SLAKE
Models answer English and Chinese questions about radiology images of the head, neck, chest, abdomen, and pelvis. Scoring is accuracy.
The authors say the released data was cleaned and may differ slightly from the paper.
- Released
- February 2021
- Kind
- Medicine
- Level
- University
- Scored
- Checked automatically
- Answers
- Short answer
- Tasks
- All public
- Strongest model tested
-
Qwen 3.8 Max #29 on the capability index
- Last in a launch post
- August 2026, dropped after it saturated
- Last model added
- August 2026
In the authors’ words
Medical visual question answering (Med-VQA) has tremendous potential in healthcare. However, the development of this technology is hindered by the lacking of publicly-available and high-quality labeled datasets for training and evaluation. In this paper, we present a large bilingual dataset, SLAKE, with comprehensive semantic labels annotated by experienced physicians and a new structural medical knowledge base for Med-VQA. Besides, SLAKE includes richer modalities and covers more human body parts than the currently available dataset. We show that SLAKE can be used to facilitate the development and evaluation of Med-VQA systems. The dataset can be downloaded from http://www.med-vqa.com/slake.
Qwen 3.8 Max leads with 90.8% among models released by August 2026
Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.
The newest model with a score here came out in August 2026, and nobody has reported a newer one. Among the 20 highest-ranked models on the capability index, these have no score yet:
- Claude Fable 5.2
-
Gemini 4 Carbon
- GPT-6 Astra
- Claude Opus 5.5
- and 16 more
- 1
Qwen 3.8 Max 90.8%
- 2
Qwen3.5-Omni-Plus 84.7%
- 3
Qwen3.5-122B-A10B 81.6%
- 4
Qwen3.5-27B 80%
- 5
Qwen3.5 397B-A17B 79.9%
- 6
Qwen3.5-9B 79%
- 7
Qwen3.5-35B-A3B 78.7%
- 8
Qwen3.5-4B 76.1%
- 9
Qwen3.5-2B 74.4%
- 10
Qwen3.5-0.8B 62.6%
Source: Labs’ model cards
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | | 90.8% | Aug 2026 | Lab model card | |
| 2 | | 84.7% | Mar 2026 | Lab model card | |
| 3 | | 81.6% | Feb 2026 | Lab model card | |
| 4 | | 80% | Feb 2026 | Lab model card | |
| 5 | | 79.9% | Feb 2026 | Lab model card | |
| 6 | | 79% | Mar 2026 | Lab model card | |
| 7 | | 78.7% | Feb 2026 | Lab model card | |
| 8 | | 76.1% | Mar 2026 | Lab model card | |
| 9 | | 74.4% | Mar 2026 | Lab model card | |
| 10 | | 62.6% | Mar 2026 | Lab model card |
4 models have held number one in labs’ own numbers since 2023
Lab claims count from the day the card came out, independent runs from the model’s release.
Source: Labs’ model cards
Qwen’s own number for Qwen 3.8 Max passed 85% in August 2026
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Source: Labs’ model cards
Labs headline it less often now, last in August 2026
Launch posts from every lab that has listed it, one tick per post. Tall colored ticks include it, and short gray ones leave it out.
| Date | Launch post | Score | As the post writes it |
|---|---|---|---|
| Aug 3, 2026 | 90.8 | SLAKE | |
| Mar 30, 2026 | 84.7 | SLAKE | |
| Mar 2, 2026 | 62.6 | SLAKE 62.6/59.5 (with CI / without CI) | |
| Mar 2, 2026 | 74.4 | SLAKE 74.4/67.5 (with CI / without CI) | |
| Mar 2, 2026 | 76.1 | SLAKE | |
| Mar 2, 2026 | 79 | SLAKE | |
| Feb 24, 2026 | 78.7 | SLAKE | |
| Feb 24, 2026 | 80 | SLAKE | |
| Feb 24, 2026 | 81.6 | SLAKE | |
| Feb 16, 2026 | 79.9 | SLAKE |
One system card reports it
Besides launch posts, we read the system cards, model cards and technical reports labs publish with a release. They report far more, including safety and frontier-risk tests.
| Date | Document | Score | As the document writes it | Section |
|---|---|---|---|---|
| Apr 17, 2026 | | 84.7 | SLAKE (Table 6) | Health |
More in Law, finance and medicine
- MedXpertQA-MM In use Models answer expert-level medical exam questions that combine images with clinical records and test results. Scoring is accuracy.
Qwen 3.8 Max 80.4%
- HealthBench Professional In use 525 physician-authored tasks from real clinician chats (care consult, documentation, research) with physician-adjudicated rubrics. Claude Sonnet 5.5 69.2%
- HealthBench In use 5,000 realistic health conversations graded against physician-written rubrics. A length-adjusted variant penalizes verbosity. GPT-5 67.2%
- FinSearchComp In use Agents search the web to fetch live financial data, look up history, and run multi-step investigations, across 635 expert-written questions. Scored by answer accuracy.
Ling-3.1-flash 81.7%
- KBL In use Models answer Korean legal knowledge and reasoning tasks and Korean bar exam questions. It has 7 knowledge tasks, 4 reasoning tasks and 2,510 bar exam items.
Solar Pro 4 77.5%
- KorMedMCQA In use Models answer 7,469 multiple-choice questions from Korean licensing exams for doctors, nurses, pharmacists and dentists, held from 2012 to 2024.
Solar Pro 4 93.2%