Vision & documents
MMMU-Pro w/ Python leaderboard
As of 2026-10-07, the highest measured score on MMMU-Pro w/ Python is 84.6% by GPT-5.6 Sol. 105 more models have estimated scores, calibrated from the benchmarks they were measured on.
Measured scores: benchlm.ai.
| # | Model | Score | Source |
|---|---|---|---|
| 1 | Claude Opus 5.5 | 86.2% | estimated ± 1.6 pp, medium confidence |
| 2 | GPT-6 Astra | 85.8% | estimated ± 1.6 pp, medium confidence |
| 3 | Gemini 3.1 Pro | 85.3% | estimated ± 0.6 pp, medium confidence |
| 4 | GPT-6.1 Sol | 85.3% | estimated ± 1.6 pp, medium confidence |
| 5 | Gemini 3.8 Flash | 85.0% | estimated ± 1.6 pp, medium confidence |
| 6 | Gemini 3.5 Flash | 85.0% | estimated ± 0.6 pp, medium confidence |
| 7 | Gemini 3.7 Flash | 85.0% | estimated ± 1.6 pp, medium confidence |
| 8 | GPT-5.6 Sol | 84.6% | measured |
| 9 | Claude Opus 5 | 84.5% | estimated ± 1.6 pp, medium confidence |
| 10 | Qwen3.8 Max | 83.7% | estimated ± 0.6 pp, high confidence |
| 11 | Gemini 3.6 Flash | 83.7% | estimated ± 1.6 pp, high confidence |
| 12 | GPT-6 Sol | 83.5% | estimated ± 1.6 pp, high confidence |
| 13 | Qwen3.8 Max Preview | 83.4% | estimated ± 1.6 pp, high confidence |
| 14 | Kimi K3 | 83.4% | measured |
| 15 | GPT-5.5 | 83.2% | measured |
| 16 | Seed 2.1 Pro | 83.0% | estimated ± 0.6 pp, high confidence |
| 17 | Gemini 3 Pro | 82.4% | estimated ± 0.6 pp, high confidence |
| 18 | GPT-5.4 | 82.1% | measured |
| 19 | GPT-5.6 Terra | 82.0% | measured |
| 20 | Grok 4.5 | 82.0% | estimated ± 1.6 pp, high confidence |
| 21 | Muse Spark | 81.7% | estimated ± 0.6 pp, high confidence |
| 22 | Qwen3.8-Flash-Next | 81.6% | estimated ± 1.6 pp, high confidence |
| 23 | GPT-6 Luna | 81.6% | estimated ± 1.6 pp, high confidence |
| 24 | Seed 2.1 Turbo | 81.4% | estimated ± 0.6 pp, high confidence |
| 25 | Apodex 1.1 | 81.3% | estimated ± 1.6 pp, high confidence |
| 26 | Apodex 1.1 Mini | 81.3% | estimated ± 1.6 pp, high confidence |
| 27 | Gemini 3.5 Flash-Lite | 81.1% | estimated ± 1.6 pp, high confidence |
| 28 | Ling 3.0 Flash VL | 81.1% | estimated ± 1.6 pp, high confidence |
| 29 | Claude Opus 4.7 (Adaptive) | 81.0% | estimated ± 1.6 pp, high confidence |
| 30 | Gemini 3 Flash | 80.9% | estimated ± 1.6 pp, high confidence |
| 31 | GPT-5.2 | 80.8% | estimated ± 0.6 pp, high confidence |
| 32 | GPT-5.3 Codex | 80.8% | estimated ± 1.6 pp, high confidence |
| 33 | dots3-note Preview | 80.4% | estimated ± 0.6 pp, high confidence |
| 34 | Qwen3.5 397B | 80.3% | estimated ± 0.6 pp, high confidence |
| 35 | Qwen3.7 Plus | 80.3% | estimated ± 0.6 pp, high confidence |
| 36 | Qwen3.6 Plus | 80.1% | estimated ± 0.6 pp, high confidence |
