OpenVLM Q-Bench - How (In-context Others): leaderboard
Q-Bench accuracy on how questions about other low-level attributes 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
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | InternVL3-78B | 82.4 | #361 |
| 2 | InternVL3-38B | 81.2 | #413 |
| 3 | InternVL3-14B | 81.2 | #506 |
| 4 | Qwen 2 VL 72B | 81.2 | #450 |
| 5 | GPT-4.1 Mini | 80 | #363 |
| 6 | Gemma 3 12B | 80 | #674 |
| 7 | Qwen 2.5 VL 7B | 78.8 | #641 |
| 8 | Moonshot v1 8K | 78.8 | #622 |
| 9 | InternVL3-8B | 77.6 | #624 |
| 10 | GPT-4.1 (2025-04-14) | 77.6 | #257 |
| 11 | MiniCPM-V-2.6 | 77.6 | #827 |
| 12 | Pixtral-12B | 77.6 | #805 |
| 13 | Aquila-VL-2B | 77.6 | #1216 |
| 14 | Gemini 1.5 Flash | 77.6 | #620 |
| 15 | InternVL2-8B | 75.3 | #813 |
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-in-context-others · How It Works · Data refreshed daily, snapshot 2026-11-05.