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.
9rows
scoreprimary metric
2026-05-06sampled
Metadata
Metrics
Score, Normalized Score
| Rank | Subject | Score | Model Match | Provenance | Sampled |
|---|---|---|---|---|---|
| 1 | Qwen3.6-27B | 0.88 |  Qwen3.6 27B qwen-qwen3.6-27b | Self-reported | 2026-05-06 |
| 2 | Qwen3.5-122B-A10B | 0.87 | Qwen3.5-122B-A10B qwen-qwen3.5-122b-a10b | Self-reported | 2026-05-06 |
| 3 | Qwen3.5-27B | 0.87 | Qwen3.5-27B qwen-qwen3.5-27b | Self-reported | 2026-05-06 |
| 4 | GPT-5 | 0.87 |  GPT-5 openai-gpt-5 | Self-reported | 2026-05-06 |
| 5 | Qwen3.5-35B-A3B | 0.87 | Qwen3.5-35B-A3B qwen-qwen3.5-35b-a3b | Self-reported | 2026-05-06 |
| 5 | Qwen3.6-35B-A3B | 0.87 | Qwen3.6 35B A3B qwen-qwen3.6-35b-a3b | Self-reported | 2026-05-06 |
| 7 | Qwen2.5 VL 32B Instruct | 0.78 | — | Self-reported | 2026-05-06 |
| 8 | Qwen2.5-Omni-7B | 0.72 | — | Self-reported | 2026-05-06 |
| 9 | Qwen2.5 VL 7B Instruct | 0.72 | — | Self-reported | 2026-05-06 |
No matching rows.