benchgap
Calibration

AA-MMMU-Pro → MMMU-Pro

MMMU-Pro is estimated from AA-MMMU-Pro with a Michaelis–Menten + offset curve fitted on 32 models measured on both: y = 0.3302 + 2.0000·x / (2.66446 + x), R² = 0.43, cross-validated error 4.4 pp. It is used for 59 estimates.

Estimated modelAA-MMMU-ProMMMU-ProSource
Apodex 1.179.2%78.8%estimated ± 4.4 pp, medium confidence
Apodex 1.1 Mini79.2%78.8%estimated ± 4.4 pp, medium confidence
Claude 3 Haiku30.8%53.7%estimated ± 4.4 pp, low confidence
Claude 4.1 Opus Thinking67.9%73.6%estimated ± 4.4 pp, medium confidence
Claude 4 Sonnet62.4%71.0%estimated ± 4.4 pp, medium confidence
Claude Opus 4.5 Thinking74.0%76.5%estimated ± 4.4 pp, medium confidence
Claude Opus 4.6 (Adaptive)75.4%77.1%estimated ± 4.4 pp, medium confidence
Claude Opus 4.776.4%77.6%estimated ± 4.4 pp, medium confidence
Claude Opus 584.7%81.3%estimated ± 4.4 pp, low confidence
Claude Opus 5.587.7%82.5%estimated ± 4.4 pp, low confidence
DeepSeek V4.1 Flash77.0%77.9%estimated ± 4.4 pp, medium confidence
Gemini 1.5 Pro55.0%67.2%estimated ± 4.4 pp, medium confidence
Gemini 2.5 Flash65.5%72.5%estimated ± 4.4 pp, medium confidence
Gemini 2.5 Pro74.9%76.9%estimated ± 4.4 pp, medium confidence
Gemini 3.5 Flash-Lite79.0%78.8%estimated ± 4.4 pp, medium confidence
Gemini 3.6 Flash83.2%80.6%estimated ± 4.4 pp, medium confidence
Gemini 3 Flash78.6%78.6%estimated ± 4.4 pp, medium confidence
Gemma 3 27B48.0%63.5%estimated ± 4.4 pp, low confidence
Gemma 4 E2B44.6%61.7%estimated ± 4.4 pp, low confidence
Gemma 4 E4B51.4%65.4%estimated ± 4.4 pp, low confidence
GLM-5V-Turbo72.8%75.9%estimated ± 4.4 pp, medium confidence
GPT-4.161.2%70.4%estimated ± 4.4 pp, medium confidence
GPT-4.1 mini58.7%69.1%estimated ± 4.4 pp, medium confidence
GPT-4.1 nano40.1%59.2%estimated ± 4.4 pp, low confidence
GPT-4o mini41.5%60.0%estimated ± 4.4 pp, low confidence
GPT-5.175.5%77.2%estimated ± 4.4 pp, medium confidence
GPT-5.1-Codex72.5%75.8%estimated ± 4.4 pp, medium confidence
GPT-5.1-Codex-Max72.5%75.8%estimated ± 4.4 pp, medium confidence
GPT-5.2-Codex76.3%77.5%estimated ± 4.4 pp, medium confidence
GPT-5.3 Codex78.5%78.5%estimated ± 4.4 pp, medium confidence
GPT-5 (high)74.2%76.6%estimated ± 4.4 pp, medium confidence
GPT-5 (medium)74.3%76.6%estimated ± 4.4 pp, medium confidence
GPT-6.1 Sol86.0%81.8%estimated ± 4.4 pp, low confidence
GPT-6 Luna79.7%79.1%estimated ± 4.4 pp, medium confidence
GPT-6 Sol82.9%80.5%estimated ± 4.4 pp, medium confidence
Grok 468.8%74.1%estimated ± 4.4 pp, medium confidence
Grok 4.1 Fast48.4%63.8%estimated ± 4.4 pp, low confidence
Grok 4.1 Fast (Reasoning)63.3%71.4%estimated ± 4.4 pp, medium confidence
Grok 4.580.4%79.4%estimated ± 4.4 pp, medium confidence
Grok 4 Fast (Reasoning)61.8%70.7%estimated ± 4.4 pp, medium confidence
LFM2.5-VL-1.6B-Extract26.5%51.1%estimated ± 4.4 pp, low confidence
Ling 3.0 Flash VL79.0%78.8%estimated ± 4.4 pp, medium confidence
Llama 4 Maverick62.1%70.8%estimated ± 4.4 pp, medium confidence
Llama 4 Scout52.9%66.1%estimated ± 4.4 pp, medium confidence
MiMo-V2.6-Flash73.1%76.1%estimated ± 4.4 pp, medium confidence
MiMo-V2-Omni69.9%74.6%estimated ± 4.4 pp, medium confidence
Mistral Large 355.7%67.6%estimated ± 4.4 pp, medium confidence
Mistral Large 476.4%77.6%estimated ± 4.4 pp, medium confidence
Mistral Medium 353.0%66.2%estimated ± 4.4 pp, medium confidence
Mistral Medium 3.5 128B64.9%72.2%estimated ± 4.4 pp, medium confidence
Mistral Small 456.8%68.2%estimated ± 4.4 pp, medium confidence
Mistral Small 4 (Reasoning)56.8%68.2%estimated ± 4.4 pp, medium confidence
Nova Pro44.3%61.5%estimated ± 4.4 pp, low confidence
o370.1%74.7%estimated ± 4.4 pp, medium confidence
Phi-4 Multimodal Instruct14.5%43.3%estimated ± 4.4 pp, low confidence
Qwen3.5 397B (Reasoning)52.7%66.0%estimated ± 4.4 pp, medium confidence
Qwen3.8 Max Preview82.8%80.4%estimated ± 4.4 pp, medium confidence
Qwen3-Omni-30B-A3B-Instruct55.5%67.5%estimated ± 4.4 pp, medium confidence
Qwen3-Omni-30B-A3B-Thinking60.2%69.9%estimated ± 4.4 pp, medium confidence