multimodal benchmark
VideoMMMU Leaderboard
VideoMMMU evaluates Large Multimodal Models' ability to acquire knowledge from expert-level professional videos across six disciplines through perception, comprehension, and adaptation.
Updated Oct 23, 2026
Models28
Model coverage28
MetricScore
EvidenceB
VideoMMMU Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelGO | Score87.60% | Percentile100.00% | Participants28 | EvidenceC | Evaluated |
| Rank02 | ModelGO | Score86.90% | Percentile96.30% | Participants28 | EvidenceC | Evaluated |
| Rank03 | ModelMA | Score86.60% | Percentile92.59% | Participants28 | EvidenceC | Evaluated |
| Rank04 | ModelOP | Score85.90% | Percentile88.89% | Participants28 | EvidenceC | Evaluated |
| Rank05 | ModelAC | Score85.40% | Percentile85.19% | Participants28 | EvidenceC | Evaluated |
| Rank06 | ModelGO | Score84.80% | Percentile81.48% | Participants28 | EvidenceC | Evaluated |
| Rank07 | ModelOP | Score84.60% | Percentile77.78% | Participants28 | EvidenceC | Evaluated |
| Rank08 | ModelMI | Score84.60% | Percentile74.07% | Participants28 | EvidenceC | Evaluated |
| Rank09 | ModelAC | Score84.40% | Percentile70.37% | Participants28 | EvidenceC | Evaluated |
| Rank10 | ModelAC | Score84.00% | Percentile66.67% | Participants28 | EvidenceC | Evaluated |
| Rank11 | ModelAC | Score83.70% | Percentile62.96% | Participants28 | EvidenceC | Evaluated |
| Rank12 | ModelGO | Score83.60% | Percentile59.26% | Participants28 | EvidenceC | Evaluated |
| Rank13 | ModelOP | Score83.30% | Percentile55.56% | Participants28 | EvidenceC | Evaluated |
| Rank14 | ModelBY | Score82.70% | Percentile51.85% | Participants28 | EvidenceC | Evaluated |
| Rank15 | ModelAC | Score82.30% | Percentile48.15% | Participants28 | EvidenceC | Evaluated |
| Rank16 | ModelAC | Score82.00% | Percentile44.44% | Participants28 | EvidenceC | Evaluated |
| Rank17 | ModelBY | Score80.60% | Percentile40.74% | Participants28 | EvidenceC | Evaluated |
| Rank18 | ModelAC | Score80.40% | Percentile37.04% | Participants28 | EvidenceC | Evaluated |
| Rank19 | ModelAC | Score80.00% | Percentile33.33% | Participants28 | EvidenceC | Evaluated |
| Rank20 | ModelAC | Score79.00% | Percentile29.63% | Participants28 | EvidenceC | Evaluated |
| Rank21 | ModelAC | Score75.00% | Percentile25.93% | Participants28 | EvidenceC | Evaluated |
| Rank22 | ModelAC | Score74.70% | Percentile22.22% | Participants28 | EvidenceC | Evaluated |
| Rank23 | ModelAC | Score72.80% | Percentile18.52% | Participants28 | EvidenceC | Evaluated |
| Rank24 | ModelAC | Score69.40% | Percentile14.81% | Participants28 | EvidenceC | Evaluated |
| Rank25 | ModelAC | Score68.70% | Percentile11.11% | Participants28 | EvidenceC | Evaluated |
| Rank26 | ModelAC | Score65.30% | Percentile7.41% | Participants28 | EvidenceC | Evaluated |
| Rank27 | ModelOP | Score61.20% | Percentile3.70% | Participants28 | EvidenceC | Evaluated |
| Rank28 | ModelAC | Score56.20% | Percentile0.00% | Participants28 | 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.
What is VideoMMMU?
What VideoMMMU measures and how its scores work.
VideoMMMU is a multimodal benchmark containing 300 videos and 900 human-annotated questions spanning Art, Business, Science, Medicine, Humanities, and Engineering.
It measures Large Multimodal Models' ability to acquire knowledge from expert-level professional videos across the cognitive stages of perception, comprehension, and adaptation, reported as a Score in ratio units.
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
- No
- Evaluation key
- overall
LLM Stats. 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 87.60%.
What are the top three models on VideoMMMU?
The current leaders are Gemini 3 Pro (87.60%), Gemini 3 Flash (86.90%), and Kimi K2.5 (86.60%).
Which VideoMMMU model has the lowest official input price?
Gemini 3.1 Flash-Lite has the lowest matched official input price at $0.25 input / $1.5 output per 1M tokens.
Which models are fastest among VideoMMMU results?
The fastest matched records are GPT-4o (132.00 tok/s via OpenAI), GPT-5.2 (100.00 tok/s via OpenAI), and GPT-5 (100.00 tok/s via OpenAI).
Does the highest score result prove overall model quality?
No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.