MMMU-Pro
Harder MMMU: college-level multimodal questions with more options and vision-only inputs to remove text shortcuts.
Variant (standard vs vision, 4 vs 10 options) often unstated in cards.
- Made by
- MMMU team
- Released
- September 2024
- Kind
- General visual questions
- Level
- University
- Scored
- Checked automatically
- Answers
- Multiple choice
- Tasks
- All public
- Strongest model tested
- GPT-5.6 Sol #13 on the capability index
- Last in a launch post
- November 2026
- Last model added
- November 2026
- Scores refreshed
- November 12th, 2026
In the authors’ words
This paper introduces MMMU-Pro, a robust version of the Massive Multi-discipline Multimodal Understanding and Reasoning (MMMU) benchmark. MMMU-Pro rigorously assesses multimodal models' true understanding and reasoning capabilities through a three-step process based on MMMU: (1) filtering out questions answerable by text-only models, (2) augmenting candidate options, and (3) introducing a vision-only input setting where questions are embedded within images. This setting challenges AI to truly "see" and "read" simultaneously, testing a fundamental human cognitive skill of seamlessly integrating visual and textual information. Results show that model performance is substantially lower on MMMU-Pro than on MMMU, ranging from 16.8% to 26.9% across models. We explore the impact of OCR prompts and Chain of Thought (CoT) reasoning, finding that OCR prompts have minimal effect while CoT generally improves performance. MMMU-Pro provides a more rigorous evaluation tool, closely mimicking real-world scenarios and offering valuable directions for future research in multimodal AI.
GPT-5.6 Sol leads with 84.6%
Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.
GPT-5.4 leads with 82.1% across all independent runs
Best score per model across the official leaderboard, Epoch AI’s own runs and any board Epoch AI copied. Each bar and row names its source.
GPT-5.6 Sol leads with 84.6%, claims included
Best score per model from every source, including labs’ own numbers and claims Epoch AI collected from reports and papers. Labs pick their own settings, so a claim can beat an independent run of the same model.
- 84.6 GPT-5.6 Sol
- 84.1 Kimi K3.1 Pro
- 83.6
Gemini 3.5 Flash
- 83.2 GPT-5.5
- 82.7
Seed2.1 Pro
- 82.7
Qwen3.8 Max (0902)
- 82.3
Qwen 3.8 Max
- 82.0 GPT-5.6 Terra
- 81.7
Intern-S2-397B
- 81.6 Kimi K3
- 81.6
Inkling 2 Small
- 81.5
Gemini 3 Deep Think
- 81.2
Gemini 3 Flash
- 81.2 GPT-5.4
- 81.0
Gemini 3 Pro
- 80.5
Gemini 3.1 Pro
- 80.4
Muse Spark
- 79.5 GPT-5.6 Luna
- 79.4 Kimi K2.6
- 79.0
Qwen3.5 397B-A17B
- 79.0
Qwen3.7-Plus
- 78.8
Qwen 3.6 Plus
- 78.5 Kimi K2.5
- 78.4 GPT-5
- 78.4
Seed2.0 Lite (0428)
- 78.2
Seed2.0 Pro
- 78.1
MiniMax-M3
- 78.0 GPT-5.4 Mini
- 77.9 MiMo-V2.5
- 77.3 Claude Opus 4.6
- 76.9
Qwen3.5-122B-A10B
- 76.9
Gemma 4 31B IT
- 76.8
Gemini 3.1 Flash-Lite
- 76.8 MiMo-V2-Omni
- 76.0 GPT-5.5 Instant
- 76.0
Step 5 Preview
- 75.8
Qwen3.6 27B
- 75.6 Claude Sonnet 4.6
- 75.3
Qwen 3.6 35B-A3B
- 75.1
Qwen3.5-35B-A3B
- 75.0
Qwen3.5-27B
- 74.1 GPT-5 mini
- 74.0
Inkling-Small
- 74.0
Muse Glimmer
- 73.9
Qwen3.5-Omni-Plus
- 73.8
Gemma 4 26B A4B
- 73.5
Inkling
- 73.2
Seed1.8
- 72.8
Intern-S1-Pro
- 70.1
Qwen3.5-9B
- 69.5 GPT-5.4 Nano
- 69.3
Qwen3-VL-235B-A22B
- 69.1
Gemma 4 12B
- 68.6
ERNIE 5.0
- 68.6
EXAONE 4.5 33B
- 67.6
Seed1.5-VL
- 66.4
Seed1.6-Thinking
- 66.3
Qwen3.5-4B
- 66.0 GLM-4.6V
- 65.2 GLM-4.5V
- 64.1
STEP3-VL-10B
- 63.5
Nova 2.0 Pro Preview
- 63.0
Command A+
- 62.6 GPT-5 nano
- 61.8
Nova 2 Lite
- 61.4
Nova 2 Omni Preview
- 60.0
Mistral Small 4
- 59.6
Llama 4 Maverick
- 57.9
Magistral Medium 1.0
- 57.1 GLM-4.1V-9B-Thinking
- 57.0
Qwen3-Omni-30B-A3B
- 56.5
DeepSeek V4.1 Flash
- 56.5
DeepSeek-V4.1-Flash Base
- 54.3
DiffusionGemma 26B A4B
- 52.6
Gemma 4 E4B
- 52.2
Llama 4 Scout
- 51.8
Magistral Small 1.0
- 51.1
Qwen2.5-VL-72B
- 50.3
Qwen3.5-2B
- 49.3
Mistral Small 3.1
- 46.3 Kimi-VL-A3B-Thinking-2506
- 44.2
Gemma 4 E2B
- 42.0
Nemotron 3.5 Bolt E4B
- 41.1
Cosmos3-Nano
- 38.5
Phi-4-multimodal
- 36.6
Qwen2.5-Omni-7B
- 31.2
Qwen3.5-0.8B
- 30.5 LFM2.5-VL-3B
- 28.0
Nemotron Nano 12B v2 VL
- 26.4
Cosmos3-Edge
- 1 GPT-5.6 Sol 84.6%
- 2 Kimi K3.1 Pro 84.1%
- 3
Gemini 3.5 Flash 83.6%
- 4 GPT-5.5 83.2%
- 5
Seed2.1 Pro 82.7%
- 6
Qwen3.8 Max (0902) 82.7%
- 7
Qwen 3.8 Max 82.3%
- 8 GPT-5.6 Terra 82%
- 9
Intern-S2-397B 81.7%
- 10 Kimi K3 81.6%
- 11
Inkling 2 Small 81.6%
- 12
Gemini 3 Deep Think 81.5%
- 13
Gemini 3 Flash 81.2%
- 14 GPT-5.4 81.2%
- 15
Gemini 3 Pro 81%
- 16
Gemini 3.1 Pro 80.5%
- 17
Muse Spark 80.4%
- 18 GPT-5.6 Luna 79.5%
- 19 Kimi K2.6 79.4%
- 20
Qwen3.5 397B-A17B 79%
- 21
Qwen3.7-Plus 79%
- 22
Qwen 3.6 Plus 78.8%
- 23 Kimi K2.5 78.5%
- 24 GPT-5 78.4%
- 25
Seed2.0 Lite (0428) 78.4%
- 26
Seed2.0 Pro 78.2%
- 27
MiniMax-M3 78.1%
- 28 GPT-5.4 Mini 78%
- 29 MiMo-V2.5 77.9%
- 30 Claude Opus 4.6 77.3%
- 31
Qwen3.5-122B-A10B 76.9%
- 32
Gemma 4 31B IT 76.9%
- 33
Gemini 3.1 Flash-Lite 76.8%
- 34 MiMo-V2-Omni 76.8%
- 35 GPT-5.5 Instant 76%
- 36
Step 5 Preview 76%
- 37
Qwen3.6 27B 75.8%
- 38 Claude Sonnet 4.6 75.6%
- 39
Qwen 3.6 35B-A3B 75.3%
- 40
Qwen3.5-35B-A3B 75.1%
- 41
Qwen3.5-27B 75%
- 42 GPT-5 mini 74.1%
- 43
Inkling-Small 74%
