β | β |\n| **Groq** | β | β | β | β | β | β |\n| **Martian** | β Automatic | β | β Per-query | β | β | β 20-96% savings |\n| **DeepInfra** | β | β Auto-scaling | β | β | β | β |\n| **Fireworks AI** | β | β | β | β | β | β |\n| **Eden AI** | β | β | β | β | β | β |\n| **Novita AI** | β | β | β | β | β | β |\n\n**Key Insights**:\n- **Kong AI Gateway** offers the most advanced routing with semantic matching and multiple algorithms\n- **Martian** specializes in cost-based dynamic routing with claimed 20-96% savings\n- **Amazon Bedrock** provides automatic prompt routing for ~30% cost savings\n- **Cloudflare AI Gateway** enables A/B testing through a visual interface\n\n---\n\n## 4. Observability & Analytics\n\n| **Gateway** | **Cost Tracking** | **Latency Metrics** | **Token Usage** | **Error Monitoring** | **Custom Dashboards** | **Log Export** |\n|-------------|-------------------|--------------------|-----------------|--------------------|----------------------|----------------|\n| **OpenRouter** | β Per-model | Basic | β | Basic | β | β |\n| **LiteLLM** | β Full attribution | β | β | β | β Postgres | β Multiple integrations |\n| **Portkey** | β | β | β | β | β | β Audit logs |\n| **Helicone** | β Real-time | β 8ms P50 | β | β | β | β |\n| **Cloudflare AI Gateway** | β Custom costs | β | β | β | β | β Logpush |\n| **Vercel AI Gateway** | β | β | β | β | β | β |\n| **Kong AI Gateway** | β LLM cost control | β | β | β | β Metrics export | β OpenTelemetry |\n| **Amazon Bedrock** | β | β | β | β | β CloudWatch | β |\n| **Together AI** | β | β | β | Basic | β | β |\n| **Groq** | β | β | β | Basic | β | β |\n| **Martian** | β Cost calculator | Basic | β | Basic | β | β |\n| **DeepInfra** | β Spending limits | β | β | Basic | β | β |\n| **Fireworks AI** | β | β | β | Basic | β | β |\n| **Eden AI** | β | β | β | β | β | β |\n| **Novita AI** | β | β | β | Basic | β | β |\n\n**Key Insights**:\n- **Helicone** is built specifically for observability with Rust-based performance\n- **LiteLLM** integrates with multiple observability platforms (Lunary, MLflow, Langfuse, etc.)\n- **Kong AI Gateway** supports OpenTelemetry for distributed tracing\n- **Cloudflare AI Gateway** allows custom cost configuration for negotiated rates\n\n---\n\n## 5. Security & Compliance\n\n| **Gateway** | **SOC 2** | **GDPR** | **HIPAA** | **ISO 27001** | **Data Retention Control** | **VPC/On-Prem** |\n|-------------|-----------|----------|-----------|---------------|---------------------------|-----------------|\n| **OpenRouter** | β | β Privacy filters | β | β | β | β |\n| **LiteLLM** | Enterprise | β | Enterprise | β | β Self-hosted | β Full control |\n| **Portkey** | β Type 2 | β | β | β | β ZDR available | β Private cloud |\n| **Helicone** | β | β | β | β | β | β VPC |\n| **Cloudflare AI Gateway** | β | β | β | β | β Logpush | β |\n| **Vercel AI Gateway** | β | β | β | β | β | β |\n| **Kong AI Gateway** | Enterprise | β | Enterprise | Enterprise | β Self-hosted | β Full control |\n| **Amazon Bedrock** | β | β | β | β | β | β AWS VPC |\n| **Together AI** | β | β | β | β | β | β |\n| **Groq** | β | β | β | β | β | β Private cloud |\n| **Martian** | β | β | β | β | β | β |\n| **DeepInfra** | β | β | β | β | β | β |\n| **Fireworks AI** | β | β | β | β | β | β |\n| **Eden AI** | β | β | β | β | β | Enterprise |\n| **Novita AI** | β | β | β | β | β | β |\n\n**Key