VirtueBench (128 Frames): leaderboard

Metric: Accuracy (%) over VirtueBench's 1,191 open-ended long-video questions answered from 128 uniformly sampled frames (at most 512x512 pixels), each with a reference answer for that frame level: an answerable question counts when a GPT-4o judge finds the answer consistent with the reference, an unanswerable one only when the model says the frames lack the information; the prompt tells the model not to guess; higher is better. Source: arxiv.org. Saturation forecast: Around January 2027. 25 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 2.5 Flash57.18#237
2GPT-553.76#91
3GPT-4o52.83#333
4Qwen 3 VL 32B Instruct50.63#276
5GPT-5 Chat47.84#233
6Qwen 3 VL 32B (Thinking)45.76#287 (Qwen 3 VL 32B)
7Qwen 2.5 VL 72B Instruct45#364
8Qwen 3 VL 8B (Thinking)40.3
9Qwen 3 VL 8B Instruct37.62#401
10Qwen 2.5 VL 32B Instruct37.53#443
11Qwen 2.5 VL 7B Instruct35.1#643

No result here: #3 Claude Opus 5.5, #5 GPT-6 Astra, #8 Claude Fable 5.1.

Interactive version: theaggregate.ai/benchmark?slug=virtuebench-128-frames · How It Works · Data refreshed daily, snapshot 2026-10-11.