- 44
Muse Glimmer 74%
- 45
Qwen3.5-Omni-Plus 73.9%
- 46
Gemma 4 26B A4B 73.8%
- 47
Inkling 73.5%
- 48
Seed1.8 73.2%
- 49
Intern-S1-Pro 72.8%
- 50
Qwen3.5-9B 70.1%
- 51 GPT-5.4 Nano 69.5%
- 52
Qwen3-VL-235B-A22B 69.3%
- 53
Gemma 4 12B 69.1%
- 54
ERNIE 5.0 68.6%
- 55
EXAONE 4.5 33B 68.6%
- 56
Seed1.5-VL 67.6%
- 57
Seed1.6-Thinking 66.4%
- 58
Qwen3.5-4B 66.3%
- 59 GLM-4.6V 66%
- 60 GLM-4.5V 65.2%
- 61
STEP3-VL-10B 64.1%
- 62
Nova 2.0 Pro Preview 63.5%
- 63
Command A+ 63%
- 64 GPT-5 nano 62.6%
- 65
Nova 2 Lite 61.8%
- 66
Nova 2 Omni Preview 61.4%
- 67
Mistral Small 4 60%
- 68
Llama 4 Maverick 59.6%
- 69
Magistral Medium 1.0 57.9%
- 70 GLM-4.1V-9B-Thinking 57.1%
- 71
Qwen3-Omni-30B-A3B 57%
- 72
DeepSeek V4.1 Flash 56.5%
- 73
DeepSeek-V4.1-Flash Base 56.5%
- 74
DiffusionGemma 26B A4B 54.3%
- 75
Gemma 4 E4B 52.6%
- 76
Llama 4 Scout 52.2%
- 77
Magistral Small 1.0 51.8%
- 78
Qwen2.5-VL-72B 51.1%
- 79
Qwen3.5-2B 50.3%
- 80
Mistral Small 3.1 49.3%
- 81 Kimi-VL-A3B-Thinking-2506 46.3%
- 82
Gemma 4 E2B 44.2%
- 83
Nemotron 3.5 Bolt E4B 42%
- 84
Cosmos3-Nano 41.1%
- 85
Phi-4-multimodal 38.5%
- 86
Qwen2.5-Omni-7B 36.6%
- 87
Qwen3.5-0.8B 31.2%
- 88 LFM2.5-VL-3B 30.5%
- 89
Nemotron Nano 12B v2 VL 28%
- 90
Cosmos3-Edge 26.4%
Source: Labs’ model cards
- 82.1 GPT-5.4
- 81.0
Gemini 3 Pro
- 80.5
Gemini 3.1 Pro
- 80.4 GPT-5.2
- 80.4
Muse Spark
- 79.0 GPT-5.1
- 78.4 GPT-5
- 77.3 Claude Opus 4.6
- 76.9
Gemma 4 31B IT
- 76.4 o3
- 75.6 Claude Sonnet 4.6
- 73.9 Claude Opus 4.5
- 73.8
Gemma 4 26B A4B
- 70.1 dots.vlm1
- 68.9 Claude Sonnet 4.5
- 68.1
Qwen3-VL-235B-A22B
- 68.0
Gemini 2.5 Pro
- 67.6
Seed1.5-VL
- 66.4
Seed1.6-Thinking
- 65.2 GLM-4.5V
- 57.1 GLM-4.1V-9B-Thinking
- 55.4
Skywork-R1V3-38B
- 52.6
Gemma 4 E4B
- 51.9 GPT-4o
- 51.5 Claude 3.5 Sonnet
- 48.6
InternVL2_5-78B
- 46.2 Qwen2-VL-72B-Instruct
- 46.2
Qwen2.5-VL-72B
- 46.0
InternVL2.5-38B
- 44.2
Gemma 4 E2B
- 43.5
Gemini 1.5 Pro
- 43.3 MiMo-VL-7B-RL
- 42.3 MiMo-VL-7B-SFT
- 40.0
InternVL2-Llama3-76B
- 39.5
Llama 3.2 90B
- 38.3
Qwen2.5-VL-7B
- 37.6 GPT-4o mini
- 37.1
InternVL2.5-26B
- 34.3
InternVL2.5-8B
- 34.2
InternVL2-40B
- 31.6
Qwen2.5-VL-3B
- 31.0 LLaVA-OneVision 72B
- 29.0
InternVL2-8B
- 28.4
Llama 3.2 11B
- 27.2 MiniCPM-V-2_6
- 25.3
MAmmoTH-VL-8B
- 25.1
LLaVA-NeXT-72B
- 24.1
LLaVA-OneVision 7B
- 23.8
LLaVA-v1.6-34B
- 23.7
InternVL2.5-2B
- 22.9
Idefics3-8B-Llama3
- 19.7 Phi-3.5-vision-instruct
- 19.6
MiniCPM-Llama3-V 2.5
- 19.4
InternVL2.5-1B
- 17.2 llava-v1.6-vicuna-13b
- 17.0 llava-v1.6-mistral-7b
- 16.1 llava-v1.6-vicuna-7b
- 1 GPT-5.4 thinking, with tools 82.1%
- 2
Gemini 3 Pro 81%
- 3
Gemini 3.1 Pro thinking, high 80.5%
- 4 GPT-5.2 thinking, no python 80.4%
- 5
Muse Spark thinking 80.4%
- 6 GPT-5.1 thinking 79%
- 7 GPT-5 thinking 78.4%
- 8 Claude Opus 4.6 with tools 77.3%
- 9
Gemma 4 31B IT 76.9%
- 10 o3 76.4%
- 11 Claude Sonnet 4.6 with tools 75.6%
- 12 Claude Opus 4.5 73.9%
- 13
Gemma 4 26B A4B 73.8%
- 14 dots.vlm1 70.1%
- 15 Claude Sonnet 4.5 68.9%
- 16
Qwen3-VL-235B-A22B 68.1%
- 17
Gemini 2.5 Pro May 2025 68%
- 18
Seed1.5-VL thinking 67.6%
- 19
Seed1.6-Thinking 66.4%
- 20 GLM-4.5V thinking 65.2%
- 21 GLM-4.1V-9B-Thinking thinking 57.1%
- 22
Skywork-R1V3-38B 55.4%
- 23
Gemma 4 E4B 52.6%
- 24 GPT-4o May 2024 51.9%
- 25 Claude 3.5 Sonnet 51.5%
- 26
InternVL2_5-78B 48.6%
- 27 Qwen2-VL-72B-Instruct 46.2%
- 28
Qwen2.5-VL-72B 46.2%
- 29
InternVL2.5-38B 46%
- 30
Gemma 4 E2B 44.2%
- 31
Gemini 1.5 Pro May 2024 43.5%
- 32 MiMo-VL-7B-RL 43.3%
- 33 MiMo-VL-7B-SFT 42.3%
- 34
InternVL2-Llama3-76B 40%
- 35
Llama 3.2 90B 39.5%
- 36
Qwen2.5-VL-7B 38.3%
- 37 GPT-4o mini 37.6%
- 38
InternVL2.5-26B 37.1%
- 39
InternVL2.5-8B 34.3%
- 40
InternVL2-40B 34.2%
- 41
Qwen2.5-VL-3B 31.6%
- 42 LLaVA-OneVision 72B 31%
- 43
InternVL2-8B 29%
- 44
Llama 3.2 11B 28.4%
- 45 MiniCPM-V-2_6 27.2%
- 46
MAmmoTH-VL-8B 25.3%
- 47
LLaVA-NeXT-72B 25.1%
- 48
LLaVA-OneVision 7B 24.1%
- 49
LLaVA-v1.6-34B 23.8%
- 50
InternVL2.5-2B 23.7%
- 51
Idefics3-8B-Llama3 22.9%
- 52 Phi-3.5-vision-instruct 19.7%
- 53
MiniCPM-Llama3-V 2.5 19.6%
- 54
InternVL2.5-1B 19.4%
- 55 llava-v1.6-vicuna-13b 17.2%
- 56 llava-v1.6-mistral-7b 17%
- 57 llava-v1.6-vicuna-7b 16.1%
Source: Official MMMU-Pro leaderboard
- 84.6 GPT-5.6 Sol
- 84.1 Kimi K3.1 Pro
- 83.6
Gemini 3.5 Flash
- 83.2 GPT-5.5
- 82.7
Seed2.1 Pro
- 82.7
Qwen3.8 Max (0902)
- 82.3
Qwen 3.8 Max
- 82.1 GPT-5.4
- 82.0 GPT-5.6 Terra
- 81.7
Intern-S2-397B
- 81.6 Kimi K3
- 81.6
Inkling 2 Small
- 81.5
Gemini 3 Deep Think
- 81.2
Gemini 3 Flash
- 81.0
Gemini 3 Pro
- 80.5
Gemini 3.1 Pro
- 80.4 GPT-5.2
- 80.4
Muse Spark
- 79.5 GPT-5.6 Luna
- 79.4 Kimi K2.6
- 79.0 GPT-5.1
- 79.0
Qwen3.5 397B-A17B
- 79.0
Qwen3.7-Plus
- 78.8
Qwen 3.6 Plus
- 78.5 Kimi K2.5
- 78.4 GPT-5
- 78.4
Seed2.0 Lite (0428)
- 78.2
Seed2.0 Pro
- 78.1
MiniMax-M3
- 78.0 GPT-5.4 Mini
- 77.9 MiMo-V2.5
- 77.3 Claude Opus 4.6
- 76.9
Qwen3.5-122B-A10B
- 76.9
Gemma 4 31B IT
- 76.8
Gemini 3.1 Flash-Lite
- 76.8 MiMo-V2-Omni
- 76.4 o3
- 76.0 GPT-5.5 Instant
- 76.0
Step 5 Preview
- 75.8
Qwen3.6 27B
- 75.6 Claude Sonnet 4.6
- 75.3
Qwen 3.6 35B-A3B
- 75.1
Qwen3.5-35B-A3B
- 75.0
Qwen3.5-27B
- 74.1 GPT-5 mini
- 74.0
Inkling-Small
- 74.0
Muse Glimmer
- 73.9 Claude Opus 4.5
- 73.9
Qwen3.5-Omni-Plus
- 73.8
Gemma 4 26B A4B
