OpenVLM MTVQA - Arabic: leaderboard

MTVQA Arabic accuracy from the OpenCompass OpenVLM Leaderboard (VLMEvalKit): questions about Arabic text in scene and document images, asked and answered in Arabic. One of the nine language splits of the multilingual text-centric VQA benchmark; accuracy in percent, higher is better.

Metric: Accuracy (%). Source: huggingface.co. Saturation forecast: Estimated already saturated. 157 models tracked.

Top models

#ModelScoreOverall rank
1GPT-4.1 Mini25.7#363
2GPT-4.1 (2025-04-14)23.3#257
3Gemini 1.5 Pro20.6#454
4Claude 3.7 Sonnet20.5#259
5Qwen 2.5 VL 7B17.8#641
6Qwen 2 VL 7B16.2#743
7InternVL3-78B15.9#361
8InternVL3-38B15.8#413
9Qwen 2 VL 72B15.5#450
10Gemma 3 27B15.4#606
11Gemini 1.5 Flash14.7#620
12GPT-4.1 Nano13.7#730
13InternVL3-14B13.2#506
14Gemma 3 12B11.7#674
15InternVL3-8B9.8#624

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

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