Rough Cost comparison: Clouds vs Self-hosted

cost_comparison.csv

plot.py

#!/usr/bin/env python3
import pandas as pd
import matplotlib.pyplot as plt
import os

# Read the CSV file
csv_path = os.path.expanduser('~/Downloads/cost_comparison.csv')
df = pd.read_csv(csv_path)

# Convert tokens to millions for better readability
df['tokens_millions'] = df['tokens'] / 1_000_000
# Convert to Piece & Wars volumes (1M tokens = 3 volumes)
df['piece_and_wars_volumes'] = df['tokens_millions'] * 3

# Create figure for cost comparison
plt.figure(figsize=(10, 6))
plt.plot(df['piece_and_wars_volumes'], df['cost_gcp_managed'], 'blue', marker='o', label='GCP Vertex AI', linewidth=2, markersize=6)
plt.plot(df['piece_and_wars_volumes'], df['cost_aws_managed'], 'orange', marker='o', label='AWS Bedrock', linewidth=2, markersize=6)
plt.plot(df['piece_and_wars_volumes'], df['cost_L4_self_hosted'], 'green', marker='o', label='Self-hosted L4 (500 tps)', linewidth=2, markersize=6)

plt.xlabel('Piece & War volumes', fontsize=12)
plt.ylabel('Cost ($)', fontsize=12)
plt.title('Rough Cost Comparison: Clouds vs Self-hosted L4', fontsize=14, fontweight='bold')
plt.legend(fontsize=10)
plt.grid(True, alpha=0.3)
plt.tight_layout()

# Save the cost plot
plt.savefig('/tmp/cost_to_tokens.png', dpi=300, bbox_inches='tight')
print("Cost plot saved to /tmp/cost_to_tokens.png")

# Create figure for latency comparison
plt.figure(figsize=(10, 6))

# Plot latency in hours for better readability
plt.plot(df['piece_and_wars_volumes'], df['latency_GCP_Vertex_hours'], 'chocolate', marker='o', label='GCP/AWS', linewidth=2, markersize=6)
# plt.plot(df['piece_and_wars_volumes'], df['latency_AWS_Managed_hours'], 'orange', marker='o', label='AWS Bedrock', linewidth=2, markersize=6)
plt.plot(df['piece_and_wars_volumes'], df['latency_L4_hours'], 'green', marker='o', label='Self-hosted L4', linewidth=2, markersize=6)

plt.xlabel('Piece & War volumes', fontsize=12)
plt.ylabel('Latency (Hours)', fontsize=12)
plt.title('Rough Latency Comparison: Clouds vs Self-hosted L4', fontsize=14, fontweight='bold')
plt.legend(fontsize=10)
plt.grid(True, alpha=0.3)
plt.tight_layout()

plt.savefig('/tmp/latency_to_tokens.png', dpi=300, bbox_inches='tight')
print("Latency plot saved to /tmp/latency_to_tokens.png")

plt.close('all')