- 73.5
Inkling
- 73.2
Seed1.8
- 72.8
Intern-S1-Pro
- 70.1 dots.vlm1
- 70.1
Qwen3.5-9B
- 69.5 GPT-5.4 Nano
- 69.3
Qwen3-VL-235B-A22B
- 69.1
Gemma 4 12B
- 68.9 Claude Sonnet 4.5
- 68.6
ERNIE 5.0
- 68.6
EXAONE 4.5 33B
- 68.0
Gemini 2.5 Pro
- 67.6
Seed1.5-VL
- 66.4
Seed1.6-Thinking
- 66.3
Qwen3.5-4B
- 66.0 GLM-4.6V
- 65.2 GLM-4.5V
- 64.1
STEP3-VL-10B
- 63.5
Nova 2.0 Pro Preview
- 63.0
Command A+
- 62.6 GPT-5 nano
- 61.8
Nova 2 Lite
- 61.4
Nova 2 Omni Preview
- 60.0
Mistral Small 4
- 59.6
Llama 4 Maverick
- 57.9
Magistral Medium 1.0
- 57.1 GLM-4.1V-9B-Thinking
- 57.0
Qwen3-Omni-30B-A3B
- 56.5
DeepSeek V4.1 Flash
- 56.5
DeepSeek-V4.1-Flash Base
- 55.4
Skywork-R1V3-38B
- 54.3
DiffusionGemma 26B A4B
- 52.6
Gemma 4 E4B
- 52.2
Llama 4 Scout
- 51.9 GPT-4o
- 51.8
Magistral Small 1.0
- 51.5 Claude 3.5 Sonnet
- 51.1
Qwen2.5-VL-72B
- 50.3
Qwen3.5-2B
- 49.3
Mistral Small 3.1
- 48.6
InternVL2_5-78B
- 46.3 Kimi-VL-A3B-Thinking-2506
- 46.2 Qwen2-VL-72B-Instruct
- 46.0
InternVL2.5-38B
- 44.2
Gemma 4 E2B
- 43.5
Gemini 1.5 Pro
- 43.3 MiMo-VL-7B-RL
- 42.3 MiMo-VL-7B-SFT
- 42.0
Nemotron 3.5 Bolt E4B
- 41.1
Cosmos3-Nano
- 40.0
InternVL2-Llama3-76B
- 39.5
Llama 3.2 90B
- 38.5
Phi-4-multimodal
- 38.3
Qwen2.5-VL-7B
- 37.6 GPT-4o mini
- 37.1
InternVL2.5-26B
- 36.6
Qwen2.5-Omni-7B
- 34.3
InternVL2.5-8B
- 34.2
InternVL2-40B
- 31.6
Qwen2.5-VL-3B
- 31.2
Qwen3.5-0.8B
- 31.0 LLaVA-OneVision 72B
- 30.5 LFM2.5-VL-3B
- 29.0
InternVL2-8B
- 28.4
Llama 3.2 11B
- 28.0
Nemotron Nano 12B v2 VL
- 27.2 MiniCPM-V-2_6
- 26.4
Cosmos3-Edge
- 25.3
MAmmoTH-VL-8B
- 25.1
LLaVA-NeXT-72B
- 24.1
LLaVA-OneVision 7B
- 23.8
LLaVA-v1.6-34B
- 23.7
InternVL2.5-2B
- 22.9
Idefics3-8B-Llama3
- 19.7 Phi-3.5-vision-instruct
- 19.6
MiniCPM-Llama3-V 2.5
- 19.4
InternVL2.5-1B
- 17.2 llava-v1.6-vicuna-13b
- 17.0 llava-v1.6-mistral-7b
- 16.1 llava-v1.6-vicuna-7b
- 1 GPT-5.6 Sol 84.6%
- 2 Kimi K3.1 Pro 84.1%
- 3
Gemini 3.5 Flash 83.6%
- 4 GPT-5.5 83.2%
- 5
Seed2.1 Pro 82.7%
- 6
Qwen3.8 Max (0902) 82.7%
- 7
Qwen 3.8 Max 82.3%
- 8 GPT-5.4 thinking, with tools 82.1%
- 9 GPT-5.6 Terra 82%
- 10
Intern-S2-397B 81.7%
- 11 Kimi K3 81.6%
- 12
Inkling 2 Small 81.6%
- 13
Gemini 3 Deep Think 81.5%
- 14
Gemini 3 Flash 81.2%
- 15
Gemini 3 Pro 81%
- 16
Gemini 3.1 Pro thinking, high 80.5%
- 17 GPT-5.2 thinking, no python 80.4%
- 18
Muse Spark thinking 80.4%
- 19 GPT-5.6 Luna 79.5%
- 20 Kimi K2.6 79.4%
- 21 GPT-5.1 thinking 79%
- 22
Qwen3.5 397B-A17B 79%
- 23
Qwen3.7-Plus 79%
- 24
Qwen 3.6 Plus 78.8%
- 25 Kimi K2.5 78.5%
- 26 GPT-5 thinking 78.4%
- 27
Seed2.0 Lite (0428) 78.4%
- 28
Seed2.0 Pro 78.2%
- 29
MiniMax-M3 78.1%
- 30 GPT-5.4 Mini 78%
- 31 MiMo-V2.5 77.9%
- 32 Claude Opus 4.6 with tools 77.3%
- 33
Qwen3.5-122B-A10B 76.9%
- 34
Gemma 4 31B IT 76.9%
- 35
Gemini 3.1 Flash-Lite 76.8%
- 36 MiMo-V2-Omni 76.8%
- 37 o3 76.4%
- 38 GPT-5.5 Instant 76%
- 39
Step 5 Preview 76%
- 40
Qwen3.6 27B 75.8%
- 41 Claude Sonnet 4.6 with tools 75.6%
- 42
Qwen 3.6 35B-A3B 75.3%
- 43
Qwen3.5-35B-A3B 75.1%
- 44
Qwen3.5-27B 75%
- 45 GPT-5 mini 74.1%
- 46
Inkling-Small 74%
- 47
Muse Glimmer 74%
- 48 Claude Opus 4.5 73.9%
- 49
Qwen3.5-Omni-Plus 73.9%
- 50
Gemma 4 26B A4B 73.8%
- 51
Inkling 73.5%
- 52
Seed1.8 73.2%
- 53
Intern-S1-Pro 72.8%
- 54 dots.vlm1 70.1%
- 55
Qwen3.5-9B 70.1%
- 56 GPT-5.4 Nano 69.5%
- 57
Qwen3-VL-235B-A22B 69.3%
- 58
Gemma 4 12B 69.1%
- 59 Claude Sonnet 4.5 68.9%
- 60
ERNIE 5.0 68.6%
- 61
EXAONE 4.5 33B 68.6%
- 62
Gemini 2.5 Pro May 2025 68%
- 63
Seed1.5-VL thinking 67.6%
- 64
Seed1.6-Thinking 66.4%
- 65
Qwen3.5-4B 66.3%
- 66 GLM-4.6V 66%
- 67 GLM-4.5V thinking 65.2%
- 68
STEP3-VL-10B 64.1%
- 69
Nova 2.0 Pro Preview 63.5%
- 70
Command A+ 63%
- 71 GPT-5 nano 62.6%
- 72
Nova 2 Lite 61.8%
- 73
Nova 2 Omni Preview 61.4%
- 74
Mistral Small 4 60%
- 75
Llama 4 Maverick 59.6%
- 76
Magistral Medium 1.0 57.9%
- 77 GLM-4.1V-9B-Thinking thinking 57.1%
- 78
Qwen3-Omni-30B-A3B 57%
- 79
DeepSeek V4.1 Flash 56.5%
- 80
DeepSeek-V4.1-Flash Base 56.5%
- 81
Skywork-R1V3-38B 55.4%
- 82
DiffusionGemma 26B A4B 54.3%
- 83
Gemma 4 E4B 52.6%
- 84
Llama 4 Scout 52.2%
- 85 GPT-4o May 2024 51.9%
- 86
Magistral Small 1.0 51.8%
- 87 Claude 3.5 Sonnet 51.5%
- 88
Qwen2.5-VL-72B 51.1%
- 89
Qwen3.5-2B 50.3%
- 90
Mistral Small 3.1 49.3%
- 91
InternVL2_5-78B 48.6%
- 92 Kimi-VL-A3B-Thinking-2506 46.3%
- 93 Qwen2-VL-72B-Instruct 46.2%
- 94
InternVL2.5-38B 46%
- 95
Gemma 4 E2B 44.2%
- 96
Gemini 1.5 Pro May 2024 43.5%
- 97 MiMo-VL-7B-RL 43.3%
- 98 MiMo-VL-7B-SFT 42.3%
- 99
Nemotron 3.5 Bolt E4B 42%
- 100
Cosmos3-Nano 41.1%
- 101
InternVL2-Llama3-76B 40%
- 102
Llama 3.2 90B 39.5%
- 103
Phi-4-multimodal 38.5%
- 104
Qwen2.5-VL-7B 38.3%
- 105 GPT-4o mini 37.6%
- 106
InternVL2.5-26B 37.1%
- 107
Qwen2.5-Omni-7B 36.6%
- 108
InternVL2.5-8B 34.3%
- 109
InternVL2-40B 34.2%
- 110
Qwen2.5-VL-3B 31.6%
- 111
Qwen3.5-0.8B 31.2%
- 112 LLaVA-OneVision 72B 31%
- 113 LFM2.5-VL-3B 30.5%
- 114
InternVL2-8B 29%
- 115
Llama 3.2 11B 28.4%
- 116
Nemotron Nano 12B v2 VL 28%
- 117 MiniCPM-V-2_6 27.2%
- 118
Cosmos3-Edge 26.4%
- 119
MAmmoTH-VL-8B 25.3%
- 120
LLaVA-NeXT-72B 25.1%
- 121
LLaVA-OneVision 7B 24.1%
- 122
LLaVA-v1.6-34B 23.8%
- 123
InternVL2.5-2B 23.7%
- 124
Idefics3-8B-Llama3 22.9%
- 125 Phi-3.5-vision-instruct 19.7%
- 126
MiniCPM-Llama3-V 2.5 19.6%