| 37 | Kimi K2.6 | 80.1% | measured |
| 38 | Claude Sonnet 5 | 80.1% | estimated ± 1.6 pp, high confidence |
| 39 | DeepSeek V4.1 Flash | 79.9% | estimated ± 1.6 pp, high confidence |
| 40 | Kimi K2.5 | 79.8% | estimated ± 0.6 pp, high confidence |
| 41 | Kimi K2.5 (Reasoning) | 79.8% | estimated ± 0.6 pp, high confidence |
| 42 | Claude Opus 4.7 | 79.5% | estimated ± 1.6 pp, high confidence |
| 43 | Mistral Large 4 | 79.5% | estimated ± 1.6 pp, high confidence |
| 44 | GPT-5.6 Luna | 79.5% | measured |
| 45 | GPT-5.2-Codex | 79.5% | estimated ± 1.6 pp, high confidence |
| 46 | Qwen3.8-27B | 79.5% | estimated ± 1.6 pp, high confidence |
| 47 | Grok 4.3 | 79.5% | estimated ± 0.6 pp, high confidence |
| 48 | MiniMax M3 | 79.5% | estimated ± 0.6 pp, high confidence |
| 49 | Pareto 26.9 | 79.4% | estimated ± 0.6 pp, high confidence |
| 50 | MiMo-V2.5 | 79.3% | estimated ± 0.6 pp, high confidence |
| 51 | GPT-5.1 | 79.0% | estimated ± 1.6 pp, high confidence |
| 52 | Claude Opus 4.6 (Adaptive) | 78.9% | estimated ± 1.6 pp, high confidence |
| 53 | Step 3.7 Flash | 78.8% | estimated ± 1.6 pp, high confidence |
| 54 | Claude Opus 4.6 | 78.7% | estimated ± 0.6 pp, high confidence |
| 55 | Qwen3.5-122B-A10B | 78.7% | estimated ± 1.6 pp, high confidence |
| 56 | Qwen3.5-27B | 78.7% | estimated ± 1.6 pp, high confidence |
| 57 | Gemini 2.5 Pro | 78.6% | estimated ± 1.6 pp, high confidence |
| 58 | Gemma 4 31B | 78.3% | estimated ± 0.6 pp, high confidence |
| 59 | GPT-5 (medium) | 78.2% | estimated ± 1.6 pp, high confidence |
| 60 | GPT-5 (high) | 78.1% | estimated ± 1.6 pp, high confidence |
| 61 | Claude Opus 4.5 Thinking | 78.0% | estimated ± 1.6 pp, high confidence |
| 62 | GPT-5.4 mini | 78.0% | measured |
| 63 | Step 5 Preview | 77.4% | estimated ± 0.6 pp, high confidence |
| 64 | MiMo-V2.6-Flash | 77.4% | estimated ± 1.6 pp, high confidence |
| 65 | Qwen3.6-27B | 77.2% | estimated ± 0.6 pp, high confidence |
| 66 | GLM-5V-Turbo | 77.2% | estimated ± 1.6 pp, high confidence |
| 67 | Qwen3.5-35B-A3B | 77.2% | estimated ± 1.6 pp, high confidence |
| 68 | GPT-5.1-Codex | 77.0% | estimated ± 1.6 pp, high confidence |
| 69 | GPT-5.1-Codex-Max | 77.0% | estimated ± 1.6 pp, high confidence |
| 70 | Qwen3.6-35B-A3B | 76.8% | estimated ± 0.6 pp, high confidence |
| 71 | Grok 4.20 | 76.7% | estimated ± 0.6 pp, high confidence |
| 72 | Claude Sonnet 4.6 | 75.8% | estimated ± 1.6 pp, high confidence |
| 73 | Inkling-Small | 75.6% | estimated ± 0.6 pp, high confidence |
| 74 | Muse Glimmer 30B | 75.6% | estimated ± 0.6 pp, high confidence |
| 75 | o3 | 75.5% | estimated ± 1.6 pp, high confidence |
