MedXpertQA-MM
Models answer expert-level medical exam questions that combine images with clinical records and test results. Scoring is accuracy.
This is the multimodal subset of MedXpertQA, which has 4,460 questions in total across its Text and MM subsets.
- Released
- January 2025
- Kind
- Medicine
- Level
- Expert
- Scored
- Checked automatically
- Answers
- Multiple choice
- Tasks
- All public
- Strongest model tested
-
Qwen 3.8 Max #29 on the capability index
- Last in a launch post
- August 2026
- Last model added
- October 2026
- Scores refreshed
- November 12th, 2026
In the authors’ words
We introduce MedXpertQA, a highly challenging and comprehensive benchmark to evaluate expert-level medical knowledge and advanced reasoning. MedXpertQA includes 4,460 questions spanning 17 specialties and 11 body systems. It includes two subsets, Text for text evaluation and MM for multimodal evaluation. Notably, MM introduces expert-level exam questions with diverse images and rich clinical information, including patient records and examination results, setting it apart from traditional medical multimodal benchmarks with simple QA pairs generated from image captions. MedXpertQA applies rigorous filtering and augmentation to address the insufficient difficulty of existing benchmarks like MedQA, and incorporates specialty board questions to improve clinical relevance and comprehensiveness. We perform data synthesis to mitigate data leakage risk and conduct multiple rounds of expert reviews to ensure accuracy and reliability. We evaluate 18 leading models on \benchmark. Moreover, medicine is deeply connected to real-world decision-making, providing a rich and representative setting for assessing reasoning abilities beyond mathematics and code. To this end, we develop a reasoning-oriented subset to facilitate the assessment of o1-like models. Code and data are available at: https://github.com/TsinghuaC3I/MedXpertQA
Qwen 3.8 Max leads with 80.4%
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.
o1 leads with 56.3% across all independent runs
Best score per model across the official leaderboard, Epoch AI’s own runs and any board Epoch AI copied. Each bar and row names its source.
Qwen 3.8 Max leads with 80.4%, claims included
Best score per model from every source, including labs’ own numbers and claims Epoch AI collected from reports and papers. Labs pick their own settings, so a claim can beat an independent run of the same model.
- 80.4
Qwen 3.8 Max
- 79.6
Seed2.0 Lite (0428)
- 78.4
Muse Spark
- 71.0
Qwen3.7-Plus
- 70.0
Qwen3.5 397B-A17B
- 67.3
Qwen3.5-122B-A10B
- 62.4
Qwen3.5-27B
- 61.4
Qwen3.5-35B-A3B
- 61.3
Gemma 4 31B IT
- 58.1
Gemma 4 26B A4B
- 54.7
Qwen3.5-Omni-Plus
- 49.9
Qwen3.5-9B
- 49.0
DiffusionGemma 26B A4B
- 48.7
Gemma 4 12B
- 42.9
Qwen3.5-4B
- 42.1
EXAONE 4.5 33B
- 28.7
Gemma 4 E4B
- 26.9
Qwen3.5-2B
- 26.9
Nemotron 3.5 Bolt E4B
- 23.5
Gemma 4 E2B
- 17.1
Qwen3.5-0.8B
- 1
Qwen 3.8 Max 80.4%
- 2
Seed2.0 Lite (0428) 79.6%
- 3