- 127
InternVL2.5-1B 19.4%
- 128 llava-v1.6-vicuna-13b 17.2%
- 129 llava-v1.6-mistral-7b 17%
- 130 llava-v1.6-vicuna-7b 16.1%
Sources: Labs’ model cards and official MMMU-Pro leaderboard
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | GPT-5.6 Sol | 84.6% | Jul 2026 | Lab model card | |
| 2 | Kimi K3.1 Pro | 84.1% | Oct 2026 | Lab model card | |
| 3 | | 83.6% | May 2026 | Lab model card | |
| 4 | GPT-5.5 | 83.2% | Apr 2026 | Lab model card | |
| 5 | | 82.7% | Jun 2026 | Lab model card | |
| 6 | | 82.7% | Sep 2026 | Lab model card | |
| 7 | | 82.3% | Aug 2026 | Lab model card | |
| 8 | GPT-5.6 Terra | 82% | Jul 2026 | Lab model card | |
| 9 | | 81.7% | Sep 2026 | Lab model card | |
| 10 | Kimi K3 | 81.6% | Jul 2026 | Lab model card | |
| 11 | | 81.6% | Nov 2026 | Lab model card | |
| 12 | | 81.5% | Feb 2026 | Lab model card | |
| 13 | | 81.2% | Dec 2025 | Lab model card | |
| 14 | GPT-5.4 | 81.2% | Mar 2026 | Lab model card | |
| 15 | | 81% | Nov 2025 | Lab model card | |
| 16 | | 80.5% | Feb 2026 | Lab model card | |
| 17 | | 80.4% | Apr 2026 | Lab model card | |
| 18 | GPT-5.6 Luna | 79.5% | Jul 2026 | Lab model card | |
| 19 | Kimi K2.6 | 79.4% | Apr 2026 | Lab model card | |
| 20 | | 79% | Feb 2026 | Lab model card | |
| 21 | | 79% | Jun 2026 | Lab model card | |
| 22 | | 78.8% | Apr 2026 | Lab model card | |
| 23 | Kimi K2.5 | 78.5% | Jan 2026 | Lab model card | |
| 24 | GPT-5 | 78.4% | Aug 2025 | Lab model card | |
| 25 | | 78.4% | Apr 2026 | Lab model card | |
| 26 | | 78.2% | Feb 2026 | Lab model card | |
| 27 | | 78.1% | Jun 2026 | Lab model card | |
| 28 | GPT-5.4 Mini | 78% | Mar 2026 | Lab model card | |
| 29 | MiMo-V2.5 | 77.9% | Apr 2026 | Lab model card | |
| 30 | Claude Opus 4.6 | 77.3% | Feb 2026 | Lab model card | |
| 31 | | 76.9% | Feb 2026 | Lab model card | |
| 32 | | 76.9% | Apr 2026 | Lab model card | |
| 33 | | 76.8% | Mar 2026 | Lab model card | |
| 34 | MiMo-V2-Omni | 76.8% | Mar 2026 | Lab model card | |
| 35 | GPT-5.5 Instant | 76% | May 2026 | Lab model card | |
| 36 | | 76% | Sep 2026 | Lab model card | |
| 37 | | 75.8% | Apr 2026 | Lab model card | |
| 38 | Claude Sonnet 4.6 | 75.6% | Feb 2026 | Lab model card | |
| 39 | | 75.3% | Apr 2026 | Lab model card | |
| 40 | | 75.1% | Feb 2026 | Lab model card | |
| 41 | | 75% | Feb 2026 | Lab model card | |
| 42 | GPT-5 mini | 74.1% | Aug 2025 | Lab model card | |
| 43 | | 74% | Jul 2026 | Lab model card | |
| 44 | | 74% | Aug 2026 | Lab model card | |
| 45 | | 73.9% | Mar 2026 | Lab model card | |
| 46 | | 73.8% | Apr 2026 | Lab model card | |
| 47 | | 73.5% | Jul 2026 | Lab model card | |
| 48 | | 73.2% | Dec 2025 | Lab model card | |
| 49 | | 72.8% | Feb 2026 | Lab model card | |
| 50 | | 70.1% | Mar 2026 | Lab model card | |
| 51 | GPT-5.4 Nano | 69.5% | Mar 2026 | Lab model card | |
| 52 | | 69.3% | Sep 2025 | Lab model card | |
| 53 | | 69.1% | Jun 2026 | Lab model card | |
| 54 | | 68.6% | Feb 2026 | Lab model card | |
| 55 | | 68.6% | Apr 2026 | Lab model card | |
| 56 | | 67.6% | May 2025 | Lab model card | |
| 57 | | 66.4% | Jun 2025 | Lab model card | |
| 58 | | 66.3% | Mar 2026 | Lab model card | |
| 59 | GLM-4.6V | 66% | Dec 2025 | Lab model card | |
| 60 | GLM-4.5V | 65.2% | Aug 2025 | Lab model card | |
| 61 | | 64.1% | Jan 2026 | Lab model card | |
| 62 | | 63.5% | Dec 2025 | Lab model card | |
| 63 | | 63% | May 2026 | Lab model card | |
| 64 | GPT-5 nano | 62.6% | Aug 2025 | Lab model card | |
| 65 | | 61.8% | Dec 2025 | Lab model card | |
| 66 | | 61.4% | Dec 2025 | Lab model card | |
| 67 | | 60% | Mar 2026 | Lab model card | |
| 68 | | 59.6% | Apr 2025 | Lab model card | |
| 69 | | 57.9% | Jun 2025 | Lab model card | |
| 70 | GLM-4.1V-9B-Thinking | 57.1% | Jul 2025 | Lab model card | |
| 71 | | 57% | Sep 2025 | Lab model card | |
| 72 | | 56.5% | Sep 2026 | Lab model card | |
| 73 | | 56.5% | Sep 2026 | Lab model card | |
| 74 | | 54.3% | Jun 2026 | Lab model card | |
| 75 | | 52.6% | Apr 2026 | Lab model card | |
| 76 | | 52.2% | Apr 2025 | Lab model card | |
| 77 | | 51.8% | Jun 2025 | Lab model card | |
| 78 | | 51.1% | Jan 2025 | Lab model card | |
| 79 | | 50.3% | Mar 2026 | Lab model card | |
| 80 | | 49.3% | Mar 2025 | Lab model card | |
| 81 | Kimi-VL-A3B-Thinking-2506 | 46.3% | Jun 2025 | Lab model card | |
| 82 | | 44.2% | Apr 2026 | Lab model card | |
| 83 | | 42% | Oct 2026 | Lab model card | |
| 84 | | 41.1% | May 2026 | Lab model card | |
| 85 | | 38.5% | Feb 2025 | Lab model card | |
| 86 | | 36.6% | Mar 2025 | Lab model card | |
| 87 | | 31.2% | Mar 2026 | Lab model card | |
| 88 | LFM2.5-VL-3B | 30.5% | Aug 2026 | Lab model card | |
| 89 | | 28% | Nov 2025 | Lab model card | |
| 90 | | 26.4% | May 2026 | Lab model card |
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | GPT-5.4 | 82.1% | thinking, with tools | Mar 2026 | Official leaderboard |
| 2 | | 81% | Nov 2025 | Official leaderboard | |
| 3 | | 80.5% | thinking, high | Feb 2026 | Official leaderboard |
| 4 | GPT-5.2 | 80.4% | thinking, no python | Dec 2025 | Official leaderboard |
| 5 | | 80.4% | thinking | Apr 2026 | Official leaderboard |
| 6 | GPT-5.1 | 79% | thinking | Nov 2025 | Official leaderboard |
