Best AI Models for Coding (2026)
Ranked by performance on coding benchmarks that test real software engineering — SWE-Bench Verified (fixing real GitHub issues), LiveCodeBench (contamination-free competitive programming) and SciCode. This is the score that matters if you code with AI.
| # | Model | Coding avg | Price / 1M |
|---|---|---|---|
| 1 | Qwen3 Max Thinking | 91.4% | $1.56 |
| 2 |  Claude Opus 4.8 | 88.6% | $10.00 |
| 3 | Claude Opus 4.7 | 87.6% | $10.00 |
| 4 |  DeepSeek V4 Pro | 87.1% | $0.54 |
| 5 | DeepSeek V4 Flash | 85.3% | $0.11 |
| 6 |  Gemini 3.1 Pro Preview | 80.6% | $4.50 |
| 7 | Claude Sonnet 4.6 | 79.6% | $6.00 |
| 8 | Gemini 3 Flash Preview | 78% | $1.13 |
| 9 |  Kimi K2 Thinking | 77.2% | $1.07 |
| 10 | Qwen3 Max | 69.6% | $1.56 |
| 11 | Gemini 2.5 Pro | 64.3% | $3.44 |
| 12 |  Llama 4 Maverick | 43.4% | $0.26 |
Based on verified public benchmarks; see methodology. Prices are blended 3:1 input:output per million tokens.
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FAQ
What is the best AI model for coding?
Qwen3 Max Thinking leads this ranking with 91.4%. The full top 20 is in the table above, updated as new benchmark results land.
How is this ranking calculated?
Ranked by performance on coding benchmarks that test real software engineering — SWE-Bench Verified (fixing real GitHub issues), LiveCodeBench (contamination-free competitive programming) and SciCode. This is the score that matters if you code with AI. We only use publicly verifiable benchmark results with cited sources — no estimates. See our methodology page for the exact formula.
How often does this list change?
Pricing and model availability refresh hourly from OpenRouter; benchmark scores update whenever a lab publishes new official results. The ranking reflects the latest verified data.