# Vals GPQA Diamond → Vals MMLU-Pro Calibration · https://benchgap.net/calibration/1553 · data retrieved 2026-10-29 Vals MMLU-Pro is estimated from Vals GPQA Diamond with a Hill curve fitted on 55 models measured on both: y = 0.7083 + (0.9866 − 0.7083)·x^6.00 / (0.83901^6.00 + x^6.00), R² = 0.82, cross-validated error 2.2 pp. It is used for 0 estimates. ## Fitted on | Model | Vals GPQA Diamond | Vals MMLU-Pro | |---|---|---| | [Claude Fable 5](https://benchgap.net/model/claude-fable.md) | 93.2% | 91.5% | | [Claude Fable 5.1](https://benchgap.net/model/claude-fable-5-1.md) | 93.4% | 92.4% | | [Claude Haiku 4.5](https://benchgap.net/model/claude-haiku-4-5.md) | 72.2% | 78.7% | | [Claude Opus 4.7](https://benchgap.net/model/claude-opus-4-7.md) | 90.2% | 89.9% | | [Claude Opus 4.8](https://benchgap.net/model/claude-opus-4-8.md) | 92.4% | 89.6% | | [Claude Opus 5](https://benchgap.net/model/claude-opus-5.md) | 93.4% | 91.6% | | [Claude Sonnet 4.6](https://benchgap.net/model/claude-sonnet-4-6.md) | 85.6% | 87.3% | | [Claude Sonnet 5](https://benchgap.net/model/claude-sonnet-5.md) | 88.9% | 87.5% | | [DeepSeek V4 Flash 0731](https://benchgap.net/model/deepseek-v4-flash-0731.md) | 89.9% | 86.2% | | [DeepSeek V4 Pro 0813](https://benchgap.net/model/deepseek-v4-pro-0813.md) | 92.4% | 87.0% | | [Gemini 3.1 Flash-Lite](https://benchgap.net/model/gemini-3-1-flash-lite.md) | 81.1% | 86.2% | | [Gemini 3.1 Pro](https://benchgap.net/model/gemini-3-1-pro.md) | 95.5% | 91.0% | | [Gemini 3.5 Flash](https://benchgap.net/model/gemini-3-5-flash.md) | 92.7% | 89.5% | | [Gemini 3.5 Flash-Lite](https://benchgap.net/model/gemini-3-5-flash-lite.md) | 83.8% | 85.8% | | [Gemini 3.6 Flash](https://benchgap.net/model/gemini-3-6-flash.md) | 93.4% | 89.3% | | [Gemini 3.7 Flash](https://benchgap.net/model/gemini-3-7-flash.md) | 93.9% | 90.1% | | [Gemini 3.8 Flash](https://benchgap.net/model/gemini-3-8-flash.md) | 94.4% | 90.2% | | [Gemini 3 Flash](https://benchgap.net/model/gemini-3-flash.md) | 87.9% | 88.6% | | [GLM-4.5](https://benchgap.net/model/glm-4-5.md) | 72.2% | 81.2% | | [GLM-4.6](https://benchgap.net/model/glm-4-6.md) | 74.5% | 82.2% | | [GLM-4.7](https://benchgap.net/model/glm-4-7.md) | 80.1% | 82.7% | | [GLM-5.1](https://benchgap.net/model/glm-5-1.md) | 84.5% | 86.9% | | [GLM-5.2](https://benchgap.net/model/glm-5-2.md) | 85.6% | 86.7% | | [GLM-5.3](https://benchgap.net/model/glm-5-3.md) | 88.1% | 86.8% | | [GLM-5.3-Flash](https://benchgap.net/model/glm-5-3-flash.md) | 86.4% | 86.1% | | [GPT-5.4 mini](https://benchgap.net/model/gpt-5-4-mini.md) | 83.1% | 84.6% | | [GPT-5.4 nano](https://benchgap.net/model/gpt-5-4-nano.md) | 77.5% | 77.2% | | [GPT-5.5](https://benchgap.net/model/gpt-5-5.md) | 93.2% | 88.1% | | [GPT-5.6 Luna](https://benchgap.net/model/gpt-5-6-luna.md) | 91.7% | 86.0% | | [GPT-5.6 Sol](https://benchgap.net/model/gpt-5-6-sol.md) | 95.2% | 89.1% | | [GPT-5.6 Terra](https://benchgap.net/model/gpt-5-6-terra.md) | 90.9% | 86.7% | | [Grok 4.20](https://benchgap.net/model/grok-4-20-beta.md) | 88.6% | 86.3% | | [Grok 4.3](https://benchgap.net/model/grok-4-3.md) | 91.4% | 85.8% | | [Grok 4.5](https://benchgap.net/model/grok-4-5.md) | 92.9% | 89.2% | | [Grok 4.6](https://benchgap.net/model/grok-4-6.md) | 94.7% | 89.4% | | [Inkling](https://benchgap.net/model/inkling.md) | 87.1% | 86.3% | | [Inkling-Small](https://benchgap.net/model/inkling-small.md) | 83.6% | 85.6% | | [Kimi K2.6](https://benchgap.net/model/kimi-2-6.md) | 89.1% | 87.6% | | [Kimi K3](https://benchgap.net/model/kimi-k3.md) | 92.9% | 88.0% | | [Laguna M.1](https://benchgap.net/model/laguna-m-1.md) | 27.0% | 68.8% | | [Laguna XS.2](https://benchgap.net/model/laguna-xs-2.md) | 55.1% | 69.1% | | [Ling 3.0 Flash](https://benchgap.net/model/ling-3-0-flash.md) | 84.8% | 82.0% | | [MiMo-V2.5](https://benchgap.net/model/mimo-v2-5.md) | 81.6% | 82.9% | | [MiMo-V2.5-Pro](https://benchgap.net/model/mimo-v2-5-pro.md) | 82.6% | 84.6% | | [MiniMax M2.7](https://benchgap.net/model/minimax-m2-7.md) | 86.6% | 80.4% | | [MiniMax M3](https://benchgap.net/model/minimax-m3.md) | 92.7% | 84.2% | | [Mistral Medium 3.5 128B](https://benchgap.net/model/mistral-medium-3-5-128b.md) | 34.8% | 75.3% | | [Muse Spark](https://benchgap.net/model/muse-spark.md) | 89.6% | 87.3% | | [Muse Spark 1.1](https://benchgap.net/model/muse-spark-1-1.md) | 91.2% | 88.7% | | [Nemotron 3 Ultra](https://benchgap.net/model/nemotron-3-ultra.md) | 86.1% | 85.8% | | [Qwen3.5 Flash](https://benchgap.net/model/qwen3-5-flash.md) | 82.8% | 84.1% | | [Qwen3.6 Plus](https://benchgap.net/model/qwen3-6-plus.md) | 87.4% | 87.7% | | [Qwen3.7 Max](https://benchgap.net/model/qwen3-7-max.md) | 90.2% | 89.3% | | [Qwen3.8-27B](https://benchgap.net/model/qwen3-8-27b.md) | 88.9% | 84.3% | | [Qwen3.8 Max](https://benchgap.net/model/qwen3-8-max.md) | 93.7% | 88.6% |