# Vals MMLU-Pro → HealthBench Professional

Calibration · https://benchgap.net/calibration/1563 · data retrieved 2026-10-29

HealthBench Professional is estimated from Vals MMLU-Pro with a offset logistic curve fitted on 5 models measured on both: y = 0.4983 + (0.5999 − 0.4983) / (1 + exp(−130.12·(x − 0.8576))), R² = 0.95, cross-validated error 1.3 pp. It is used for 46 estimates.

| Estimated model | Vals MMLU-Pro | HealthBench Professional | Source |
|---|---|---|---|
| [Claude Fable 5.1](https://benchgap.net/model/claude-fable-5-1.md) | 92.4% | 60.0% | estimated ± 1.3 pp, low confidence |
| [Claude Fable 5](https://benchgap.net/model/claude-fable.md) | 91.5% | 60.0% | estimated ± 1.3 pp, medium confidence |
| [Gemini 3.1 Pro](https://benchgap.net/model/gemini-3-1-pro.md) | 91.0% | 60.0% | estimated ± 1.3 pp, medium confidence |
| [Gemini 3.8 Flash](https://benchgap.net/model/gemini-3-8-flash.md) | 90.2% | 60.0% | estimated ± 1.3 pp, medium confidence |
| [Gemini 3.7 Flash](https://benchgap.net/model/gemini-3-7-flash.md) | 90.1% | 60.0% | estimated ± 1.3 pp, medium confidence |
| [Claude Opus 4.7](https://benchgap.net/model/claude-opus-4-7.md) | 89.9% | 59.9% | estimated ± 1.3 pp, medium confidence |
| [Claude Opus 4.8](https://benchgap.net/model/claude-opus-4-8.md) | 89.6% | 59.9% | estimated ± 1.3 pp, medium confidence |
| [Gemini 3.5 Flash](https://benchgap.net/model/gemini-3-5-flash.md) | 89.5% | 59.9% | estimated ± 1.3 pp, medium confidence |
| [Grok 4.6](https://benchgap.net/model/grok-4-6.md) | 89.4% | 59.9% | estimated ± 1.3 pp, medium confidence |
| [Gemini 3.6 Flash](https://benchgap.net/model/gemini-3-6-flash.md) | 89.3% | 59.9% | estimated ± 1.3 pp, medium confidence |
| [Qwen3.7 Max](https://benchgap.net/model/qwen3-7-max.md) | 89.3% | 59.9% | estimated ± 1.3 pp, medium confidence |
| [Grok 4.5](https://benchgap.net/model/grok-4-5.md) | 89.2% | 59.9% | estimated ± 1.3 pp, medium confidence |
| [Gemini 3 Flash](https://benchgap.net/model/gemini-3-flash.md) | 88.6% | 59.7% | estimated ± 1.3 pp, medium confidence |
| [Qwen3.8 Max](https://benchgap.net/model/qwen3-8-max.md) | 88.6% | 59.7% | estimated ± 1.3 pp, medium confidence |
| [Muse Spark 1.2](https://benchgap.net/model/muse-spark-1-2.md) | 88.3% | 59.6% | estimated ± 1.3 pp, medium confidence |
| [GPT-5.5](https://benchgap.net/model/gpt-5-5.md) | 88.1% | 59.5% | estimated ± 1.3 pp, medium confidence |
| [Kimi K3](https://benchgap.net/model/kimi-k3.md) | 88.0% | 59.5% | estimated ± 1.3 pp, medium confidence |
| [Qwen3.6 Plus](https://benchgap.net/model/qwen3-6-plus.md) | 87.7% | 59.2% | estimated ± 1.3 pp, medium confidence |
| [Kimi K2.6](https://benchgap.net/model/kimi-2-6.md) | 87.6% | 59.1% | estimated ± 1.3 pp, medium confidence |
| [Claude Sonnet 5](https://benchgap.net/model/claude-sonnet-5.md) | 87.5% | 59.0% | estimated ± 1.3 pp, medium confidence |
| [Claude Sonnet 4.6](https://benchgap.net/model/claude-sonnet-4-6.md) | 87.3% | 58.8% | estimated ± 1.3 pp, medium confidence |
| [Muse Spark](https://benchgap.net/model/muse-spark.md) | 87.3% | 58.8% | estimated ± 1.3 pp, medium confidence |
| [DeepSeek V4 Pro 0813](https://benchgap.net/model/deepseek-v4-pro-0813.md) | 87.0% | 58.3% | estimated ± 1.3 pp, medium confidence |
