VirtueBench (1024 Frames): leaderboard

Metric: Accuracy (%) over VirtueBench's 587 open-ended long-video questions answered from 1024 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. 14 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 2.5 Flash53.66#237
2Qwen 3 VL 32B Instruct32.54#276
3Qwen 2.5 VL 72B Instruct31.52#364
4Qwen 2.5 VL 32B Instruct31.52#443
5Qwen 3 VL 8B Instruct29.98#401
6Qwen 3 VL 32B (Thinking)25.89#287 (Qwen 3 VL 32B)
7Qwen 2.5 VL 7B Instruct25.55#643
8Qwen 3 VL 8B (Thinking)23.34

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

Interactive version: theaggregate.ai/benchmark?slug=virtuebench-1024-frames · How It Works · Data refreshed daily, snapshot 2026-10-11.