Survey of open-source evaluation/agent harness frameworks (lm-eval-harness, OpenAI Evals, LangChain, HELM, lmms-eval, leaderboards)

AI Agent Harness — Survey of Open-Source Evaluation Frameworks

# AI Agent Harness Survey

Short Description of Research Question

I surveyed major open-source projects and leaderboards for evaluating language models (LLMs), multimodal models (LMMs), and agent systems to answer: "What existing harnesses, frameworks, and leaderboards are available for evaluating LLMs/LMMs and building/running agent harnesses?"

## Summary of Findings

- lm-evaluation-harness (EleutherAI)
  - A mature, widely-used framework for few-shot evaluation of language models. Supports many model backends (HF transformers, vLLM, GGUF/llama.cpp, OpenAI/Anthropic/TextSynth APIs, vLLM, SGLang, NeMo, etc.), many tasks (>60 academic benchmarks), flexible prompt templating (Jinja2, Promptsource), caching, logging, and hub integration. Backend for Hugging Face's Open LLM Leaderboard.

- OpenAI Evals (openai/evals)
  - Framework and registry focused on writing, running, and sharing evals. Provides templates for many eval types, model-graded evals, and integration with OpenAI API. Oriented toward reproducible evaluation workflows and supports private evals. Suitable for designing custom evaluation logic and templates without coding heavy custom code for many cases.

- LangChain (langchain-ai/langchain)
  - Not an evaluation harness per se; LangChain is an agent and application framework for building LLM-powered agents, chains, tools, and integrations. For "agent harnesses" (running, orchestrating, and observing agent behavior) LangChain (plus LangSmith) is the main open-source ecosystem used in production to build, debug, and evaluate agents and trajectories.

- HELM (stanford-crfm/helm)
  - Holistic Evaluation of Language Models: a framework & leaderboard for large-scale, reproducible, multi-aspect evaluation (capabilities, safety, bias, efficiency). Maintains leaderboards and docs; supports diverse models and metrics beyond accuracy.

- LMMs-Eval (EvolvingLMMs-Lab/lmms-eval)
  - A fork/extension of lm-evaluation-harness for multimodal (text+image/video/audio) models. Focused on consistent evaluation across LMMs with many tasks (100+), multimodal model support, vLLM and OpenAI-compatible APIs, and tooling for batched/multimodal evaluation.

- Meta LLaMA repo (meta-llama/llama)
  - Inference code and examples for LLaMA family models; useful as model-specific inference harness and quickstart for running model inference locally; not an evaluation harness but relevant for hosting and running models under evaluation.

- Open LLM Leaderboard (Hugging Face Space)
  - Public leaderboard running on results produced by lm-evaluation-harness; good reference for community results and configurations.

- Notes/404: attempted to visit an "awesome" list (LAION) but repo/page not found; still covered other major projects.

Recommendations

- If you need a general-purpose evaluation harness for LLMs: start with EleutherAI's lm-evaluation-harness (broad backend support, reproducible tasks, HF integration).
- If you will use OpenAI APIs or want a registry and templating-first system: evaluate OpenAI Evals (templates, model-graded YAMLs, registry of evals).
- For agent development and evaluation (trajectories, tool use, observability): use LangChain + LangSmith; LangChain for orchestration and LangSmith for agent-level debugging/observability.
- For multimodal evaluation (images/video/audio): use lmms-eval or HELM VHELM depending on tasks and leaderboards you want to align with.
- For leaderboards and benchmarking references: review Hugging Face Open LLM Leaderboard and HELM leaderboards.

## Sources

- [EleutherAI / lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness) - README & docs: features, supported backends (HF, vLLM, APIs), usage examples, tasks, and installation.
- [OpenAI / evals](https://github.com/openai/evals) - README: framework for defining and running evals, registry, templates, and OpenAI-specific integrations.
- [LangChain (langchain-ai/langchain)](https://github.com/langchain-ai/langchain) - Repo overview: agent framework for building and running agents; not an evaluation harness but central to agent orchestration.
- [Meta LLaMA (meta-llama/llama)](https://github.com/meta-llama/llama) - Inference code and quickstart info for LLaMA family models.
- [Stanford CRFM / HELM](https://github.com/stanford-crfm/helm) - Holistic evaluation framework and leaderboards for multi-aspect model evaluation.
- [EvolvingLMMs-Lab / lmms-eval](https://github.com/EvolvingLMMs-Lab/lmms-eval) - Multimodal evaluation toolkit forked from lm-eval harness with support for image/video/audio tasks and many models/tasks.
- [Open LLM Leaderboard (Hugging Face Space)](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) - Public leaderboard running evaluation results (uses lm-eval-harness as backend).
- [LAION / awesome-open-source-eval-frameworks (404)](https://github.com/LAION-AI/awesome-open-source-eval-frameworks) - attempted visit (page not found).

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If you want, I can:
- produce a short comparison table of features (backends, multimodal support, agent features, leaderboard integration) across these projects;
- generate example commands for getting started with one or two of the frameworks (lm-eval-harness, OpenAI Evals, LangChain) tailored to your models and infrastructure.