OpenVLM A-Bench - Attribute Awareness: leaderboard

A-Bench Attribute Awareness accuracy from the OpenCompass OpenVLM Leaderboard (VLMEvalKit): multiple-choice questions on AI-generated images, checking whether object attributes such as colour or material match the image. A dimension of A-Bench-P1 (high-level semantic understanding). Accuracy in percent, higher is better.

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

Top models

#ModelScoreOverall rank
1InternVL3-78B96.4#361
2Qwen 2 VL 72B96.4#450
3InternVL3-38B95.5#413
4Gemini 1.5 Pro95.5#454
5GPT-4.1 (2025-04-14)93.6#257
6InternVL3-8B92.7#624
7Pixtral-12B92.7#805
8Qwen 2 VL 7B91.8#743
9Grok 2 (1212)91.8#502
10GPT-4.1 Mini90.9#363
11MiniCPM-V-2.690.9#827
12Gemma 3 27B90.9#606
13Qwen 2 VL 2B90.9#1191
14InternVL3-14B90#506
15Claude 3.7 Sonnet90#259

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

Interactive version: theaggregate.ai/benchmark?slug=openvlm-a-bench-attribute-awareness · How It Works · Data refreshed daily, snapshot 2026-11-05.