Insights**:\n- **Portkey** offers the most comprehensive compliance: SOC 2 Type 2, GDPR, HIPAA, and ISO 27001\n- **Amazon Bedrock** provides full AWS-grade security and compliance\n- **LiteLLM** and **Kong** offer complete control through self-hosting\n- **Fireworks AI** is one of few inference providers with SOC2 and HIPAA compliance\n\n---\n\n## 6. Caching & Performance Optimization\n\n| **Gateway** | **Response Caching** | **Semantic Caching** | **Edge Deployment** | **Latency Overhead** | **Rate Limiting** |\n|-------------|---------------------|---------------------|--------------------|--------------------|-------------------|\n| **OpenRouter** | β | β | β | Variable | Provider-based |\n| **LiteLLM** | β | β | β | 8ms P95 | β Configurable |\n| **Portkey** | β | β | β Edge workers | 20-40ms | β |\n| **Helicone** | β | β | β | 8ms P50 | β |\n| **Cloudflare AI Gateway** | β 90% latency reduction | β | β Global edge | Minimal | β Flexible |\n| **Vercel AI Gateway** | β | β | β Edge | Sub-20ms | β (no limits) |\n| **Kong AI Gateway** | β | β Semantic | β | Minimal | β |\n| **Amazon Bedrock** | β | β | β AWS regions | Variable | β |\n| **Together AI** | β | β | β | Sub-100ms | API-based |\n| **Groq** | β | β | β | Ultra-low | Tier-based |\n| **Martian** | β | β | β | Variable | API-based |\n| **DeepInfra** | β | β | β | Low | 200 concurrent |\n| **Fireworks AI** | β | β | β | Ultra-low | API-based |\n| **Eden AI** | β Personal+ | β | β | Variable | Plan-based |\n| **Novita AI** | β | β | β | Low | API-based |\n\n**Key Insights**:\n- **Cloudflare AI Gateway** offers the best caching with up to 90% latency reduction\n- **Kong AI Gateway** uniquely offers semantic caching\n- **Groq** and **Fireworks AI** focus on ultra-low latency inference\n- **Vercel AI Gateway** imposes no rate limits from their side\n\n---\n\n## 7. Pricing Models & Free Tiers\n\n| **Gateway** | **Pricing Model** | **Markup** | **Free Tier** | **Entry Price** | **Enterprise** |\n|-------------|-------------------|------------|---------------|-----------------|----------------|\n| **OpenRouter** | Pay-as-you-go | 0% + 5.5% credit fee | β | Credit purchase | β Volume discounts |\n| **LiteLLM** | Self-host or Enterprise | 0% (self-host) | β Self-host | Free | β SSO, audit logs |\n| **Portkey** | Usage-based | Varies | β 10K req/mo | $49/month | β Custom |\n| **Helicone** | Usage-based | 0% | β 10K req/mo | Team pricing | β Custom |\n| **Cloudflare AI Gateway** | Usage-based | 0% + transaction fee | β Free base | Per-log charges | β |\n| **Vercel AI Gateway** | Pay-as-you-go | 0% | β $5/month | Credit-based | β |\n| **Kong AI Gateway** | Self-host or Enterprise | 0% (self-host) | β Self-host | Free | β Kong Inc. |\n| **Amazon Bedrock** | Pay-per-token | 0% | β $200 credits | Token-based | β Provisioned |\n| **Together AI** | Pay-per-token | N/A | β | Token-based | β Dedicated |\n| **Groq** | Pay-per-token | N/A | β Free tier | $0.11/M input | β Dedicated |\n| **Martian** | Usage-based | Savings model | β | Contact | β |\n| **DeepInfra** | Pay-per-token | N/A | β | $0.03/M input | β |\n| **Fireworks AI** | Pay-per-token | N/A | β $1 credits | Token-based | β |\n| **Eden AI** | Pay-per-call | 0% | β $10 credits | $29/month | β Custom |\n| **Novita AI** | Pay-as-you-go | N/A | Promotions | $0.05/M input | β |\n\n**Key Insights**:\n- **OpenRouter**, **Helicone**, **Cloudflare**, and **Vercel** charge zero markup on model pricing\n- **LiteLLM** and **Kong** are completely free when self-hosted\n- **Vercel AI Gateway** provides the most generous recurring free tier at $5/month\n- **Amazon Bedrock** offers $200 in free credits for new AWS customers\n\n---\n\n## 8. Specialized Capabilities\n\n| **Gateway** | **Guardrails** | **Prompt Templates** | **RAG Integration** | **Fine-Tuning** | **Multi-Modal** | **Batch Processing** |\n|-------------|----------------|---------------------|--------------------|-----------------|-----------------|--------------------|\n| **OpenRouter** | β Privacy filters | β | β | β | β Audio, PDF | β |\n| **LiteLLM** | β | β | β | β | β | β |\n| **Portkey** | β 50+ guardrails | β | β | β | β | β |\n| **Helicone** | β | β | β | β | β | β |\n| **Cloudflare AI Gateway** | β | β | β | β | β | β |\n| **Vercel AI Gateway** | β | β | β | β | β | β |\n| **Kong AI Gateway** | β Content safety | β | β Automated | β | β | β |\n| **Amazon Bedrock** | β | β | β | β | β | β 50% discount |\n| **Together AI** | β | β | β | β Pay-per-token | β | β |\n| **Groq** | β | β | β | β | β STT, TTS | β 25% discount |\n| **Martian** | β Compliance | β | β | β | β | β |\n| **DeepInfra** | β | β | β | β | β | β |\n| **Fireworks AI** | β | β | β | β Free deploy | β Image, audio | β 50% discount |\n| **Eden AI** | β | β Workflows | β Chatbot builder | β | β Full stack | β |\n| **Novita AI** | β | β | β | β | β Image, video | β 50% discount |\n\n**Key Insights**:\n- **Portkey** offers 50+ AI guardrails for enterprise content safety\n- **Kong AI Gateway** provides automated RAG pipelines to reduce hallucinations\n- **Amazon Bedrock** and **Fireworks AI** offer batch processing with significant discounts\n- **Eden AI** goes beyond LLMs with full multi-modal AI stack (image, audio, video, NLP)\n\n---\n\n## 9. Open-Source & Licensing\n\n| **Gateway** | **Open Source** | **License** | **GitHub Stars** | **Self-Host** | **Commercial Use** |\n|-------------|-----------------|-------------|------------------|---------------|-------------------|\n| **OpenRouter** | β | Proprietary | N/A | β | β |\n| **LiteLLM** | β | MIT | High | β | β |\n| **Portkey** | Partial | Apache 2.0 (gateway) | 10K+ | β | β |\n| **Helicone** | β | Open source | Growing | β | β |\n| **Cloudflare AI Gateway** | β | Proprietary | N/A | β | β |\n| **Vercel AI Gateway** | β | Proprietary | N/A | β | β |\n| **Kong AI Gateway** | β | Apache 2.0 | 40K+ (Kong) | β | β |\n| **Amazon Bedrock** | β | AWS | N/A | β | β |\n| **Together AI** | β | Proprietary | N/A | β | β |\n| **Groq** | β | Proprietary | N/A | β | β |\n| **Martian** | β | Proprietary | N/A | β | β |\n| **DeepInfra** | β | Proprietary | N/A | β | β |\n| **Fireworks AI** | β | Proprietary | N/A | β | β |\n| **Eden AI** | β | Proprietary | N/A | Enterprise | β |\n| **Novita AI** | β | Proprietary | N/A | β | β |\n\n**Key Insights**:\n- **LiteLLM** (MIT) and **Kong** (Apache 2.0) offer the most permissive open-source licenses\n- **Portkey**'s gateway is open-source (10K+ stars) while the full platform is commercial\n- **Kong** has the largest open-source community with 40K+ GitHub stars\n\n---\n\n## 10. Quick Feature Summary by Use Case\n\n### For Startups & Individual Developers\n| Priority | Recommended Gateway | Why |\n|----------|-------------------|-----|\n| **Lowest