| 76 | Gemma 4 26B A4B | 75.4% | estimated ± 0.6 pp, high confidence |
| 77 | MiMo-V2-Omni | 75.3% | estimated ± 1.6 pp, high confidence |
| 78 | Inkling | 75.1% | estimated ± 0.6 pp, high confidence |
| 79 | Grok 4 | 74.6% | estimated ± 1.6 pp, high confidence |
| 80 | Claude 4.1 Opus Thinking | 74.0% | estimated ± 1.6 pp, high confidence |
| 81 | Interfaze Beta | 73.1% | estimated ± 0.6 pp, high confidence |
| 82 | Claude Opus 4.5 | 72.7% | estimated ± 0.6 pp, high confidence |
| 83 | Gemini 2.5 Flash | 72.3% | estimated ± 1.6 pp, high confidence |
| 84 | Mistral Medium 3.5 128B | 71.9% | estimated ± 1.6 pp, medium confidence |
| 85 | Gemma 4 12B | 71.5% | estimated ± 0.6 pp, high confidence |
| 86 | Grok 4.1 Fast (Reasoning) | 70.7% | estimated ± 1.6 pp, medium confidence |
| 87 | Claude 4 Sonnet | 70.1% | estimated ± 1.6 pp, medium confidence |
| 88 | Llama 4 Maverick | 69.8% | estimated ± 1.6 pp, medium confidence |
| 89 | Grok 4 Fast (Reasoning) | 69.6% | estimated ± 1.6 pp, medium confidence |
| 90 | GPT-5.4 nano | 69.5% | measured |
| 91 | GPT-4.1 | 69.2% | estimated ± 1.6 pp, medium confidence |
| 92 | Qwen3-Omni-30B-A3B-Thinking | 68.4% | estimated ± 1.6 pp, medium confidence |
| 93 | Command A+ | 67.5% | estimated ± 0.6 pp, medium confidence |
| 94 | GPT-4.1 mini | 67.3% | estimated ± 1.6 pp, medium confidence |
| 95 | Mistral Small 4 | 65.8% | estimated ± 1.6 pp, medium confidence |
| 96 | Mistral Small 4 (Reasoning) | 65.8% | estimated ± 1.6 pp, medium confidence |
| 97 | Mistral Large 3 | 65.0% | estimated ± 1.6 pp, medium confidence |
| 98 | Qwen3-Omni-30B-A3B-Instruct | 64.8% | estimated ± 1.6 pp, medium confidence |
| 99 | Gemini 1.5 Pro | 64.4% | estimated ± 1.6 pp, medium confidence |
| 100 | Nemotron 3 Nano Omni 30B A3B | 63.0% | estimated ± 1.6 pp, medium confidence |
| 101 | Mistral Medium 3 | 62.8% | estimated ± 1.6 pp, medium confidence |
| 102 | Llama 4 Scout | 62.7% | estimated ± 1.6 pp, medium confidence |
| 103 | Qwen3.5 397B (Reasoning) | 62.6% | estimated ± 1.6 pp, medium confidence |
| 104 | Gemma 4 E4B | 61.5% | estimated ± 1.6 pp, medium confidence |
| 105 | LFM2.5-VL-3B | 60.9% | estimated ± 0.6 pp, medium confidence |
| 106 | Grok 4.1 Fast | 59.0% | estimated ± 1.6 pp, medium confidence |
| 107 | Gemma 3 27B | 58.6% | estimated ± 1.6 pp, medium confidence |
| 108 | Gemma 4 E2B | 55.6% | estimated ± 1.6 pp, medium confidence |
| 109 | Nova Pro | 55.4% | estimated ± 1.6 pp, medium confidence |
| 110 | GPT-4o mini | 52.8% | estimated ± 1.6 pp, medium confidence |
| 111 | GPT-4.1 nano | 51.5% | estimated ± 1.6 pp, medium confidence |
