long context benchmark
LongVideoBench
LongVideoBench is a question-answering benchmark featuring video-language interleaved inputs up to an hour long. It includes 3,763 varying-length web-collected videos with subtitles across diverse themes and 6,678 human-annotated multiple-choice questions in 17 fine-grained categories for comprehensive evaluation of long-term multimodal understanding.
Updated Aug 11, 2026
Models4
Model coverage4
MetricScore
EvidenceB
LongVideoBench Ranking
Higher score ranks better on this benchmark.
| 01 | BY | 80.6% | 100.0% | 4 | C | |
| 02 | BY | 80.6% | 66.7% | 4 | C | |
| 03 | MA | 79.8% | 33.3% | 4 | C | |
| 04 | AC | 54.7% | 0.0% | 4 | C |
LongVideoBench Score Distribution
A closer view of the leading scores on this benchmark.
LongVideoBench Highlights
The leading models and scores on this benchmark.
What is LongVideoBench?
What LongVideoBench measures and how its scores work.
LongVideoBench is a question-answering benchmark featuring video-language interleaved inputs up to an hour long. It includes 3,763 varying-length web-collected videos with subtitles across diverse themes and 6,678 human-annotated multiple-choice questions in 17 fine-grained categories for comprehensive evaluation of long-term multimodal understanding.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- LongVideoBench
- Modality
- multimodal
- Primary category
- long context
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- longvideobench|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about LongVideoBench.
Which model scores highest on LongVideoBench?
Seed 2.1 Pro is currently ranked first with 80.6%.
What does LongVideoBench measure?
LongVideoBench is a question-answering benchmark featuring video-language interleaved inputs up to an hour long. It includes 3,763 varying-length web-collected videos with subtitles across diverse themes and 6,678 human-annotated multiple-choice questions in 17 fine-grained categories for comprehensive evaluation of long-term multimodal understanding.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
4 model results are currently shown.
Does this benchmark affect the overall score?
Yes. This benchmark can contribute to the current LLMBoard capability score.