cost** | LiteLLM (self-hosted) | Free, full control |\n| **Easiest setup** | OpenRouter | Largest catalog, simple API |\n| **Best free tier** | Vercel AI Gateway | $5 monthly credits, no markup |\n| **Fastest inference** | Groq | Free tier, ultra-low latency |\n\n### For Enterprise & Teams\n| Priority | Recommended Gateway | Why |\n|----------|-------------------|-----|\n| **Governance & compliance** | Portkey | SOC 2, ISO 27001, HIPAA |\n| **AWS integration** | Amazon Bedrock | Native AWS, 11K+ models |\n| **Self-hosted control** | LiteLLM or Kong | MIT/Apache 2.0 licenses |\n| **Observability focus** | Helicone | Zero markup, Rust performance |\n\n### For Specific Workloads\n| Workload | Recommended Gateway | Why |\n|----------|-------------------|-----|\n| **Multi-modal apps** | Eden AI | Full AI stack beyond LLMs |\n| **Open-source models** | Together AI | 200+ models, best price-performance |\n| **Real-time/low latency** | Groq | LPU hardware, 1,200 tokens/sec |\n| **Cost optimization** | Martian | Dynamic routing, 20-96% savings |\n| **Batch processing** | Amazon Bedrock or Fireworks | 50% discount on batch |\n\n---\n\n## 11. Integration Ecosystem\n\n| **Gateway** | **IDE Plugins** | **CI/CD** | **Zapier/Make** | **Slack** | **Jira** | **GitHub** |\n|-------------|-----------------|-----------|-----------------|-----------|----------|------------|\n| **OpenRouter** | β | β | β | β | β | β |\n| **LiteLLM** | β | β | β | β | β | β |\n| **Portkey** | β | β | β | β | β | β |\n| **Helicone** | β | β | β | β | β | β |\n| **Cloudflare AI Gateway** | β | β Workers | β | β | β | β |\n| **Vercel AI Gateway** | β | β | β | β | β | β |\n| **Kong AI Gateway** | β | β | β | β | β | β |\n| **Amazon Bedrock** | β AWS Toolkit | β | β | β 1-click | β 1-click | β |\n| **Together AI** | β | β | β | β | β | β |\n| **Groq** | β | β | β | β | β | β |\n| **Martian** | β | β | β | β | β | β |\n| **DeepInfra** | β | β | β | β | β | β |\n| **Fireworks AI** | β | β | β | β | β | β |\n| **Eden AI** | β | β | β Zapier, Make | β | β | β |\n| **Novita AI** | β | β | β | β | β | β |\n\n**Key Insights**:\n- **Amazon Bedrock** offers the richest integration ecosystem with 1-click connections\n- **Eden AI** provides no-code integrations via Zapier and Make\n- Most gateways focus on API-first approach with CI/CD compatibility\n\n---\n\n## 12. Decision Matrix\n\nUse this matrix to quickly identify the best gateway for your needs:\n\n| **If you need...** | **Choose...** |\n|--------------------|---------------|\n| Largest model selection | OpenRouter (500+ models) |\n| Complete open-source control | LiteLLM (MIT license) |\n| Enterprise governance | Portkey (SOC 2/ISO 27001) |\n| Best observability | Helicone (built-in, zero markup) |\n| Cloudflare integration | Cloudflare AI Gateway |\n| Vercel/AI SDK users | Vercel AI Gateway |\n| Plugin extensibility | Kong AI Gateway (Apache 2.0) |\n| AWS ecosystem | Amazon Bedrock |\n| Open-source model focus | Together AI (200+ models) |\n| Fastest inference | Groq (LPU, 1,200 tok/sec) |\n| Dynamic cost optimization | Martian (20-96% savings) |\n| Simple open-source access | DeepInfra (100+ models) |\n| High-performance inference | Fireworks AI (SOC2/HIPAA) |\n| Multi-modal beyond LLMs | Eden AI (image/audio/video) |\n| Budget-friendly startup | Novita AI (GPT OSS) |\n\n---\n\n## References\n\n- [OpenRouter