| 112 | Claude 3 Haiku | 42.0% | estimated ± 1.6 pp, medium confidence |
| 113 | LFM2.5-VL-1.6B-Extract | 37.3% | estimated ± 1.6 pp, medium confidence |
| 114 | Phi-4 Multimodal Instruct | 22.3% | estimated ± 1.6 pp, medium confidence |
All leaderboards
Agentic · terminal
- AA Terminal-Bench 2.1
- AA Terminal-Bench 4.0
- Terminal-Bench 2.0
- Terminal-Bench 3.0
- Terminal-Bench 4.0
- Terminal-Bench-Science 0.1
- Terminal-Bench 2.1
- Terminal-Bench 2.1 (Vals AI)
Agentic · tools
- AA Agentic Index
- AA-AnalystAgent
- AA AutomationBench
- AA EnterpriseOps-Gym
- GDP.pdf
- AA Harvey LAB
- AA ITBench
- AA Tau3 Banking
- Agents' Last Exam
- APEX-Agents
- APEX-Agents-AA
- ApprenticeBench
- AutomationBench
- BFCL v4
- BrowseComp
- Claw-Eval
- CWE-bench v1
- CyberGym
- DeepPlanning
- DeepSearchQA
- DRACO
- ExploitGym
- GDPval-AA
- Gert Labs
- HLE w/ tools
- JobBench
- MCP Atlas
- MCP-Tasks
- OSWorld-Verified
- OSWorld 2.0
- QwenClawBench
- ResearchClawBench
- SkillsBench
- τ²-bench results
- τ³-bench results
- Toolathlon
- Toolathlon-Verified
- VITA-Bench
- WideResearch
Coding
- AA Coding Index
- AA-SciCode
- CursorBench 3.1
- CursorBench 3.2
- CursorBench 4.0
- DeepSWE
- FrontierCode 1.1 Main
- FrontierCode 1.1 Extended
- FrontierSWE v2
- LiveCodeBench
- LiveCodeBench Pro
- LiveCodeBench v6
- NL2Repo
- OpenHarmony Bench
- PostTrainBench v1.1
- ProgramBench
- React Native Evals
- SciCode
- SWE-bench Pro
- SWE-bench Verified
- SWE-Rebench
- Vals LiveCodeBench
- Vals SWE-bench
- Vibe Code Bench
- VulcanBench v3
Math
- AIME 2025
- AIME26
- FrontierMath (legacy)
- FrontierMath v2 (Tier 4)
- FrontierMath v2 (Tiers 1-3)
- HMMT Feb 2025
- HMMT Feb 2026
- HMMT Nov 2025
- IMOAnswerBench
- MATH-500
- MMAnswerBench
Knowledge & reasoning
- AA-GPQA Diamond
- AA-HLE
- ARC-AGI-2
- ARC-AGI-1
- ARC-AGI-3
- Artificial Analysis Intelligence Index
- BioMysteryBench (human-difficult)
- BioMysteryBench (human-solvable)
- C-Eval
- CritPt
- GPQA
- GPQA Diamond
- HealthBench (raw)
- HealthBench Hard
- HealthBench (length-adjusted)
- HealthBench Professional
- HealthBench Professional (raw)
- HLE
- HLE w/o tools
- HLE-Verified
- JevBench 1.4
- LABBench2
- MedXpertQA (Text)
- MMLU
- MMLU-Pro
- MMLU-Pro (Arcee)
- MMLU-Redux
- MMMLU
- AA-Omniscience Accuracy
- SuperGPQA
- Vals GPQA Diamond
- Vals MMLU-Pro
Instruction following
Multilingual
Vision & documents
- AA-MMMU-Pro
- BabyVision
- CharXiv
- CharXiv w/o tools
- ERQA
- MathVision
- MathVision w/ Python
- MedXpertQA (MM)
- MMMU
- MMMU-Pro
- MMMU-Pro w/ Python
- MMVU
- OfficeQA Pro
- OmniDocBench 1.5
- RealWorldQA
- RefCOCO (avg)
- ScreenSpot Pro
- SimpleVQA
- Video-MME (with subtitle)
- VideoMMMU
- V*
- ZeroBench