OpenVLM Q-Bench - What (In-context Distortion): leaderboard

Q-Bench accuracy on what and which questions about distortions of a particular object or region, from the OpenCompass OpenVLM Leaderboard (VLMEvalKit) on the Q-Bench dev split. Q-Bench probes low-level visual perception; each of its twelve question-type by concern cells holds 70-188 of the 1,495 dev questions. Accuracy in percent, higher is better.

Metric: Accuracy (%). Source: huggingface.co. Saturation forecast: Estimated already saturated. 160 models tracked.

Top models

#ModelScoreOverall rank
1GPT-4.1 Mini92#363
2GPT-4.1 (2025-04-14)92#257
3InternVL3-78B91#361
4InternVL3-38B88#413
5Qwen 2 VL 72B87#450
6Moonshot v1 8K86#622
7InternVL3-14B85#506
8Qwen 2.5 VL 7B83#641
9GPT-4.1 Nano80#730
10InternVL3-8B79#624
11MiniCPM-V-2.679#827
12Qwen 2 VL 7B79#743
13Aquila-VL-2B78#1216
14Grok 2 (1212)77#502
15Pixtral-12B76#805

No result here: #3 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.

Interactive version: theaggregate.ai/benchmark?slug=openvlm-q-bench-what-in-context-distortion · How It Works · Data refreshed daily, snapshot 2026-11-05.