| [GLM-5.1](https://benchgap.net/model/glm-5-1.md) | 86.9% | 58.1% | estimated ± 1.3 pp, medium confidence |
| [GLM-5.3](https://benchgap.net/model/glm-5-3.md) | 86.8% | 57.9% | estimated ± 1.3 pp, medium confidence |
| [GLM-5.2](https://benchgap.net/model/glm-5-2.md) | 86.7% | 57.7% | estimated ± 1.3 pp, medium confidence |
| [Grok 4.20](https://benchgap.net/model/grok-4-20-beta.md) | 86.3% | 56.6% | estimated ± 1.3 pp, medium confidence |
| [Inkling](https://benchgap.net/model/inkling.md) | 86.3% | 56.6% | estimated ± 1.3 pp, medium confidence |
| [DeepSeek V4 Flash 0731](https://benchgap.net/model/deepseek-v4-flash-0731.md) | 86.2% | 56.3% | estimated ± 1.3 pp, medium confidence |
| [Gemini 3.1 Flash-Lite](https://benchgap.net/model/gemini-3-1-flash-lite.md) | 86.2% | 56.3% | estimated ± 1.3 pp, medium confidence |
| [GLM-5.3-Flash](https://benchgap.net/model/glm-5-3-flash.md) | 86.1% | 56.0% | estimated ± 1.3 pp, medium confidence |
| [Gemini 3.5 Flash-Lite](https://benchgap.net/model/gemini-3-5-flash-lite.md) | 85.8% | 55.0% | estimated ± 1.3 pp, low confidence |
| [Grok 4.3](https://benchgap.net/model/grok-4-3.md) | 85.8% | 55.0% | estimated ± 1.3 pp, low confidence |
| [Nemotron 3 Ultra](https://benchgap.net/model/nemotron-3-ultra.md) | 85.8% | 55.0% | estimated ± 1.3 pp, low confidence |
| [Inkling-Small](https://benchgap.net/model/inkling-small.md) | 85.6% | 54.4% | estimated ± 1.3 pp, low confidence |
| [GPT-5.4 mini](https://benchgap.net/model/gpt-5-4-mini.md) | 84.6% | 51.7% | estimated ± 1.3 pp, low confidence |
| [MiMo-V2.5-Pro](https://benchgap.net/model/mimo-v2-5-pro.md) | 84.6% | 51.7% | estimated ± 1.3 pp, low confidence |
| [Qwen3.8-27B](https://benchgap.net/model/qwen3-8-27b.md) | 84.3% | 51.2% | estimated ± 1.3 pp, low confidence |
| [MiniMax M3](https://benchgap.net/model/minimax-m3.md) | 84.2% | 51.0% | estimated ± 1.3 pp, low confidence |
| [Qwen3.5 Flash](https://benchgap.net/model/qwen3-5-flash.md) | 84.1% | 50.9% | estimated ± 1.3 pp, low confidence |
| [MiMo-V2.5](https://benchgap.net/model/mimo-v2-5.md) | 82.9% | 50.1% | estimated ± 1.3 pp, low confidence |
| [GLM-4.7](https://benchgap.net/model/glm-4-7.md) | 82.7% | 50.0% | estimated ± 1.3 pp, low confidence |
| [GLM-4.6](https://benchgap.net/model/glm-4-6.md) | 82.2% | 49.9% | estimated ± 1.3 pp, low confidence |
| [Ling 3.0 Flash](https://benchgap.net/model/ling-3-0-flash.md) | 82.0% | 49.9% | estimated ± 1.3 pp, low confidence |
| [GLM-4.5](https://benchgap.net/model/glm-4-5.md) | 81.2% | 49.9% | estimated ± 1.3 pp, low confidence |
| [MiniMax M2.7](https://benchgap.net/model/minimax-m2-7.md) | 80.4% | 49.8% | estimated ± 1.3 pp, low confidence |

## Fitted on

| Model | Vals MMLU-Pro | HealthBench Professional |
|---|---|---|
| [Claude Opus 5](https://benchgap.net/model/claude-opus-5.md) | 91.6% | 59.8% |
| [GPT-5.6 Luna](https://benchgap.net/model/gpt-5-6-luna.md) | 86.0% | 55.7% |
| [GPT-5.6 Sol](https://benchgap.net/model/gpt-5-6-sol.md) | 89.1% | 60.5% |
| [GPT-5.6 Terra](https://benchgap.net/model/gpt-5-6-terra.md) | 86.7% | 57.7% |
| [Muse Spark 1.1](https://benchgap.net/model/muse-spark-1-1.md) | 88.7% | 59.3% |