VideoMME w sub.
The first-ever comprehensive evaluation benchmark of Multi-modal LLMs in Video analysis. Features 900 videos (254 hours) with 2,700 question-answer pairs covering 6 primary visual domains and 30 subfields. Evaluates temporal understanding across short (11 seconds) to long (1 hour) videos with multi-modal inputs including video frames, subtitles, and audio.
Qwen3.6-27B from Alibaba Cloud / Qwen Team currently leads the VideoMME w sub. leaderboard with a score of 0.877 across 9 evaluated AI models.
Qwen3.6-27B leads with 87.7%, followed by Qwen3.5-122B-A10B at 87.3% and Qwen3.5-27B at 87.0%.
Progress Over Time
Interactive timeline showing model performance evolution on VideoMME w sub.
VideoMME w sub. Leaderboard
| Context | Cost | License | ||||
|---|---|---|---|---|---|---|
| 1 |  Alibaba Cloud / Qwen Team | 28B | 262K | $0.60 / $3.60 | ||
| 2 | Alibaba Cloud / Qwen Team | 122B | 262K | $0.40 / $3.20 | ||
| 3 | Alibaba Cloud / Qwen Team | 27B | 262K | $0.30 / $2.40 | ||
| 4 |  OpenAI | — | — | — | ||
| 5 | Alibaba Cloud / Qwen Team | 35B | 262K | $0.25 / $2.00 | ||
| 5 | Alibaba Cloud / Qwen Team | 35B | — | — | ||
| 7 | Alibaba Cloud / Qwen Team | 34B | — | — | ||
| 8 | Alibaba Cloud / Qwen Team | 7B | — | — | ||
| 9 | Alibaba Cloud / Qwen Team | 8B | — | — |
FAQ
Common questions about VideoMME w sub..
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