| 7 | GPT-5 | 78.4% | thinking | Aug 2025 | Official leaderboard |
| 8 | Claude Opus 4.6 | 77.3% | with tools | Feb 2026 | Official leaderboard |
| 9 | | 76.9% | Apr 2026 | Official leaderboard | |
| 10 | o3 | 76.4% | Apr 2025 | Official leaderboard | |
| 11 | Claude Sonnet 4.6 | 75.6% | with tools | Feb 2026 | Official leaderboard |
| 12 | Claude Opus 4.5 | 73.9% | Nov 2025 | Official leaderboard | |
| 13 | | 73.8% | Apr 2026 | Official leaderboard | |
| 14 | dots.vlm1 | 70.1% | Aug 2025 | Official leaderboard | |
| 15 | Claude Sonnet 4.5 | 68.9% | Sep 2025 | Official leaderboard | |
| 16 | | 68.1% | Sep 2025 | Official leaderboard | |
| 17 | | 68% | May 2025 | Official leaderboard | |
| 18 | | 67.6% | thinking | May 2025 | Official leaderboard |
| 19 | | 66.4% | Jun 2025 | Official leaderboard | |
| 20 | GLM-4.5V | 65.2% | thinking | Aug 2025 | Official leaderboard |
| 21 | GLM-4.1V-9B-Thinking | 57.1% | thinking | Jul 2025 | Official leaderboard |
| 22 | | 55.4% | Jul 2025 | Official leaderboard | |
| 23 | | 52.6% | Mar 2026 | Official leaderboard | |
| 24 | GPT-4o May 2024 | 51.9% | May 2024 | Official leaderboard | |
| 25 | Claude 3.5 Sonnet | 51.5% | Jun 2024 | Official leaderboard | |
| 26 | | 48.6% | Dec 2024 | Official leaderboard | |
| 27 | Qwen2-VL-72B-Instruct | 46.2% | Aug 2024 | Official leaderboard | |
| 28 | | 46.2% | Jan 2025 | Official leaderboard | |
| 29 | | 46% | Dec 2024 | Official leaderboard | |
| 30 | | 44.2% | Mar 2026 | Official leaderboard | |
| 31 | | 43.5% | May 2024 | Official leaderboard | |
| 32 | MiMo-VL-7B-RL | 43.3% | May 2025 | Official leaderboard | |
| 33 | MiMo-VL-7B-SFT | 42.3% | May 2025 | Official leaderboard | |
| 34 | | 40% | Jul 2024 | Official leaderboard | |
| 35 | | 39.5% | Sep 2024 | Official leaderboard | |
| 36 | | 38.3% | Jan 2025 | Official leaderboard | |
| 37 | GPT-4o mini | 37.6% | Jul 2024 | Official leaderboard | |
| 38 | | 37.1% | Dec 2024 | Official leaderboard | |
| 39 | | 34.3% | Dec 2024 | Official leaderboard | |
| 40 | | 34.2% | Jul 2024 | Official leaderboard | |
| 41 | | 31.6% | Jan 2025 | Official leaderboard | |
| 42 | LLaVA-OneVision 72B | 31% | Aug 2024 | Official leaderboard | |
| 43 | | 29% | Jul 2024 | Official leaderboard | |
| 44 | | 28.4% | Sep 2024 | Official leaderboard | |
| 45 | MiniCPM-V-2_6 | 27.2% | Aug 2024 | Official leaderboard | |
| 46 | | 25.3% | Nov 2024 | Official leaderboard | |
| 47 | | 25.1% | May 2024 | Official leaderboard | |
| 48 | | 24.1% | Aug 2024 | Official leaderboard | |
| 49 | | 23.8% | Jan 2024 | Official leaderboard | |
| 50 | | 23.7% | Dec 2024 | Official leaderboard | |
| 51 | | 22.9% | Aug 2024 | Official leaderboard | |
| 52 | Phi-3.5-vision-instruct | 19.7% | Aug 2024 | Official leaderboard | |
| 53 | | 19.6% | May 2024 | Official leaderboard | |
| 54 | | 19.4% | Dec 2024 | Official leaderboard | |
| 55 | llava-v1.6-vicuna-13b | 17.2% | Jan 2024 | Official leaderboard | |
| 56 | llava-v1.6-mistral-7b | 17% | Jan 2024 | Official leaderboard | |
| 57 | llava-v1.6-vicuna-7b | 16.1% | Jan 2024 | Official leaderboard |
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | GPT-5.6 Sol | 84.6% | Jul 2026 | Lab model card | |
| 2 | Kimi K3.1 Pro | 84.1% | Oct 2026 | Lab model card | |
| 3 | | 83.6% | May 2026 | Lab model card | |
| 4 | GPT-5.5 | 83.2% | Apr 2026 | Lab model card | |
| 5 | | 82.7% | Jun 2026 | Lab model card | |
| 6 | | 82.7% | Sep 2026 | Lab model card | |
| 7 | | 82.3% | Aug 2026 | Lab model card | |
| 8 | GPT-5.4 | 82.1% | thinking, with tools | Mar 2026 | Official leaderboard |
| 9 | GPT-5.6 Terra | 82% | Jul 2026 | Lab model card | |
| 10 | | 81.7% | Sep 2026 | Lab model card | |
| 11 | Kimi K3 | 81.6% | Jul 2026 | Lab model card | |
| 12 | | 81.6% | Nov 2026 | Lab model card | |
| 13 | | 81.5% | Feb 2026 | Lab model card | |
| 14 | | 81.2% | Dec 2025 | Lab model card | |
| 15 | | 81% | Nov 2025 | Official leaderboard | |
| 16 | | 80.5% | thinking, high | Feb 2026 | Official leaderboard |
| 17 | GPT-5.2 | 80.4% | thinking, no python | Dec 2025 | Official leaderboard |
| 18 | | 80.4% | thinking | Apr 2026 | Official leaderboard |
| 19 | GPT-5.6 Luna | 79.5% | Jul 2026 | Lab model card | |
| 20 | Kimi K2.6 | 79.4% | Apr 2026 | Lab model card | |
| 21 | GPT-5.1 | 79% | thinking | Nov 2025 | Official leaderboard |
| 22 | | 79% | Feb 2026 | Lab model card | |
| 23 | | 79% | Jun 2026 | Lab model card | |
| 24 | | 78.8% | Apr 2026 | Lab model card | |
| 25 | Kimi K2.5 | 78.5% | Jan 2026 | Lab model card | |
| 26 | GPT-5 | 78.4% | thinking | Aug 2025 | Official leaderboard |
| 27 | | 78.4% | Apr 2026 | Lab model card | |
| 28 | | 78.2% | Feb 2026 | Lab model card | |
| 29 | | 78.1% | Jun 2026 | Lab model card | |
| 30 | GPT-5.4 Mini | 78% | Mar 2026 | Lab model card | |
| 31 | MiMo-V2.5 | 77.9% | Apr 2026 | Lab model card | |
| 32 | Claude Opus 4.6 | 77.3% | with tools | Feb 2026 | Official leaderboard |
| 33 | | 76.9% | Feb 2026 | Lab model card | |
| 34 | | 76.9% | Apr 2026 | Official leaderboard | |
| 35 | | 76.8% | Mar 2026 | Lab model card | |
| 36 | MiMo-V2-Omni | 76.8% | Mar 2026 | Lab model card | |
| 37 | o3 | 76.4% | Apr 2025 | Official leaderboard | |
