OpenVLM Q-Bench - How (Distortion): leaderboard

Q-Bench accuracy on how questions about image-wide distortions such as blur, noise or exposure, 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 Mini68.2#363
2Gemma 3 27B68.2#606
3InternVL3-78B65.9#361
4GPT-4.1 (2025-04-14)65.3#257
5Gemma 3 12B65.3#674
6MiniCPM-V-2.664.8#827
7Qwen 2.5 VL 7B64.8#641
8Gemini 1.5 Flash64.8#620
9Qwen 2 VL 7B64.2#743
10Qwen 2 VL 72B63.6#450
11GPT-4.1 Nano62.5#730
12InternVL3-38B62.5#413
13Llama 3.2 11B Instruct62.5#1108
14InternVL3-8B61.9#624
15InternVL3-14B61.9#506

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-how-distortion · How It Works · Data refreshed daily, snapshot 2026-11-05.