Documentation](https://openrouter.ai/)\n- [LiteLLM GitHub](https://github.com/BerriAI/litellm)\n- [Portkey AI Gateway](https://portkey.ai/features/ai-gateway)\n- [Helicone AI Gateway Guide](https://www.helicone.ai/blog/how-to-gateway)\n- [Cloudflare AI Gateway Docs](https://developers.cloudflare.com/ai-gateway/)\n- [Vercel AI Gateway Docs](https://vercel.com/docs/ai-gateway)\n- [Kong AI Gateway](https://developer.konghq.com/ai-gateway/)\n- [Amazon Bedrock](https://aws.amazon.com/bedrock/)\n- [Together AI Products](https://www.together.ai/products)\n- [Groq Cloud](https://groq.com/groqcloud)\n- [Martian Model Router](https://route.withmartian.com/products/model-router)\n- [DeepInfra Pricing](https://deepinfra.com/pricing)\n- [Fireworks AI](https://fireworks.ai/)\n- [Eden AI Platform](https://www.edenai.co/)\n- [Novita AI](https://novita.ai/)\n", | |
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| [2025-12-28T03:15:10.076Z] [INFO] { | |
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| "content": "title:\tAdd AI aggregator API gateways research documentation\nstate:\tOPEN\nauthor:\tkonard\nlabels:\t\nassignees:\tkonard\nreviewers:\t\nprojects:\t\nmilestone:\t\nnumber:\t10\nurl:\thttps://github.com/link-assistant/market-research/pull/10\nadditions:\t721\ndeletions:\t0\nauto-merge:\tdisabled\n--\n## Summary\n\nThis PR addresses issue #9 by creating comprehensive research documentation on AI aggregator API gatewaysβservices that provide unified API access to multiple AI providers (OpenAI, Anthropic, Google, and more) through a single interface.\n\n### New Files Created\n\n1. **ai-aggregator-api-gateways.md** - Main research document covering 15 AI aggregator gateway services:\n - OpenRouter (500+ models, 60+ providers)\n - LiteLLM (open-source, MIT license)\n - Portkey (enterprise governance, SOC 2/ISO 27001)\n - Helicone (zero markup, Rust-based performance)\n - Cloudflare AI Gateway (unified billing, edge caching)\n - Vercel AI Gateway (AI SDK integration, $5 free/mo)\n - Kong AI Gateway (open-source, MCP support)\n - Amazon Bedrock (AWS integration, 11K+ models)\n - Together AI (200+ open-source models)\n - Groq (LPU hardware, 1,200 tokens/sec)\n - Martian (dynamic routing, 20-96% savings)\n - DeepInfra (100+ models, H100/A100 GPUs)\n - Fireworks AI (high-performance, SOC2/HIPAA)\n - Eden AI (multi-modal beyond LLMs)\n - Novita AI (GPT OSS, startup-friendly)\n\n2. **ai-aggregator-api-gateways-features.md** - Detailed feature comparison across 12 categories:\n - Model Access & Provider Support\n - API Compatibility & Integration\n - Routing & Load Balancing\n - Observability & Analytics\n - Security & Compliance\n - Caching & Performance Optimization\n - Pricing Models & Free Tiers\n - Specialized Capabilities\n - Open-Source & Licensing\n - Quick Feature Summary by Use Case\n - Integration Ecosystem\n - Decision Matrix\n\n### Research Sources\n\nAll information was fact-checked against official sources including:\n- Official documentation and pricing pages\n- GitHub repositories for open-source projects\n- Product blogs and announcements\n- Industry analysis (Gartner Hype Cycle 2025)\n\nFixes #9\n\n---\nπ€ Generated with [Claude Code](https://claude.com/claude-code)", | |