| 38 | GPT-5.5 Instant | 76% | May 2026 | Lab model card | |
| 39 | | 76% | Sep 2026 | Lab model card | |
| 40 | | 75.8% | Apr 2026 | Lab model card | |
| 41 | Claude Sonnet 4.6 | 75.6% | with tools | Feb 2026 | Official leaderboard |
| 42 | | 75.3% | Apr 2026 | Lab model card | |
| 43 | | 75.1% | Feb 2026 | Lab model card | |
| 44 | | 75% | Feb 2026 | Lab model card | |
| 45 | GPT-5 mini | 74.1% | Aug 2025 | Lab model card | |
| 46 | | 74% | Jul 2026 | Lab model card | |
| 47 | | 74% | Aug 2026 | Lab model card | |
| 48 | Claude Opus 4.5 | 73.9% | Nov 2025 | Official leaderboard | |
| 49 | | 73.9% | Mar 2026 | Lab model card | |
| 50 | | 73.8% | Apr 2026 | Official leaderboard | |
| 51 | | 73.5% | Jul 2026 | Lab model card | |
| 52 | | 73.2% | Dec 2025 | Lab model card | |
| 53 | | 72.8% | Feb 2026 | Lab model card | |
| 54 | dots.vlm1 | 70.1% | Aug 2025 | Official leaderboard | |
| 55 | | 70.1% | Mar 2026 | Lab model card | |
| 56 | GPT-5.4 Nano | 69.5% | Mar 2026 | Lab model card | |
| 57 | | 69.3% | Sep 2025 | Lab model card | |
| 58 | | 69.1% | Jun 2026 | Lab model card | |
| 59 | Claude Sonnet 4.5 | 68.9% | Sep 2025 | Official leaderboard | |
| 60 | | 68.6% | Feb 2026 | Lab model card | |
| 61 | | 68.6% | Apr 2026 | Lab model card | |
| 62 | | 68% | May 2025 | Official leaderboard | |
| 63 | | 67.6% | thinking | May 2025 | Official leaderboard |
| 64 | | 66.4% | Jun 2025 | Official leaderboard | |
| 65 | | 66.3% | Mar 2026 | Lab model card | |
| 66 | GLM-4.6V | 66% | Dec 2025 | Lab model card | |
| 67 | GLM-4.5V | 65.2% | thinking | Aug 2025 | Official leaderboard |
| 68 | | 64.1% | Jan 2026 | Lab model card | |
| 69 | | 63.5% | Dec 2025 | Lab model card | |
| 70 | | 63% | May 2026 | Lab model card | |
| 71 | GPT-5 nano | 62.6% | Aug 2025 | Lab model card | |
| 72 | | 61.8% | Dec 2025 | Lab model card | |
| 73 | | 61.4% | Dec 2025 | Lab model card | |
| 74 | | 60% | Mar 2026 | Lab model card | |
| 75 | | 59.6% | Apr 2025 | Lab model card | |
| 76 | | 57.9% | Jun 2025 | Lab model card | |
| 77 | GLM-4.1V-9B-Thinking | 57.1% | thinking | Jul 2025 | Official leaderboard |
| 78 | | 57% | Sep 2025 | Lab model card | |
| 79 | | 56.5% | Sep 2026 | Lab model card | |
| 80 | | 56.5% | Sep 2026 | Lab model card | |
| 81 | | 55.4% | Jul 2025 | Official leaderboard | |
| 82 | | 54.3% | Jun 2026 | Lab model card | |
| 83 | | 52.6% | Mar 2026 | Official leaderboard | |
| 84 | | 52.2% | Apr 2025 | Lab model card | |
| 85 | GPT-4o May 2024 | 51.9% | May 2024 | Official leaderboard | |
| 86 | | 51.8% | Jun 2025 | Lab model card | |
| 87 | Claude 3.5 Sonnet | 51.5% | Jun 2024 | Official leaderboard | |
| 88 | | 51.1% | Jan 2025 | Lab model card | |
| 89 | | 50.3% | Mar 2026 | Lab model card | |
| 90 | | 49.3% | Mar 2025 | Lab model card | |
| 91 | | 48.6% | Dec 2024 | Official leaderboard | |
| 92 | Kimi-VL-A3B-Thinking-2506 | 46.3% | Jun 2025 | Lab model card | |
| 93 | Qwen2-VL-72B-Instruct | 46.2% | Aug 2024 | Official leaderboard | |
| 94 | | 46% | Dec 2024 | Official leaderboard | |
| 95 | | 44.2% | Mar 2026 | Official leaderboard | |
| 96 | | 43.5% | May 2024 | Official leaderboard | |
| 97 | MiMo-VL-7B-RL | 43.3% | May 2025 | Official leaderboard | |
| 98 | MiMo-VL-7B-SFT | 42.3% | May 2025 | Official leaderboard | |
| 99 | | 42% | Oct 2026 | Lab model card | |
| 100 | | 41.1% | May 2026 | Lab model card | |
| 101 | | 40% | Jul 2024 | Official leaderboard | |
| 102 | | 39.5% | Sep 2024 | Official leaderboard | |
| 103 | | 38.5% | Feb 2025 | Lab model card | |
| 104 | | 38.3% | Jan 2025 | Official leaderboard | |
| 105 | GPT-4o mini | 37.6% | Jul 2024 | Official leaderboard | |
| 106 | | 37.1% | Dec 2024 | Official leaderboard | |
| 107 | | 36.6% | Mar 2025 | Lab model card | |
| 108 | | 34.3% | Dec 2024 | Official leaderboard | |
| 109 | | 34.2% | Jul 2024 | Official leaderboard | |
| 110 | | 31.6% | Jan 2025 | Official leaderboard | |
| 111 | | 31.2% | Mar 2026 | Lab model card | |
| 112 | LLaVA-OneVision 72B | 31% | Aug 2024 | Official leaderboard | |
| 113 | LFM2.5-VL-3B | 30.5% | Aug 2026 | Lab model card | |
| 114 | | 29% | Jul 2024 | Official leaderboard | |
| 115 | | 28.4% | Sep 2024 | Official leaderboard | |
| 116 | | 28% | Nov 2025 | Lab model card | |
| 117 | MiniCPM-V-2_6 | 27.2% | Aug 2024 | Official leaderboard | |
| 118 | | 26.4% | May 2026 | Lab model card | |
| 119 | | 25.3% | Nov 2024 | Official leaderboard | |
| 120 | | 25.1% | May 2024 | Official leaderboard | |
| 121 | | 24.1% | Aug 2024 | Official leaderboard | |
| 122 | | 23.8% | Jan 2024 | Official leaderboard | |
| 123 | | 23.7% | Dec 2024 | Official leaderboard | |
| 124 | | 22.9% | Aug 2024 | Official leaderboard | |
| 125 | Phi-3.5-vision-instruct | 19.7% | Aug 2024 | Official leaderboard | |
| 126 | | 19.6% | May 2024 | Official leaderboard | |
| 127 | | 19.4% | Dec 2024 | Official leaderboard | |
| 128 | llava-v1.6-vicuna-13b | 17.2% | Jan 2024 | Official leaderboard | |
| 129 | llava-v1.6-mistral-7b | 17% | Jan 2024 | Official leaderboard | |
| 130 | llava-v1.6-vicuna-7b | 16.1% | Jan 2024 | Official leaderboard |
The benchmark's own leaderboard has 61 entries, 57 of them models we track. Switch the scores above to rank them together.
