LLM Pricing & Performance Comparison
The definitive, monthly-updated pricing matrix comparing commercial and open-weights foundation models. Compare input token costs, output token costs, context windows, and latency SLAs across Claude 3.5 Sonnet, GPT-4o, and Gemini 1.5 Pro.
Commercial & Open-Weights Matrix
5 Major Providers| Model Name | Classification Tag | Input Price / 1M Tokens | Output Price / 1M Tokens | Context Window |
|---|---|---|---|---|
| Anthropic Claude 3.5 Sonnet | Recommended Enterprise Model | $3.00 | $15.00 | 200k tokens |
| OpenAI GPT-4o | Standard Multi-Modal | $2.50 | $10.00 | 128k tokens |
| OpenAI GPT-4o Mini | High-Efficiency API | $0.15 | $0.60 | 128k tokens |
| Anthropic Claude 3 Haiku | Fast Lightweight | $0.25 | $1.25 | 200k tokens |
| Google Gemini 1.5 Pro | Ultra-Long Context | $3.50 | $10.50 | 2M tokens |
How to Evaluate LLM Price-to-Performance Ratios
Selecting a foundation model requires evaluating more than just raw token cost. While sub-dollar API options like GPT-4o Mini ($0.15/M input) offer incredible cost efficiency for basic classification, complex multi-step reasoning in LangGraph agents often requires Claude 3.5 Sonnet ($3.00/M input) to prevent state loops.
The Hidden Overhead of Context Window Scaling
Models offering ultra-long context windows (such as Gemini 1.5 Pro's 2-million-token window) enable ingesting entire codebases in a single prompt, but long-context API calls incur exponential time-to-first-token latency penalties. Utilizing a RAG vector database (pgvector or Pinecone) alongside a 128k context model yields faster sub-50ms responses at 10% of the token cost.
Frequently Asked Questions
How frequently is this LLM pricing comparison table updated? ↓
This page is maintained directly by Founder & Principal AI Architect Umar Abbas and updated monthly. Last updated: 2026-08-13.
Are open-weights models included in the pricing comparison? ↓
Yes. For open-weights models like Llama 3 or Qwen 2.5, we compute hosting costs based on dedicated vLLM instance VRAM requirements.