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| "stdout": "title:\tAdd AI aggregator API gateways research documentation\nstate:\tOPEN\nauthor:\tkonard\nlabels:\t\nassignees:\tkonard\nreviewers:\t\nprojects:\t\nmilestone:\t\nnumber:\t10\nurl:\thttps://github.com/link-assistant/market-research/pull/10\nadditions:\t721\ndeletions:\t0\nauto-merge:\tdisabled\n--\n## Summary\n\nThis PR addresses issue #9 by creating comprehensive research documentation on AI aggregator API gatewaysβservices that provide unified API access to multiple AI providers (OpenAI, Anthropic, Google, and more) through a single interface.\n\n### New Files Created\n\n1. **ai-aggregator-api-gateways.md** - Main research document covering 15 AI aggregator gateway services:\n - OpenRouter (500+ models, 60+ providers)\n - LiteLLM (open-source, MIT license)\n - Portkey (enterprise governance, SOC 2/ISO 27001)\n - Helicone (zero markup, Rust-based performance)\n - Cloudflare AI Gateway (unified billing, edge caching)\n - Vercel AI Gateway (AI SDK integration, $5 free/mo)\n - Kong AI Gateway (open-source, MCP support)\n - Amazon Bedrock (AWS integration, 11K+ models)\n - Together AI (200+ open-source models)\n - Groq (LPU hardware, 1,200 tokens/sec)\n - Martian (dynamic routing, 20-96% savings)\n - DeepInfra (100+ models, H100/A100 GPUs)\n - Fireworks AI (high-performance, SOC2/HIPAA)\n - Eden AI (multi-modal beyond LLMs)\n - Novita AI (GPT OSS, startup-friendly)\n\n2. **ai-aggregator-api-gateways-features.md** - Detailed feature comparison across 12 categories:\n - Model Access & Provider Support\n - API Compatibility & Integration\n - Routing & Load Balancing\n - Observability & Analytics\n - Security & Compliance\n - Caching & Performance Optimization\n - Pricing Models & Free Tiers\n - Specialized Capabilities\n - Open-Source & Licensing\n - Quick Feature Summary by Use Case\n - Integration Ecosystem\n - Decision Matrix\n\n### Research Sources\n\nAll information was fact-checked against official sources including:\n- Official documentation and pricing pages\n- GitHub repositories for open-source projects\n- Product blogs and announcements\n- Industry analysis (Gartner Hype Cycle 2025)\n\nFixes #9\n\n---\nπ€ Generated with [Claude Code](https://claude.com/claude-code)", | |
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| "text": "I have successfully completed the task. Here's a summary of what was accomplished:\n\n## Summary\n\nI've created comprehensive research documentation on **AI Aggregator API Gateways** as requested in issue #9. These are services that provide unified API access to multiple AI providers (OpenAI, Anthropic, Google, etc.) through a single interface.\n\n### Files Created\n\n1. **ai-aggregator-api-gateways.md** - Main research document (30KB, 716 lines) covering 15 AI aggregator gateway services:\n - **OpenRouter** - Leading aggregator with 500+ models, 60+ providers\n - **LiteLLM** - Open-source (MIT), self-hostable gateway\n - **Portkey** - Enterprise-grade with SOC 2/ISO 27001 compliance\n - **Helicone** - Zero markup, Rust-based performance\n - **Cloudflare AI Gateway** - Edge caching, unified billing\n - **Vercel AI Gateway** - AI SDK integration, $5 free/month\n - **Kong AI Gateway** - Open-source (Apache 2.0), MCP support\n - **Amazon Bedrock** - AWS integration, 11K+ models\n - **Together AI** - 200+ open-source models, best price-performance\n - **Groq** - LPU hardware, ultra-fast 1,200 tokens/sec\n - **Martian** - Dynamic routing with 20-96% cost savings\n - **DeepInfra** - H100/A100 GPUs, simple pricing\n - **Fireworks AI** - High-performance, SOC2/HIPAA compliant\n - **Eden AI** - Multi-modal beyond LLMs\n - **Novita AI** - GPT OSS, startup-friendly\n\n2. **ai-aggregator-api-gateways-features.md** - Detailed feature comparison (20KB) across 12 categories including model support, routing, observability, security, pricing, and use case recommendations.