OpenVLM Q-Bench - Yes-or-No (Others): leaderboard

Q-Bench accuracy on yes-or-no questions about other image-wide low-level attributes such as colour, lighting or clarity, 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
1InternVL3-14B79.4#506
2Qwen 2 VL 72B78.9#450
3InternVL3-8B78.3#624
4InternVL3-78B78.3#361
5GPT-4.1 (2025-04-14)78.3#257
6MiniCPM-V-2.678.3#827
7Qwen 2 VL 7B77.7#743
8Moonshot v1 8K77.1#622
9GPT-4.1 Mini76.6#363
10Qwen 2 VL 2B76.6#1191
11Pixtral-12B76#805
12InternVL3-38B74.9#413
13Qwen 2.5 VL 7B74.9#641
14InternVL2-8B74.3#813
15Gemini 1.5 Flash72.6#620

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-yes-or-no-others · How It Works · Data refreshed daily, snapshot 2026-11-05.