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multimodal benchmark

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.

Updated Aug 11, 2026

Models10
Model coverage10
MetricScore
EvidenceB

On this page

  • Ranking
  • Distribution
  • Highlights
  • About
  • FAQ

VideoMME w/o sub. Ranking

Higher score ranks better on this benchmark.

10 rows
Columns

Show columns

01ACQwen3.5-122B-A10BAlibaba Cloud / Qwen Team83.9%100.0%10CAug 11, 2026
02ACQwen3.5-27BAlibaba Cloud / Qwen Team82.8%88.9%10CAug 11, 2026
03ACQwen3.5-35B-A3BAlibaba Cloud / Qwen Team82.5%77.8%10CAug 11, 2026
04ACQwen3.6-35B-A3BAlibaba Cloud / Qwen Team82.5%66.7%10CAug 11, 2026
05ACQwen3 VL 235B A22B InstructAlibaba Cloud / Qwen Team79.2%55.6%10CAug 11, 2026
06ACQwen3 VL 235B A22B ThinkingAlibaba Cloud / Qwen Team79.0%44.4%10CAug 11, 2026
07ACQwen3 VL 32B ThinkingAlibaba Cloud / Qwen Team77.3%33.3%10CAug 11, 2026
08ACQwen2.5 VL 72B InstructAlibaba Cloud / Qwen Team73.3%22.2%10CAug 11, 2026
09ACQwen2.5 VL 32B InstructAlibaba Cloud / Qwen Team70.5%11.1%10CAug 11, 2026
10ACQwen2.5 VL 7B InstructAlibaba Cloud / Qwen Team65.1%0.0%10CAug 11, 2026

VideoMME w/o sub. Score Distribution

A closer view of the leading scores on this benchmark.

VideoMME w/o sub.

VideoMME w/o sub. Highlights

The leading models and scores on this benchmark.

Rank #1Qwen3.5-122B-A10B83.9%Rank #2Qwen3.5-27B82.8%Rank #3Qwen3.5-35B-A3B82.5%Rank #4Qwen3.6-35B-A3B82.5%

What is VideoMME w/o sub.?

What VideoMME w/o sub. measures and how its scores work.

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.

Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.

Family
VideoMME w/o sub.
Modality
multimodal
Primary category
multimodal
Score direction
higher
LLMBoard eligible
Yes
Evaluation key
videomme-w-o-sub.|llm-stats-current

Benchmark scores retain their original unit. Overall score eligibility is shown separately.

FAQ

Common questions about VideoMME w/o sub..

Which model scores highest on VideoMME w/o sub.?

Qwen3.5-122B-A10B is currently ranked first with 83.9%.

What does VideoMME w/o sub. measure?

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.

Is a higher score better?

Yes. Higher values rank better for this benchmark.

How many models are compared?

10 model results are currently shown.

Does this benchmark affect the overall score?

Yes. This benchmark can contribute to the current LLMBoard capability score.