VirtueBench (256 Frames): leaderboard

Metric: Accuracy (%) over VirtueBench's 1,180 open-ended long-video questions answered from 256 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. 23 models tracked.

Top models

#ModelScoreOverall rank
1GPT-559.56#91
2Gemini 2.5 Flash57.71#237
3GPT-5 Chat52.3#233
4GPT-4o49.83#333
5Qwen 3 VL 32B Instruct46.69#276
6Qwen 3 VL 32B (Thinking)45.51#287 (Qwen 3 VL 32B)
7Qwen 3 VL 8B Instruct39.83#401
8Qwen 2.5 VL 72B Instruct39.66#364
9Qwen 3 VL 8B (Thinking)38.14
10Qwen 2.5 VL 32B Instruct37.46#443
11Qwen 2.5 VL 7B Instruct36.53#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-256-frames · How It Works · Data refreshed daily, snapshot 2026-10-11.