Scores at each effort level
Models the leaderboard ran at two or more effort levels. We don’t have enough cost data here to say what the extra effort costs.
Source: Official MMMU-Pro leaderboard
10 models have held number one in labs’ own numbers since its release in September 2024 6 models have held number one across all independent runs since its release in September 2024 12 models have held number one with claims included since its release in September 2024
Lab claims count from the day the card came out, independent runs from the model’s release. We draw one row each for the benchmark’s own leaderboard and what labs claim in their cards.
Sources: Official MMMU-Pro leaderboard and labs’ model cards
Scores over time
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Sources: Official MMMU-Pro leaderboard and labs’ model cards
12 labs put it in a launch post in the last six months
Launch posts from every lab that has listed it, one tick per post. Tall colored ticks include it, and short gray ones leave it out.
| Date | Launch post | Score | As the post writes it |
|---|---|---|---|
| Nov 5, 2026 | 81.6 | MMMU Pro (Standard 10) | |
| Oct 26, 2026 | GPT-6.1 Terra | MMMU-Pro (chart) | |
| Oct 24, 2026 | Kimi K3.1 Pro | 84.1 | MMMU-Pro |
| Sep 20, 2026 | 76 | MMMU-Pro | |
| Sep 13, 2026 | 81.7 | MMMU Pro | |
| Sep 10, 2026 | 56.5 | MMMU-Pro (EM) | |
| Sep 2, 2026 | 82.7 | STEM visual reasoning, MMMU-Pro | |
| Aug 12, 2026 | LFM2.5-VL-3B | 30.5 | MMMU-Pro |
| Aug 10, 2026 | 74 | MMMU Pro | |
| Aug 3, 2026 | 82.3 | MMMU-Pro | |
| Jul 30, 2026 | 74 | MMMU Pro Standard 10 | |
| Jul 16, 2026 | Kimi K3 | 81.6 | MMMU-Pro (without python) |
| Jul 15, 2026 | 73.5 | MMMU Pro Standard 10 (Artificial Analysis) | |
| Jul 9, 2026 | GPT-5.6 Luna | 79.5 | MMMU Pro (with tools) 79.5 (no tools 78.4) |
| Jul 9, 2026 | GPT-5.6 Terra | 82 | MMMU Pro (with tools) 82 (no tools 80.7) |
| Jul 9, 2026 | GPT-5.6 Sol | 84.6 | MMMU Pro with tools 84.6% (no tools 83.0%) |
| Jun 23, 2026 | 82.7 | MMMU-Pro (w. Tool) 81.6 (82.7) | |
| Jun 10, 2026 | 54.3 | MMMU Pro | |
| Jun 3, 2026 | 69.1 | MMMU Pro | |
| Jun 1, 2026 | 79 | MMMU-Pro | |
| Jun 1, 2026 | 78.1 | MMMU-Pro | |
| May 20, 2026 | 63 | MMMU Pro | |
| May 19, 2026 | 83.6 | MMMU-Pro (No tools) | |
| May 5, 2026 | GPT-5.5 Instant | 76 | MMMU-Pro Standard (Expert Multimodal Reasoning) |
| Apr 28, 2026 | 78.4 | MMMU_Pro | |
| Apr 23, 2026 | GPT-5.5 | 83.2 | MMMU Pro with tools 83.2% (no tools 81.2%) |
| Apr 22, 2026 | 75.8 | MMMU-Pro | |
| Apr 22, 2026 | MiMo-V2.5 | 77.9 | MMMU-Pro |
| Apr 20, 2026 | Kimi K2.6 | 79.4 | MMMU-Pro |
| Apr 15, 2026 | 75.3 | MMMU-Pro | |
| Apr 9, 2026 | 68.6 | MMMU-Pro | |
| Apr 8, 2026 | 80.4 | MMMU Pro (Multimodal Understanding) | |
| Apr 2, 2026 | 52.6 | MMMU Pro | |
| Apr 2, 2026 | 44.2 | MMMU Pro | |
| Apr 2, 2026 | 73.8 | MMMU Pro | |
| Apr 2, 2026 | 78.8 | MMMU-Pro | |
| Apr 2, 2026 | 76.9 | MMMU Pro | |
| Mar 30, 2026 | 73.9 | MMMU-Pro | |
| Mar 18, 2026 | MiMo-V2-Omni | 76.8 | MMMU-Pro |
| Mar 17, 2026 | GPT-5.4 Nano | 69.5 | MMMUPro w/ Python 69.5 (without 66.1) |
| Mar 17, 2026 | GPT-5.4 Mini | 78 | MMMU-Pro with Python, without Python 76.6% |
| Mar 16, 2026 | 60 | MMMU-Pro (reasoning; instruct = 46.3) | |
| Mar 5, 2026 | GPT-5.4 | 81.2 | MMMU Pro (no tools) |
| Mar 3, 2026 | 76.8 | MMMU-Pro (No tools) | |
| Mar 2, 2026 | 31.2 | MMMU-Pro 31.2/31.4 (with CI / without CI) | |
| Mar 2, 2026 | 50.3 | MMMU-Pro 50.3/47.7 (with CI / without CI) | |
| Mar 2, 2026 | 66.3 | MMMU-Pro | |
| Mar 2, 2026 | 70.1 | MMMU-Pro | |
| Feb 24, 2026 | 75.1 | MMMU-Pro | |
| Feb 24, 2026 | 75 | MMMU-Pro | |
| Feb 24, 2026 | 76.9 | MMMU-Pro | |
| Feb 19, 2026 | 80.5 | MMMU-Pro (No tools) | |
| Feb 17, 2026 | Claude Sonnet 4.6 | 75.6 | Visual reasoning MMMU-Pro (with tools) |
| Feb 16, 2026 | 79 | MMMU-Pro | |
| Feb 12, 2026 | 81.5 | MMMU-Pro, no tools, 81.5% | |
| Feb 6, 2026 | 68.6 | MMMU-Pro | |
| Feb 5, 2026 | Claude Opus 4.6 | 77.3 | Visual reasoning MMMU Pro (with tools) |
| Feb 2, 2026 | 72.8 | MMMU-Pro | |
| Jan 27, 2026 | Kimi K2.5 | 78.5 | MMMU-Pro |
| Dec 18, 2025 | 73.2 | MMMU-Pro | |
| Dec 17, 2025 | 81.2 | MMMU-Pro | |
| Dec 8, 2025 | GLM-4.6V | 66 | MMMU_Pro |
| Dec 2, 2025 | 61.4 | MMMU Pro accuracy | |
| Dec 2, 2025 | 61.8 | MMMU Pro accuracy | |
| Dec 2, 2025 | 63.5 | MMMU Pro accuracy | |
| Nov 18, 2025 | 81 | MMMU-Pro | |
| Sep 23, 2025 | 69.3 | MMMU_Pro | |
| Sep 22, 2025 | 57 | MMMU_pro | |
| Aug 11, 2025 | GLM-4.5V | 65.2 | MMMU Pro |
| Aug 7, 2025 | GPT-5 nano | 62.6 | MMMU-Pro (avg across standard and vision sets) |
| Aug 7, 2025 | GPT-5 mini | 74.1 | MMMU-Pro (avg across standard and vision sets) |
| Aug 7, 2025 | GPT-5 | 78.4 | MMMU Pro*** Graduate-level visual problem-solving |
| Jul 1, 2025 | GLM-4.1V-9B-Thinking | 57.1 | MMMU-Pro |
| Jun 25, 2025 | 66.4 | MMMU-pro | |
| Jun 21, 2025 | Kimi-VL-A3B-Thinking-2506 | 46.3 | MMMU-Pro (Pass@1) |
| May 12, 2025 | 67.6 | MMMU-Pro | |
| Apr 5, 2025 | 52.2 | MMMU Pro (avg of Standard and Vision) | |
| Apr 5, 2025 | 59.6 | MMMU Pro (avg of Standard and Vision) | |
| Mar 27, 2025 | 36.6 | MMMU-Prooverall | |
| Mar 17, 2025 | 49.3 | MMMU PRO | |
| Feb 26, 2025 | 38.5 | MMMU-Pro (std/vision) | |
| Jan 28, 2025 | 51.1 | MMMU_Pro |
45 system cards report it, from 17 labs
Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.
