long context benchmark
EgoSchema
A diagnostic benchmark for very long-form video language understanding consisting of over 5000 human curated multiple choice questions based on 3-minute video clips from Ego4D, covering a broad range of natural human activities and behaviors
Updated Aug 11, 2026
Models9
Model coverage9
MetricScore
EvidenceB
EgoSchema Ranking
Higher score ranks better on this benchmark.
| 01 | AC | 77.9% | 100.0% | 9 | C | |
| 02 | AC | 76.2% | 87.5% | 9 | C | |
| 03 | OP | 72.2% | 75.0% | 9 | C | |
| 04 | AM Nova ProAmazon | 72.1% | 62.5% | 9 | C | |
| 05 | GO | 71.5% | 50.0% | 9 | C | |
| 06 | AMNova LiteAmazon | 71.4% | 37.5% | 9 | C | |
| 07 | AC | 68.6% | 25.0% | 9 | C | |
| 08 | GO | 67.2% | 12.5% | 9 | C | |
| 09 | GO | 55.7% | 0.0% | 9 | C |
EgoSchema Score Distribution
A closer view of the leading scores on this benchmark.
EgoSchema Highlights
The leading models and scores on this benchmark.
What is EgoSchema?
What EgoSchema measures and how its scores work.
A diagnostic benchmark for very long-form video language understanding consisting of over 5000 human curated multiple choice questions based on 3-minute video clips from Ego4D, covering a broad range of natural human activities and behaviors
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- EgoSchema
- Modality
- video
- Primary category
- long context
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- egoschema|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about EgoSchema.
Which model scores highest on EgoSchema?
Qwen2-VL-72B-Instruct is currently ranked first with 77.9%.
What does EgoSchema measure?
A diagnostic benchmark for very long-form video language understanding consisting of over 5000 human curated multiple choice questions based on 3-minute video clips from Ego4D, covering a broad range of natural human activities and behaviors
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
9 model results are currently shown.
Does this benchmark affect the overall score?
Yes. This benchmark can contribute to the current LLMBoard capability score.