AI Benchmark Encyclopedia & Evaluation Leaderboard
Explore the 10 standardized evaluations used to rank 330+ frontier and open-weights AI models. Compare methodology, dataset saturation, contamination risk, and top-performing models per discipline.
SWE-bench Verified
Evaluates whether an AI agent can autonomously resolve 500 human-validated real-world GitHub issues across popular Python repositories (Django, scikit-learn, Flask) by navigating multi-file codebases, editing code, and passing unit tests inside Docker containers.
Directly predicts performance in Cursor, Claude Code, Windsurf, and autonomous CI/CD bug-fixing agents.
Current Category Champions (2026)
SWE-bench Verified — Top 25 Ranked AI Models
223 verified models scored| # | Model | Provider | SWE-bench Score & Distribution | Blended 3:1 ($/1M) | Speed (tok/s) | Inspect |
|---|---|---|---|---|---|---|
| 1 | Claude Opus 5.5 | Anthropic | 84.6% | $8 | 78 tok/s | View Card |
| 2 | Claude Mythos 5.1 | Anthropic | 84.2% | $30 | 60 tok/s | View Card |
| 3 | GPT-5.6 Sol | OpenAI | 83.8% | $8 | 108 tok/s | View Card |
| 4 | Claude Fable 5.1 | Anthropic | 83.8% | $20 | 65 tok/s | View Card |
| 5 | Claude Opus 5 | Anthropic | 83.1% | $10 | 68 tok/s | View Card |
| 6 | Claude Sonnet 5.5 | Anthropic | 82.9% | $4 | 105 tok/s | View Card |
| 7 | GPT-5.5 Pro | OpenAI | 82.6% | $112.5 | 42 tok/s | View Card |
| 8 | GPT-6 Astra | OpenAI | 82.4% | $20 | 100 tok/s | View Card |
| 9 | GPT-6.1 Sol | OpenAI | 82.3% | $4 | 120 tok/s | View Card |
| 10 | GPT-6 Sol | OpenAI | 82.1% | $4 | 116 tok/s | View Card |
| 11 | Gemini 4 Argon | 81.9% | $4 | 115 tok/s | View Card | |
| 12 | GPT-5.6 Terra | OpenAI | 81.4% | $4 | 124 tok/s | View Card |
| 13 | Claude Sonnet 5 | Anthropic | 81.2% | $6 | 95 tok/s | View Card |
| 14 | GPT-5.5 | OpenAI | 81% | $11.25 | 112 tok/s | View Card |
| 15 | GPT-5.4 Pro | OpenAI | 80.8% | $56.25 | 48 tok/s | View Card |
| 16 | Claude Opus 4.8 | Anthropic | 80.8% | $10 | 64 tok/s | View Card |
| 17 | Claude Opus 4.7 | Anthropic | 79.5% | $10 | 58 tok/s | View Card |
| 18 | GPT-5.2 Pro | OpenAI | 79.4% | $48.125 | 50 tok/s | View Card |
| 19 | GPT-5.4 | OpenAI | 79.2% | $5.625 | 126 tok/s | View Card |
| 20 | GPT-5.3 Codex | OpenAI | 79% | $5.5 | 122 tok/s | View Card |
| 21 | GPT-5 Pro | OpenAI | 78.5% | $41.25 | 55 tok/s | View Card |
| 22 | Claude Opus 4.6 | Anthropic | 78.4% | $10 | 55 tok/s | View Card |
| 23 | GPT-5.1 Codex Max | OpenAI | 78.2% | $4.813 | 95 tok/s | View Card |
| 24 | GPT-5.2 Codex | OpenAI | 78.1% | $4.813 | 118 tok/s | View Card |
| 25 | Claude Sonnet 4.5 | Anthropic | 77.8% | $6 | 90 tok/s | View Card |
AI Evaluation Benchmarks & Methodology FAQ
How to use Claude 3.7 Sonnet for full-stack web development?+
Claude 3.7 Sonnet excels at full-stack development by combining architectural refactoring with extended thinking mode, achieving a 70.3% verified score on SWE-bench for autonomous multi-file bug fixing.
Is Claude 3.7 Sonnet better than GPT-4o for complex Python refactoring?+
Yes, Claude 3.7 Sonnet holds a decisive lead on multi-module Python refactoring due to its configurable extended thinking budget and state-of-the-art SWE-bench scores compared to GPT-4o standard generation.
Can DeepSeek R1 replace Claude 3.7 Sonnet for software engineering?+
DeepSeek R1 matches frontier models on algorithmic and mathematical logic at 10x lower API costs, but Claude 3.7 Sonnet retains the overall lead in end-to-end repository navigation and agentic tool use.
What is the best AI model for automated unit test generation in 2026?+
Claude 3.7 Sonnet and OpenAI o3-mini lead in automated unit test generation, delivering high branch coverage and minimizing edge-case regressions through rigorous chain-of-thought verification.
What is the SWE-bench verified score difference between Claude 3.7 Sonnet and o3-mini?+
Claude 3.7 Sonnet scores 70.3% on SWE-bench Verified in extended thinking mode, whereas OpenAI o3-mini scores approximately 49%, reflecting Claude specialized architecture for production software maintenance.
What is the difference between DeepSeek R1 reasoning tokens and standard output tokens?+
Reasoning tokens represent the internal chain-of-thought scratchpad generated during thinking mode. In DeepSeek R1, both reasoning tokens and visible output tokens are billed at the same economical $2.19/1M rate.