| Date | Document | Score | As the document writes it | Section |
|---|---|---|---|---|
| Oct 23, 2026 | | 42 | MMMU-Pro Vision, reasoning, 39.08 non-reasoning (Table 8) | Capabilities |
| Oct 19, 2026 | | 74 | MMMU-Pro, high (Tables 2 and 5) | Capabilities |
| Sep 10, 2026 | | 56.5 | MMMU-Pro, EM, 4-shot | Capabilities |
| Jul 31, 2026 | | 54.3 | MMMU Pro, TD, 66.0 no-think (Table 3) | Capabilities |
| Jul 30, 2026 | | 74 | MMMU Pro Standard 10 (5. Evaluations table) | Capabilities |
| Jul 27, 2026 | Kimi K3 technical report | 81.6 | MMMU-Pro without Python, cell 81.6 / 83.4 (without / with Python) (Table 2) | Capabilities |
| Jul 24, 2026 | | 52.6 | MMMU Pro, max resolution, thinking (Table 6) | Capabilities |
| Jul 24, 2026 | | 44.2 | MMMU Pro, max resolution, thinking (Table 6) | Capabilities |
| Jul 24, 2026 | | 76.9 | MMMU Pro, thinking, max resolution 1120 vision tokens (Table 6). At 280 tokens: 75.8 | Capabilities |
| Jul 24, 2026 | | 73.8 | MMMU Pro, thinking, max resolution 1120 vision tokens (Table 6). At 280 tokens: 73.2 | Capabilities |
| Jul 15, 2026 | | 73.5 | MMMU Pro Standard 10 (5. Evaluations table, effort 0.99) | Capabilities |
| Jun 23, 2026 | | 81.6 | MMMU-Pro, no tools, 82.7 with tools (Table 9) | Capabilities |
| May 31, 2026 | | 41.1 | MMMU-Pro, Cosmos3-Nano 8B column, Table 10 | Capabilities |
| May 31, 2026 | | 26.4 | MMMU-Pro, Cosmos3-Edge 2B column, Table 10 | Capabilities |
| May 19, 2026 | | 83.6 | MMMU-Pro, no tools (results table, p.4) | Capabilities |
| Apr 17, 2026 | | 73.9 | MMMU-Pro (Table 6) | Capabilities |
| Apr 9, 2026 | | 68.6 | MMMU-Pro (Table 2, Reasoning mode) | Capabilities |
| Mar 26, 2026 | | 72.8 | MMMU-Pro, thinking (Table 2) | Capabilities |
| Mar 21, 2026 | | 73.2 | MMMU-Pro (Table 2). 65.4 in NoThink mode (2.4 text) | Capabilities |
| Mar 3, 2026 | | 76.8 | MMMU-Pro, no tools (results table, p.4) | Capabilities |
| Feb 19, 2026 | | 80.5 | MMMU Pro, no tools (results table, p.4) | Capabilities |
| Feb 17, 2026 | Claude Sonnet 4.6 system card | 74.5 | MMMU-Pro, no tools, adaptive thinking, max effort; 75.6 with an image cropping tool (Table 2.1.A, 2.17.2) | Capabilities |
| Feb 14, 2026 | | 78.2 | MMMU-Pro, Standard (10 options) and Vision combined (Table 8) | Capabilities |
| Feb 5, 2026 | Claude Opus 4.6 system card | 73.9 | MMMU-Pro, no tools, adaptive thinking, max effort, average of Standard (10 options) and Vision (Table 2.3.A, 2.19.2); 77.3 with an image cropping tool | Capabilities |
| Feb 4, 2026 | | 68.6 | MMMU-Pro (Table 3) | Capabilities |
| Jan 30, 2026 | Kimi K2.5 technical report | 78.5 | MMMU-Pro (Table 4) | Capabilities |
| Jan 14, 2026 | | 64.1 | MMMU-Pro, SeRe (Tables 1 and 3). PaCoRe 67.18 | Capabilities |
| Jan 1, 2026 | GLM-4.6V technical report | 66 | MMMU Pro, GLM-4.6V thinking (Table 2) | Capabilities |
| Dec 2, 2025 | | 61.4 | MMMU Pro accuracy (Table 6) | Capabilities |
| Dec 2, 2025 | | 61.8 | MMMU Pro accuracy (Table 3) | Capabilities |
| Dec 2, 2025 | | 63.5 | MMMU Pro accuracy (Table 3) | Capabilities |
| Nov 26, 2025 | | 69.3 | MMMU-Pro (Table 2) | Capabilities |
| Nov 6, 2025 | | 28 | MMMU Pro, reasoning on (Table 3). Reasoning off 14.5 | Capabilities |
| Sep 22, 2025 | | 57 | MMMU-Pro overall, Instruct (Table 9). Thinking 60.5 (Table 10) | Capabilities |
| Aug 13, 2025 | GLM-4.5V technical report | 65.2 | MMMU Pro, GLM-4.5V thinking (Table 2) | Capabilities |
| Jul 1, 2025 | GLM-4.1V-9B-Thinking technical report | 57.1 | MMMU Pro, GLM-4.1V-9B-Thinking thinking (Table 2) | Capabilities |
| Jun 23, 2025 | Kimi-VL-A3B-Thinking-2506 technical report | 46.3 | MMMU-Pro (avg) (Pass@1) (Table 4) | Capabilities |
| Jun 12, 2025 | | 51.8 | MMMU-Pro (Standard), Magistral Small bar, printed label (Figure 10). MMMU-Pro (Vision) 39.2 | Capabilities |
| Jun 12, 2025 | | 57.9 | MMMU-Pro (Standard), printed bar label (Figure 10). MMMU-Pro (Vision) 52.1 | Capabilities |
| May 11, 2025 | | 67.6 | MMMU-Pro, thinking (Table 6). Non-thinking 59.9 | Capabilities |
| Apr 5, 2025 | | 52.2 | MMMU Pro, 0-shot, average of Standard and Vision, instruction tuned (Instruction tuned models table) | Capabilities |
| Apr 5, 2025 | | 59.6 | MMMU Pro, 0-shot, average of Standard and Vision, instruction tuned (Instruction tuned models table) | Capabilities |
| Mar 26, 2025 | | 36.6 | MMMU-Pro overall (Table 5) | Capabilities |
| Mar 3, 2025 | | 38.5 | MMMUPro, average of standard 39.7 and vision 37.3 (Table 1) | Capabilities |
| Feb 19, 2025 | | 51.1 | MMMU-Pro overall (Table 3) | Capabilities |
The lab's number comes out ahead in 2 of 3 pairs that differ
Each score a lab reported for its own model, beside the same model's best score on the leaderboard. Gaps mostly come from different harnesses, effort levels and task subsets. 14 of them match, which usually means one side copied the other. Every benchmark.
| Model | Lab says | Board says | Gap |
|---|---|---|---|
| | 51.1% MMMU_Pro | 46.2% Leaderboard | +4.9 pts |
| | 69.3% MMMU_Pro | 68.1% Leaderboard | +1.2 pts |
| GPT-5.4 | 81.2% MMMU Pro (no tools) | 82.1% Leaderboard, thinking, with tools | −0.9 pts |
| | 67.6% MMMU-Pro | 67.6% Leaderboard, thinking | Same |
| | 66.4% MMMU-pro | 66.4% Leaderboard | Same |
| GLM-4.1V-9B-Thinking | 57.1% MMMU-Pro | 57.1% Leaderboard, thinking | Same |
| GPT-5 | 78.4% MMMU Pro*** Graduate-level visual problem-solving | 78.4% Leaderboard, thinking | Same |
| GLM-4.5V | 65.2% MMMU Pro | 65.2% Leaderboard, thinking | Same |
| | 81% MMMU-Pro | 81% Leaderboard | Same |
| Claude Opus 4.6 | 77.3% Visual reasoning MMMU Pro (with tools) | 77.3% Leaderboard, with tools | Same |
| Claude Sonnet 4.6 | 75.6% Visual reasoning MMMU-Pro (with tools) | 75.6% Leaderboard, with tools | Same |
| | 80.5% MMMU-Pro (No tools) | 80.5% Leaderboard, thinking, high | Same |
| | 76.9% MMMU Pro | 76.9% Leaderboard | Same |
| | 73.8% MMMU Pro | 73.8% Leaderboard | Same |
| | 44.2% MMMU Pro | 44.2% Leaderboard | Same |
| | 52.6% MMMU Pro | 52.6% Leaderboard | Same |
| | 80.4% MMMU Pro (Multimodal Understanding) | 80.4% Leaderboard, thinking | Same |
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