long context benchmark
LVBench
LVBench is an extreme long video understanding benchmark designed to evaluate multimodal models on videos up to two hours in duration. It contains 6 major categories and 21 subcategories, with videos averaging five times longer than existing datasets. The benchmark addresses applications requiring comprehension of extremely long videos.
Updated Aug 11, 2026
Models24
Model coverage24
MetricScore
EvidenceB
LVBench Ranking
Higher score ranks better on this benchmark.
LVBench Score Distribution
A closer view of the leading scores on this benchmark.
LVBench Highlights
The leading models and scores on this benchmark.
What is LVBench?
What LVBench measures and how its scores work.
LVBench is an extreme long video understanding benchmark designed to evaluate multimodal models on videos up to two hours in duration. It contains 6 major categories and 21 subcategories, with videos averaging five times longer than existing datasets. The benchmark addresses applications requiring comprehension of extremely long videos.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- LVBench
- Modality
- multimodal
- Primary category
- long context
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- lvbench|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about LVBench.
Which model scores highest on LVBench?
Qwen3.8 Max is currently ranked first with 81.8%.
What does LVBench measure?
LVBench is an extreme long video understanding benchmark designed to evaluate multimodal models on videos up to two hours in duration. It contains 6 major categories and 21 subcategories, with videos averaging five times longer than existing datasets. The benchmark addresses applications requiring comprehension of extremely long videos.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
24 model results are currently shown.
Does this benchmark affect the overall score?
Yes. This benchmark can contribute to the current LLMBoard capability score.