multimodal benchmark
Video-MME (long, no subtitles)
Video-MME is the first-ever comprehensive evaluation benchmark for Multi-modal Large Language Models (MLLMs) in video analysis. This variant focuses on long-term videos (30min-60min) without subtitle inputs, testing robust contextual dynamics across 6 primary visual domains with 30 subfields including knowledge, film & television, sports competition, life record, and multilingual content.
Updated Aug 11, 2026
Models1
Model coverage1
MetricScore
EvidenceB
Video-MME (long, no subtitles) Ranking
Higher score ranks better on this benchmark.
| 01 | OP | 72.0% | 100.0% | 1 | C |
Video-MME (long, no subtitles) Highlights
The leading models and scores on this benchmark.
What is Video-MME (long, no subtitles)?
What Video-MME (long, no subtitles) measures and how its scores work.
Video-MME is the first-ever comprehensive evaluation benchmark for Multi-modal Large Language Models (MLLMs) in video analysis. This variant focuses on long-term videos (30min-60min) without subtitle inputs, testing robust contextual dynamics across 6 primary visual domains with 30 subfields including knowledge, film & television, sports competition, life record, and multilingual content.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- Video-MME (long, no subtitles)
- Modality
- multimodal
- Primary category
- multimodal
- Score direction
- higher
- LLMBoard eligible
- No
- Evaluation key
- video-mme-(long,-no-subtitles)|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about Video-MME (long, no subtitles).
Which model scores highest on Video-MME (long, no subtitles)?
GPT-4.1 is currently ranked first with 72.0%.
What does Video-MME (long, no subtitles) measure?
Video-MME is the first-ever comprehensive evaluation benchmark for Multi-modal Large Language Models (MLLMs) in video analysis. This variant focuses on long-term videos (30min-60min) without subtitle inputs, testing robust contextual dynamics across 6 primary visual domains with 30 subfields including knowledge, film & television, sports competition, life record, and multilingual content.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
1 model results are currently shown.
Does this benchmark affect the overall score?
No. This benchmark is shown for reference but does not contribute to the overall score.