multimodal benchmark
VideoMMMU Leaderboard
Video-MMMU evaluates Large Multimodal Models' ability to acquire knowledge from expert-level professional videos across six disciplines through three cognitive stages: perception, comprehension, and adaptation. Contains 300 videos and 900 human-annotated questions spanning Art, Business, Science, Medicine, Humanities, and Engineering.
Updated Aug 17, 2026
Models26
Model coverage26
MetricScore
EvidenceB
VideoMMMU Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelGO | Score87.6% | Percentile100.0% | Participants26 | EvidenceC | Evaluated |
| Rank02 | ModelGO | Score86.9% | Percentile96.0% | Participants26 | EvidenceC | Evaluated |
| Rank03 | ModelMA | Score86.6% | Percentile92.0% | Participants26 | EvidenceC | Evaluated |
| Rank04 | ModelOP | Score85.9% | Percentile88.0% | Participants26 | EvidenceC | Evaluated |
| Rank05 | ModelAC | Score85.4% | Percentile84.0% | Participants26 | EvidenceC | Evaluated |
| Rank06 | ModelGO | Score84.8% | Percentile80.0% | Participants26 | EvidenceC | Evaluated |
| Rank07 | ModelOP | Score84.6% | Percentile76.0% | Participants26 | EvidenceC | Evaluated |
| Rank08 | ModelMI | Score84.6% | Percentile72.0% | Participants26 | EvidenceC | Evaluated |
| Rank09 | ModelAC | Score84.4% | Percentile68.0% | Participants26 | EvidenceC | Evaluated |
| Rank10 | ModelAC | Score84.0% | Percentile64.0% | Participants26 | EvidenceC | Evaluated |
| Rank11 | ModelAC | Score83.7% | Percentile60.0% | Participants26 | EvidenceC | Evaluated |
| Rank12 | ModelGO | Score83.6% | Percentile56.0% | Participants26 | EvidenceC | Evaluated |
| Rank13 | ModelOP | Score83.3% | Percentile52.0% | Participants26 | EvidenceC | Evaluated |
| Rank14 | ModelAC | Score82.3% | Percentile48.0% | Participants26 | EvidenceC | Evaluated |
| Rank15 | ModelAC | Score82.0% | Percentile44.0% | Participants26 | EvidenceC | Evaluated |
| Rank16 | ModelAC | Score80.4% | Percentile40.0% | Participants26 | EvidenceC | Evaluated |
| Rank17 | ModelAC | Score80.0% | Percentile36.0% | Participants26 | EvidenceC | Evaluated |
| Rank18 | ModelAC | Score79.0% | Percentile32.0% | Participants26 | EvidenceC | Evaluated |
| Rank19 | ModelAC | Score75.0% | Percentile28.0% | Participants26 | EvidenceC | Evaluated |
| Rank20 | ModelAC | Score74.7% | Percentile24.0% | Participants26 | EvidenceC | Evaluated |
| Rank21 | ModelAC | Score72.8% | Percentile20.0% | Participants26 | EvidenceC | Evaluated |
| Rank22 | ModelAC | Score69.4% | Percentile16.0% | Participants26 | EvidenceC | Evaluated |
| Rank23 | ModelAC | Score68.7% | Percentile12.0% | Participants26 | EvidenceC | Evaluated |
| Rank24 | ModelAC | Score65.3% | Percentile8.0% | Participants26 | EvidenceC | Evaluated |
| Rank25 | ModelOP | Score61.2% | Percentile4.0% | Participants26 | EvidenceC | Evaluated |
| Rank26 | ModelAC | Score56.2% | Percentile0.0% | Participants26 | EvidenceC | Evaluated |
VideoMMMU Highlights
The leading models and scores on this benchmark.
VideoMMMU Score Distribution
A closer view of the leading scores on this benchmark.
The Top AI Models for VideoMMMU
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis videommmu AI model leaderboard uses descending score in the benchmark's original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.
- 01GOGemini 3 ProGoogle
- Score
- 87.6%
- Speed
- Up to 90 tok/s via Google
Strengths
- Ranks #1 of 26 compared models
- 100th percentile on this benchmark
- C evidence result
Considerations
- This result measures VideoMMMU, not total model capability
- 02GOGemini 3 FlashGoogle
- Score
- 86.9%
- Price
- $0.50 input / $3.0 output per 1M tokens
- Speed
- Up to 65 tok/s via Google
Strengths
- Ranks #2 of 26 compared models
- 96th percentile on this benchmark
- C evidence result
Considerations
- This result measures VideoMMMU, not total model capability
- 03MAKimi K2.5Moonshot AI
- Score
- 86.6%
- Price
- $0.60 input / $3.0 output per 1M tokens
Strengths
- Ranks #3 of 26 compared models
- 92th percentile on this benchmark
- C evidence result
Considerations
- This result measures VideoMMMU, not total model capability
- 04OPGPT-5.2OpenAI
- Score
- 85.9%
- Price
- $1.8 input / $14 output per 1M tokens
- Speed
- Up to 100 tok/s via OpenAI
Strengths
- Ranks #4 of 26 compared models
- 88th percentile on this benchmark
- C evidence result
Considerations
- This result measures VideoMMMU, not total model capability
- 05ACQwen3.7-PlusAlibaba Cloud / Qwen Team
- Score
- 85.4%
- Price
- $0.50 input / $3.0 output per 1M tokens
Strengths
- Ranks #5 of 26 compared models
- 84th percentile on this benchmark
- C evidence result
Considerations
- This result measures VideoMMMU, not total model capability
Selection summary
Best AI Models for VideoMMMU
Gemini 3 Pro currently leads VideoMMMU with 87.6%. It is the top model on this specific benchmark, while the best LLM for the broader task should also be checked against other benchmarks, price and runtime.
Use this leaderboard with the supporting benchmark results and coverage details above. A leaderboard position summarizes the selected ranking signal; it does not replace workload-specific testing.
What is VideoMMMU?
What VideoMMMU measures and how its scores work.
Video-MMMU evaluates Large Multimodal Models' ability to acquire knowledge from expert-level professional videos across six disciplines through three cognitive stages: perception, comprehension, and adaptation. Contains 300 videos and 900 human-annotated questions spanning Art, Business, Science, Medicine, Humanities, and Engineering.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- VideoMMMU
- Modality
- multimodal
- Primary category
- multimodal
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- videommmu|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about VideoMMMU.
Which model scores highest on VideoMMMU?
Gemini 3 Pro is currently ranked first with 87.6%.
What does VideoMMMU measure?
Video-MMMU evaluates Large Multimodal Models' ability to acquire knowledge from expert-level professional videos across six disciplines through three cognitive stages: perception, comprehension, and adaptation. Contains 300 videos and 900 human-annotated questions spanning Art, Business, Science, Medicine, Humanities, and Engineering.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
26 model results are currently shown.
Does this benchmark affect the overall score?
Yes. This benchmark can contribute to the current LLMBoard capability score.