# Vals MMLU-Pro → AA-HLE

Calibration · https://benchgap.net/calibration/1555 · data retrieved 2026-10-29

AA-HLE is estimated from Vals MMLU-Pro with a inverse Michaelis–Menten curve fitted on 46 models measured on both: y = 0.06551·(x − 0.0000) / (0.0000 + 1.0294 − x), R² = 0.51, cross-validated error 7.5 pp. It is used for 0 estimates.

## Fitted on

| Model | Vals MMLU-Pro | AA-HLE |
|---|---|---|
| [Claude Fable 5](https://benchgap.net/model/claude-fable.md) | 91.5% | 55.5% |
| [Claude Fable 5.1](https://benchgap.net/model/claude-fable-5-1.md) | 92.4% | 59.1% |
| [Claude Opus 4.7](https://benchgap.net/model/claude-opus-4-7.md) | 89.9% | 33.3% |
| [Claude Opus 4.8](https://benchgap.net/model/claude-opus-4-8.md) | 89.6% | 48.7% |
| [Claude Opus 5](https://benchgap.net/model/claude-opus-5.md) | 91.6% | 54.9% |
| [Claude Sonnet 4.6](https://benchgap.net/model/claude-sonnet-4-6.md) | 87.3% | 13.3% |
| [Claude Sonnet 5](https://benchgap.net/model/claude-sonnet-5.md) | 87.5% | 41.3% |
| [DeepSeek V4 Flash 0731](https://benchgap.net/model/deepseek-v4-flash-0731.md) | 86.2% | 38.6% |
| [DeepSeek V4 Pro 0813](https://benchgap.net/model/deepseek-v4-pro-0813.md) | 87.0% | 41.0% |
| [Gemini 3.1 Pro](https://benchgap.net/model/gemini-3-1-pro.md) | 91.0% | 47.0% |
| [Gemini 3.5 Flash](https://benchgap.net/model/gemini-3-5-flash.md) | 89.5% | 42.7% |
| [Gemini 3.5 Flash-Lite](https://benchgap.net/model/gemini-3-5-flash-lite.md) | 85.8% | 18.8% |
| [Gemini 3.6 Flash](https://benchgap.net/model/gemini-3-6-flash.md) | 89.3% | 40.8% |
| [Gemini 3.7 Flash](https://benchgap.net/model/gemini-3-7-flash.md) | 90.1% | 47.9% |
| [Gemini 3.8 Flash](https://benchgap.net/model/gemini-3-8-flash.md) | 90.2% | 47.8% |
| [Gemini 3 Flash](https://benchgap.net/model/gemini-3-flash.md) | 88.6% | 15.0% |
| [GLM-4.6](https://benchgap.net/model/glm-4-6.md) | 82.2% | 5.5% |
| [GLM-4.7](https://benchgap.net/model/glm-4-7.md) | 82.7% | 27.4% |
| [GLM-5.1](https://benchgap.net/model/glm-5-1.md) | 86.9% | 30.1% |
| [GLM-5.2](https://benchgap.net/model/glm-5-2.md) | 86.7% | 41.1% |
| [GLM-5.3](https://benchgap.net/model/glm-5-3.md) | 86.8% | 42.3% |
| [GPT-5.4 mini](https://benchgap.net/model/gpt-5-4-mini.md) | 84.6% | 28.1% |
| [GPT-5.4 nano](https://benchgap.net/model/gpt-5-4-nano.md) | 77.2% | 28.3% |
| [GPT-5.5](https://benchgap.net/model/gpt-5-5.md) | 88.1% | 45.8% |
| [GPT-5.6 Luna](https://benchgap.net/model/gpt-5-6-luna.md) | 86.0% | 39.5% |
| [GPT-5.6 Sol](https://benchgap.net/model/gpt-5-6-sol.md) | 89.1% | 49.5% |
| [GPT-5.6 Terra](https://benchgap.net/model/gpt-5-6-terra.md) | 86.7% | 42.9% |
| [Grok 4.3](https://benchgap.net/model/grok-4-3.md) | 85.8% | 37.2% |
| [Grok 4.5](https://benchgap.net/model/grok-4-5.md) | 89.2% | 42.7% |
| [Grok 4.6](https://benchgap.net/model/grok-4-6.md) | 89.4% | 42.9% |
| [Inkling](https://benchgap.net/model/inkling.md) | 86.3% | 31.9% |
| [Inkling-Small](https://benchgap.net/model/inkling-small.md) | 85.6% | 33.3% |
| [Kimi K2.6](https://benchgap.net/model/kimi-2-6.md) | 87.6% | 37.5% |
| [Kimi K3](https://benchgap.net/model/kimi-k3.md) | 88.0% | 46.9% |
| [Ling 3.0 Flash](https://benchgap.net/model/ling-3-0-flash.md) | 82.0% | 23.7% |
| [MiMo-V2.5-Pro](https://benchgap.net/model/mimo-v2-5-pro.md) | 84.6% | 35.7% |
| [MiniMax M2.7](https://benchgap.net/model/minimax-m2-7.md) | 80.4% | 29.6% |
| [MiniMax M3](https://benchgap.net/model/minimax-m3.md) | 84.2% | 39.0% |
| [Mistral Medium 3.5 128B](https://benchgap.net/model/mistral-medium-3-5-128b.md) | 75.3% | 13.8% |
| [Muse Spark](https://benchgap.net/model/muse-spark.md) | 87.3% | 40.7% |
| [Muse Spark 1.1](https://benchgap.net/model/muse-spark-1-1.md) | 88.7% | 46.2% |
| [Muse Spark 1.2](https://benchgap.net/model/muse-spark-1-2.md) | 88.3% | 45.5% |
| [Nemotron 3 Ultra](https://benchgap.net/model/nemotron-3-ultra.md) | 85.8% | 28.4% |
| [Qwen3.6 Plus](https://benchgap.net/model/qwen3-6-plus.md) | 87.7% | 27.8% |
| [Qwen3.7 Max](https://benchgap.net/model/qwen3-7-max.md) | 89.3% | 40.5% |
| [Qwen3.8-27B](https://benchgap.net/model/qwen3-8-27b.md) | 84.3% | 33.9% |