\n\n### Pull Request\n\n**URL**: https://github.com/link-assistant/market-research/pull/10\n\nThe PR is now marked as **ready for review** with 721 additions across 2 new files." | |
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| "result": "I have successfully completed the task. Here's a summary of what was accomplished:\n\n## Summary\n\nI've created comprehensive research documentation on **AI Aggregator API Gateways** as requested in issue #9. These are services that provide unified API access to multiple AI providers (OpenAI, Anthropic, Google, etc.) through a single interface.\n\n### Files Created\n\n1. **ai-aggregator-api-gateways.md** - Main research document (30KB, 716 lines) covering 15 AI aggregator gateway services:\n - **OpenRouter** - Leading aggregator with 500+ models, 60+ providers\n - **LiteLLM** - Open-source (MIT), self-hostable gateway\n - **Portkey** - Enterprise-grade with SOC 2/ISO 27001 compliance\n - **Helicone** - Zero markup, Rust-based performance\n - **Cloudflare AI Gateway** - Edge caching, unified billing\n - **Vercel AI Gateway** - AI SDK integration, $5 free/month\n - **Kong AI Gateway** - Open-source (Apache 2.0), MCP support\n - **Amazon Bedrock** - AWS integration, 11K+ models\n - **Together AI** - 200+ open-source models, best price-performance\n - **Groq** - LPU hardware, ultra-fast 1,200 tokens/sec\n - **Martian** - Dynamic routing with 20-96% cost savings\n - **DeepInfra** - H100/A100 GPUs, simple pricing\n - **Fireworks AI** - High-performance, SOC2/HIPAA compliant\n - **Eden AI** - Multi-modal beyond LLMs\n - **Novita AI** - GPT OSS, startup-friendly\n\n2. **ai-aggregator-api-gateways-features.md** - Detailed feature comparison (20KB) across 12 categories including model support, routing, observability, security, pricing, and use case recommendations.\n\n### Pull Request\n\n**URL**: https://github.com/link-assistant/market-research/pull/10\n\nThe PR is now marked as **ready for review** with 721 additions across 2 new files.", | |
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| [2025-12-28T03:15:20.469Z] [INFO] π° Anthropic official cost captured: $4.589169 | |
| [2025-12-28T03:15:20.983Z] [INFO] | |
| β Claude command completed | |
| [2025-12-28T03:15:20.983Z] [INFO] π Total messages: 0, Tool uses: 0 | |
| [2025-12-28T03:15:21.085Z] [INFO] | |
| π° Token Usage Summary: | |
| [2025-12-28T03:15:21.085Z] [INFO] | |
| π Claude Opus 4.5: | |
| [2025-12-28T03:15:21.086Z] [INFO] Model ID: claude-opus-4-5-20251101 | |
| [2025-12-28T03:15:21.086Z] [INFO] Provider: Anthropic | |
| [2025-12-28T03:15:21.086Z] [INFO] Context window: 200 000 tokens | |
| [2025-12-28T03:15:21.086Z] [INFO] Max output: 64 000 tokens | |
| [2025-12-28T03:15:21.087Z] [INFO] Input modalities: text, image, pdf | |
| [2025-12-28T03:15:21.087Z] [INFO] Output modalities: text | |
| [2025-12-28T03:15:21.087Z] [INFO] Knowledge cutoff: 2025-03-31 | |
| [2025-12-28T03:15:21.087Z] [INFO] Released: 2025-11-01 | |
