VideoMME w/o sub.
Video-MME is a comprehensive evaluation benchmark for multi-modal large language models in video analysis. It features 900 videos across 6 primary visual domains with 30 subfields, ranging from 11 seconds to 1 hour in duration, with 2,700 question-answer pairs. The benchmark evaluates MLLMs' capabilities in processing sequential visual data and multi-modal content including video frames, subtitles, and audio.
10rows
scoreprimary metric
2026-05-06sampled
Metadata
Metrics
Score, Normalized Score
| Rank | Subject | Score | Model Match | Provenance | Sampled |
|---|---|---|---|---|---|
| 1 | Qwen3.5-122B-A10B | 0.84 |  Qwen3.5-122B-A10B qwen-qwen3.5-122b-a10b | Self-reported | 2026-05-06 |
| 2 | Qwen3.5-27B | 0.83 | Qwen3.5-27B qwen-qwen3.5-27b | Self-reported | 2026-05-06 |
| 3 | Qwen3.6-35B-A3B | 0.82 | Qwen3.6 35B A3B qwen-qwen3.6-35b-a3b | Self-reported | 2026-05-06 |
| 3 | Qwen3.5-35B-A3B | 0.82 | Qwen3.5-35B-A3B qwen-qwen3.5-35b-a3b | Self-reported | 2026-05-06 |
| 5 | Qwen3 VL 235B A22B Instruct | 0.79 | Qwen3 VL 235B A22B Instruct qwen-qwen3-vl-235b-a22b-instruct | Self-reported | 2026-05-06 |
| 6 | Qwen3 VL 235B A22B Thinking | 0.79 | Qwen3 VL 235B A22B Thinking qwen-qwen3-vl-235b-a22b-thinking | Self-reported | 2026-05-06 |
| 7 | Qwen3 VL 32B Thinking | 0.77 | — | Self-reported | 2026-05-06 |
| 8 | Qwen2.5 VL 72B Instruct | 0.73 | Qwen2.5 VL 72B Instruct qwen-qwen2.5-vl-72b-instruct | Self-reported | 2026-05-06 |
| 9 | Qwen2.5 VL 32B Instruct | 0.70 | — | Self-reported | 2026-05-06 |
| 10 | Qwen2.5 VL 7B Instruct | 0.65 | — | Self-reported | 2026-05-06 |
No matching rows.