SlakeVQA
A semantically-labeled knowledge-enhanced dataset for medical visual question answering. Contains 642 radiology images (CT scans, MRI scans, X-rays) covering five body parts and 14,028 bilingual English-Chinese question-answer pairs annotated by experienced physicians. Features comprehensive semantic labels and a structural medical knowledge base with both vision-only and knowledge-based questions requiring external medical knowledge reasoning.
Qwen3.5-122B-A10B from Alibaba Cloud / Qwen Team currently leads the SlakeVQA leaderboard with a score of 0.816 across 4 evaluated AI models.
Qwen3.5-122B-A10B leads with 81.6%, followed by Qwen3.5-27B at 80.0% and Qwen3.5-35B-A3B at 78.7%.
Progress Over Time
Interactive timeline showing model performance evolution on SlakeVQA
SlakeVQA Leaderboard
| Context | Cost | License | ||||
|---|---|---|---|---|---|---|
| 1 |  Alibaba Cloud / Qwen Team | 122B | 262K | $0.40 / $3.20 | ||
| 2 | Alibaba Cloud / Qwen Team | 27B | 262K | $0.30 / $2.40 | ||
| 3 | Alibaba Cloud / Qwen Team | 35B | 262K | $0.25 / $2.00 | ||
| 4 |  Google | 4B | — | — |
FAQ
Common questions about SlakeVQA.
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