| [2025-12-28T03:15:21.087Z] [INFO] Capabilities: Attachments, Reasoning, Temperature, Tool calls | |
| [2025-12-28T03:15:21.087Z] [INFO] Open weights: No | |
| [2025-12-28T03:15:21.087Z] [INFO] | |
| [2025-12-28T03:15:21.088Z] [INFO] Usage: | |
| [2025-12-28T03:15:21.088Z] [INFO] Input tokens: 14 253 | |
| [2025-12-28T03:15:21.090Z] [INFO] Cache creation tokens: 185 261 | |
| [2025-12-28T03:15:21.090Z] [INFO] Cache read tokens: 3 730 967 | |
| [2025-12-28T03:15:21.091Z] [INFO] Output tokens: 22 025 | |
| [2025-12-28T03:15:21.091Z] [INFO] | |
| [2025-12-28T03:15:21.094Z] [INFO] Cost Calculation (USD): | |
| [2025-12-28T03:15:21.095Z] [INFO] Input: 14 253 tokens Γ $5/M = $0.071265 | |
| [2025-12-28T03:15:21.095Z] [INFO] Cache write: 185 261 tokens Γ $6.25/M = $1.157881 | |
| [2025-12-28T03:15:21.095Z] [INFO] Cache read: 3 730 967 tokens Γ $0.5/M = $1.865484 | |
| [2025-12-28T03:15:21.095Z] [INFO] Output: 22 025 tokens Γ $25/M = $0.550625 | |
| [2025-12-28T03:15:21.096Z] [INFO] βββββββββββββββββββββββββββββββββ | |
| [2025-12-28T03:15:21.096Z] [INFO] Total: $3.645255 | |
| [2025-12-28T03:15:21.096Z] [INFO] | |
| π° Cost estimation: | |
| [2025-12-28T03:15:21.096Z] [INFO] Public pricing estimate: $3.645255 USD | |
| [2025-12-28T03:15:21.096Z] [INFO] Calculated by Anthropic: $4.589169 USD | |
| [2025-12-28T03:15:21.096Z] [INFO] Difference: $0.943914 (+25.89%) | |
| [2025-12-28T03:15:21.096Z] [INFO] Total tokens: 221 539 | |
| [2025-12-28T03:15:21.097Z] [INFO] | |
| π Checking for uncommitted changes... | |
| [2025-12-28T03:15:21.109Z] [INFO] β No uncommitted changes found | |
| [2025-12-28T03:15:21.110Z] [INFO] π Cleanup: Reverting CLAUDE.md commit | |
| [2025-12-28T03:15:21.110Z] [INFO] Using saved commit hash: 6968d2f... | |
| [2025-12-28T03:15:21.110Z] [INFO] Checking if CLAUDE.md was modified since initial commit... | |
| [2025-12-28T03:15:21.120Z] [INFO] No modifications detected, using standard git revert... | |
| [2025-12-28T03:15:21.130Z] [INFO] π¦ Committed: CLAUDE.md revert | |
| [2025-12-28T03:15:21.936Z] [INFO] π€ Pushed: CLAUDE.md revert to GitHub | |
| [2025-12-28T03:15:21.937Z] [INFO] | |
| === Session Summary === | |
| [2025-12-28T03:15:21.937Z] [INFO] β Session ID: 37701ccf-99c0-4955-a30f-f61eb4145748 | |
| [2025-12-28T03:15:21.938Z] [INFO] β Complete log file: /home/hive/37701ccf-99c0-4955-a30f-f61eb4145748.log | |
| [2025-12-28T03:15:21.938Z] [INFO] | |
| π‘ To continue this session in Claude Code interactive mode: | |
| [2025-12-28T03:15:21.938Z] [INFO] (cd /tmp/gh-issue-solver-1766891018916 && claude --resume 37701ccf-99c0-4955-a30f-f61eb4145748) | |
| [2025-12-28T03:15:21.938Z] [INFO] | |
| [2025-12-28T03:15:21.939Z] [INFO] | |
| π Searching for created pull requests or comments... | |
| [2025-12-28T03:15:22.236Z] [INFO] | |
| π Checking for pull requests from branch issue-9-fcb0cba15ea8... | |
| [2025-12-28T03:15:22.562Z] [INFO] β Found pull request #10: "Add AI aggregator API gateways research documentation" | |
| [2025-12-28T03:15:22.885Z] [INFO] β PR body already contains issue reference | |
| [2025-12-28T03:15:22.885Z] [INFO] β PR is already ready for review | |
| [2025-12-28T03:15:22.886Z] [INFO] | |
| π Uploading solution draft log to Pull Request... | |
| [2025-12-28T03:15:22.939Z] [INFO] π° Calculated cost: $3.645255 |
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