# Vals LiveCodeBench → AA Coding Index

Calibration · https://benchgap.net/calibration/1575 · data retrieved 2026-10-29

AA Coding Index is estimated from Vals LiveCodeBench with a offset logistic curve fitted on 39 models measured on both: y = 0.5959 + (0.7724 − 0.5959) / (1 + exp(−172.91·(x − 0.8723))), R² = 0.39, cross-validated error 9.0 pp. It is used for 1 estimate.

| Estimated model | Vals LiveCodeBench | AA Coding Index | Source |
|---|---|---|---|
| [GLM-4.5](https://benchgap.net/model/glm-4-5.md) | 67.4% | 59.6% | estimated ± 9.0 pp, low confidence |

## Fitted on

| Model | Vals LiveCodeBench | AA Coding Index |
|---|---|---|
| [Claude Fable 5](https://benchgap.net/model/claude-fable.md) | 89.8% | 76.5% |
| [Claude Fable 5.1](https://benchgap.net/model/claude-fable-5-1.md) | 90.5% | 81.6% |
| [Claude Opus 4.8](https://benchgap.net/model/claude-opus-4-8.md) | 87.8% | 74.3% |
| [Claude Opus 5](https://benchgap.net/model/claude-opus-5.md) | 89.0% | 78.0% |
| [Claude Sonnet 5](https://benchgap.net/model/claude-sonnet-5.md) | 82.4% | 71.6% |
| [DeepSeek V4 Flash 0731](https://benchgap.net/model/deepseek-v4-flash-0731.md) | 87.3% | 69.1% |
| [DeepSeek V4 Pro 0813](https://benchgap.net/model/deepseek-v4-pro-0813.md) | 87.5% | 68.8% |
| [Gemini 3.1 Pro](https://benchgap.net/model/gemini-3-1-pro.md) | 88.5% | 68.8% |
| [Gemini 3.5 Flash](https://benchgap.net/model/gemini-3-5-flash.md) | 87.6% | 70.1% |
| [Gemini 3.5 Flash-Lite](https://benchgap.net/model/gemini-3-5-flash-lite.md) | 79.0% | 49.3% |
| [Gemini 3.6 Flash](https://benchgap.net/model/gemini-3-6-flash.md) | 88.1% | 69.2% |
| [Gemini 3.7 Flash](https://benchgap.net/model/gemini-3-7-flash.md) | 88.7% | 76.1% |
| [Gemini 3.8 Flash](https://benchgap.net/model/gemini-3-8-flash.md) | 89.5% | 76.3% |
| [GLM-4.7](https://benchgap.net/model/glm-4-7.md) | 82.2% | 45.3% |
| [GLM-5.1](https://benchgap.net/model/glm-5-1.md) | 81.4% | 55.8% |
| [GLM-5.2](https://benchgap.net/model/glm-5-2.md) | 69.5% | 68.8% |
| [GLM-5.3](https://benchgap.net/model/glm-5-3.md) | 80.5% | 74.8% |
| [GPT-5.4 mini](https://benchgap.net/model/gpt-5-4-mini.md) | 81.5% | 56.1% |
| [GPT-5.4 nano](https://benchgap.net/model/gpt-5-4-nano.md) | 84.0% | 56.1% |
| [GPT-5.5](https://benchgap.net/model/gpt-5-5.md) | 85.3% | 74.9% |
| [GPT-5.6 Sol](https://benchgap.net/model/gpt-5-6-sol.md) | 82.6% | 77.4% |
| [GPT-5.6 Terra](https://benchgap.net/model/gpt-5-6-terra.md) | 85.9% | 76.7% |
| [Grok 4.3](https://benchgap.net/model/grok-4-3.md) | 84.5% | 42.3% |
| [Grok 4.5](https://benchgap.net/model/grok-4-5.md) | 87.4% | 72.5% |
| [Grok 4.6](https://benchgap.net/model/grok-4-6.md) | 88.2% | 76.8% |
| [Inkling](https://benchgap.net/model/inkling.md) | 85.5% | 52.1% |
| [Inkling-Small](https://benchgap.net/model/inkling-small.md) | 85.9% | 52.9% |
| [Kimi K2.6](https://benchgap.net/model/kimi-2-6.md) | 86.8% | 61.8% |
| [Kimi K2.7 Code](https://benchgap.net/model/kimi-k2-7-code.md) | 82.1% | 60.8% |
| [Kimi K3](https://benchgap.net/model/kimi-k3.md) | 87.2% | 76.2% |
| [Ling 3.0 Flash](https://benchgap.net/model/ling-3-0-flash.md) | 84.0% | 50.6% |
| [MiMo-V2.5-Pro](https://benchgap.net/model/mimo-v2-5-pro.md) | 81.4% | 60.2% |
| [MiniMax M2.7](https://benchgap.net/model/minimax-m2-7.md) | 79.9% | 52.6% |
| [MiniMax M3](https://benchgap.net/model/minimax-m3.md) | 82.2% | 58.6% |
| [Muse Spark 1.1](https://benchgap.net/model/muse-spark-1-1.md) | 85.9% | 71.3% |
| [Nemotron 3 Ultra](https://benchgap.net/model/nemotron-3-ultra.md) | 86.0% | 49.3% |
| [Qwen3.6 Plus](https://benchgap.net/model/qwen3-6-plus.md) | 86.0% | 54.5% |
| [Qwen3.7 Max](https://benchgap.net/model/qwen3-7-max.md) | 87.1% | 66.0% |
| [Qwen3.8-27B](https://benchgap.net/model/qwen3-8-27b.md) | 84.0% | 68.1% |