video benchmark
ActivityNet Leaderboard
A large-scale video benchmark for human activity understanding. Provides samples from 203 activity classes with an average of 137 untrimmed videos per class and 1.41 activity instances per video, for a total of 849 video hours. The benchmark covers a wide range of complex human activities that are of interest to people in their daily living and can be used to compare algorithms for three scenarios: untrimmed video classification, trimmed activity classification, and activity detection.
Updated Aug 17, 2026
Models1
Model coverage1
MetricScore
EvidenceB
ActivityNet Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelOP | Score61.9% | Percentile100.0% | Participants1 | EvidenceC | Evaluated |
ActivityNet Highlights
The leading models and scores on this benchmark.
The Top AI Models for ActivityNet
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis activitynet AI model leaderboard uses descending score in the benchmark's original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.
- 01OPGPT-4oOpenAI
- Score
- 61.9%
- Price
- $2.5 input / $10 output per 1M tokens
- Speed
- Up to 132 tok/s via OpenAI
Strengths
- Ranks #1 of 1 compared models
- 100th percentile on this benchmark
- C evidence result
Considerations
- This result measures ActivityNet, not total model capability
Selection summary
Best AI Models for ActivityNet
GPT-4o currently leads ActivityNet with 61.9%. It is the top model on this specific benchmark, while the best LLM for the broader task should also be checked against other benchmarks, price and runtime.
Use this leaderboard with the supporting benchmark results and coverage details above. A leaderboard position summarizes the selected ranking signal; it does not replace workload-specific testing.
What is ActivityNet?
What ActivityNet measures and how its scores work.
A large-scale video benchmark for human activity understanding. Provides samples from 203 activity classes with an average of 137 untrimmed videos per class and 1.41 activity instances per video, for a total of 849 video hours. The benchmark covers a wide range of complex human activities that are of interest to people in their daily living and can be used to compare algorithms for three scenarios: untrimmed video classification, trimmed activity classification, and activity detection.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- ActivityNet
- Modality
- video
- Primary category
- video
- Score direction
- higher
- LLMBoard eligible
- No
- Evaluation key
- activitynet|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about ActivityNet.
Which model scores highest on ActivityNet?
GPT-4o is currently ranked first with 61.9%.
What does ActivityNet measure?
A large-scale video benchmark for human activity understanding. Provides samples from 203 activity classes with an average of 137 untrimmed videos per class and 1.41 activity instances per video, for a total of 849 video hours. The benchmark covers a wide range of complex human activities that are of interest to people in their daily living and can be used to compare algorithms for three scenarios: untrimmed video classification, trimmed activity classification, and activity detection.
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.