Muse Spark 78.4%
- 4
Qwen3.7-Plus 71%
- 5
Qwen3.5 397B-A17B 70%
- 6
Qwen3.5-122B-A10B 67.3%
- 7
Qwen3.5-27B 62.4%
- 8
Qwen3.5-35B-A3B 61.4%
- 9
Gemma 4 31B IT 61.3%
- 10
Gemma 4 26B A4B 58.1%
- 11
Qwen3.5-Omni-Plus 54.7%
- 12
Qwen3.5-9B 49.9%
- 13
DiffusionGemma 26B A4B 49%
- 14
Gemma 4 12B 48.7%
- 15
Qwen3.5-4B 42.9%
- 16
EXAONE 4.5 33B 42.1%
- 17
Gemma 4 E4B 28.7%
- 18
Qwen3.5-2B 26.9%
- 19
Nemotron 3.5 Bolt E4B 26.9%
- 20
Gemma 4 E2B 23.5%
- 21
Qwen3.5-0.8B 17.1%
Source: Labs’ model cards
- 1 o1 56.3%
- 2 GPT-4o Aug 2024 42.8%
- 3
Gemini 2.0 Flash Dec 2024 37.2%
- 4
Gemini 1.5 Pro May 2024 34.1%
- 5
QVQ-72B-Preview 33.5%
- 6 Claude 3.5 Sonnet 33.2%
- 7
Qwen2.5-VL-72B 29.9%
- 8 Qwen2-VL-72B-Instruct 28.4%
- 9 GPT-4o mini 28.1%
Source: Official MedXpertQA-MM leaderboard
- 80.4
Qwen 3.8 Max
- 79.6
Seed2.0 Lite (0428)
- 78.4
Muse Spark
- 71.0
Qwen3.7-Plus
- 70.0
Qwen3.5 397B-A17B
- 67.3
Qwen3.5-122B-A10B
- 62.4
Qwen3.5-27B
- 61.4
Qwen3.5-35B-A3B
- 61.3
Gemma 4 31B IT
- 58.1
Gemma 4 26B A4B
- 56.3 o1
- 54.7
Qwen3.5-Omni-Plus
- 49.9
Qwen3.5-9B
- 49.0
DiffusionGemma 26B A4B
- 48.7
Gemma 4 12B
- 42.9
Qwen3.5-4B
- 42.8 GPT-4o
- 42.1
EXAONE 4.5 33B
- 37.2
Gemini 2.0 Flash
- 34.1
Gemini 1.5 Pro
- 33.5
QVQ-72B-Preview
- 33.2 Claude 3.5 Sonnet
- 29.9
Qwen2.5-VL-72B
- 28.7
Gemma 4 E4B
- 28.4 Qwen2-VL-72B-Instruct
- 28.1 GPT-4o mini
- 26.9
Qwen3.5-2B
- 26.9
Nemotron 3.5 Bolt E4B
- 23.5
Gemma 4 E2B
- 17.1
Qwen3.5-0.8B
- 1
Qwen 3.8 Max 80.4%
- 2
Seed2.0 Lite (0428) 79.6%
- 3
Muse Spark 78.4%
- 4
Qwen3.7-Plus 71%
- 5
Qwen3.5 397B-A17B 70%
- 6
Qwen3.5-122B-A10B 67.3%
- 7
Qwen3.5-27B 62.4%
- 8
Qwen3.5-35B-A3B 61.4%
- 9
Gemma 4 31B IT 61.3%
- 10
Gemma 4 26B A4B 58.1%
- 11 o1 56.3%
- 12
Qwen3.5-Omni-Plus 54.7%
- 13
Qwen3.5-9B 49.9%
- 14
DiffusionGemma 26B A4B 49%
- 15
Gemma 4 12B 48.7%
- 16
Qwen3.5-4B 42.9%
- 17 GPT-4o Aug 2024 42.8%
- 18
EXAONE 4.5 33B 42.1%
- 19
Gemini 2.0 Flash Dec 2024 37.2%
- 20
Gemini 1.5 Pro May 2024 34.1%
- 21
QVQ-72B-Preview 33.5%
- 22 Claude 3.5 Sonnet 33.2%
- 23
Qwen2.5-VL-72B 29.9%
- 24
Gemma 4 E4B 28.7%
- 25 Qwen2-VL-72B-Instruct 28.4%
- 26 GPT-4o mini 28.1%
- 27
Qwen3.5-2B 26.9%
- 28
Nemotron 3.5 Bolt E4B 26.9%
- 29
Gemma 4 E2B 23.5%
- 30
Qwen3.5-0.8B 17.1%
Sources: Labs’ model cards and official MedXpertQA-MM leaderboard
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | | 80.4% | Aug 2026 | Lab model card | |
| 2 | | 79.6% | Apr 2026 | Lab model card | |
| 3 | | 78.4% | Apr 2026 | Lab model card | |
| 4 | | 71% | Jun 2026 | Lab model card | |
| 5 | | 70% | Feb 2026 | Lab model card | |
| 6 | | 67.3% | Feb 2026 | Lab model card | |
| 7 | | 62.4% | Feb 2026 | Lab model card | |
| 8 | | 61.4% | Feb 2026 | Lab model card | |
| 9 | | 61.3% | Apr 2026 | Lab model card | |
| 10 | | 58.1% | Apr 2026 | Lab model card | |
| 11 | | 54.7% | Mar 2026 | Lab model card | |
| 12 | | 49.9% | Mar 2026 | Lab model card | |
| 13 | | 49% | Jun 2026 | Lab model card | |
| 14 | | 48.7% | Jun 2026 | Lab model card | |
| 15 | | 42.9% | Mar 2026 | Lab model card | |
| 16 | | 42.1% | Apr 2026 | Lab model card | |
| 17 | | 28.7% | Apr 2026 | Lab model card | |
| 18 | | 26.9% | Mar 2026 | Lab model card | |
| 19 | | 26.9% | Oct 2026 | Lab model card | |
| 20 | | 23.5% | Apr 2026 | Lab model card | |
| 21 | | 17.1% | Mar 2026 | Lab model card |
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | o1 | 56.3% | Dec 2024 | Official leaderboard | |
| 2 | GPT-4o Aug 2024 | 42.8% | Aug 2024 | Official leaderboard | |
| 3 | | 37.2% | Dec 2024 | Official leaderboard | |
| 4 | | 34.1% | May 2024 | Official leaderboard | |
| 5 | | 33.5% | Dec 2024 | Official leaderboard | |
| 6 | Claude 3.5 Sonnet | 33.2% | Jun 2024 | Official leaderboard | |
| 7 | | 29.9% | Jan 2025 | Official leaderboard | |
| 8 | Qwen2-VL-72B-Instruct | 28.4% | Aug 2024 | Official leaderboard | |
| 9 | GPT-4o mini | 28.1% | Jul 2024 | Official leaderboard |
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | | 80.4% | Aug 2026 | Lab model card | |
| 2 | | 79.6% | Apr 2026 | Lab model card | |
| 3 | | 78.4% | Apr 2026 | Lab model card | |
| 4 | | 71% | Jun 2026 | Lab model card | |
| 5 | | 70% | Feb 2026 | Lab model card | |
| 6 | | 67.3% | Feb 2026 | Lab model card | |
| 7 | | 62.4% | Feb 2026 | Lab model card | |
| 8 | | 61.4% | Feb 2026 | Lab model card | |
| 9 | | 61.3% | Apr 2026 | Lab model card | |
| 10 | | 58.1% | Apr 2026 | Lab model card | |
| 11 | o1 | 56.3% | Dec 2024 | Official leaderboard | |
| 12 | | 54.7% | Mar 2026 | Lab model card | |
| 13 | | 49.9% | Mar 2026 | Lab model card | |
| 14 | | 49% | Jun 2026 | Lab model card | |
| 15 | | 48.7% | Jun 2026 | Lab model card | |
| 16 | | 42.9% | Mar 2026 | Lab model card | |
| 17 | GPT-4o Aug 2024 | 42.8% | Aug 2024 | Official leaderboard | |
| 18 | | 42.1% | Apr 2026 | Lab model card | |
| 19 | | 37.2% | Dec 2024 | Official leaderboard | |
| 20 | | 34.1% | May 2024 | Official leaderboard | |
| 21 | | 33.5% | Dec 2024 | Official leaderboard | |
| 22 | Claude 3.5 Sonnet | 33.2% | Jun 2024 | Official leaderboard | |
| 23 | | 29.9% | Jan 2025 | Official leaderboard | |
| 24 | | 28.7% | Apr 2026 | Lab model card | |
| 25 | Qwen2-VL-72B-Instruct | 28.4% | Aug 2024 | Official leaderboard | |
| 26 | GPT-4o mini | 28.1% | Jul 2024 | Official leaderboard | |
| 27 | | 26.9% | Mar 2026 | Lab model card | |
| 28 | | 26.9% | Oct 2026 | Lab model card | |
| 29 | | 23.5% | Apr 2026 | Lab model card | |
| 30 | | 17.1% | Mar 2026 | Lab model card |
The benchmark's own leaderboard has 9 models. Switch the scores above to rank them together.
4 models have held number one in labs’ own numbers since its release in January 2025 Number one over time 5 models have held number one with claims included since its release in January 2025
Lab claims count from the day the card came out, independent runs from the model’s release. We draw one row each for the benchmark’s own leaderboard and what labs claim in their cards.
Sources: Official MedXpertQA-MM leaderboard and labs’ model cards
Scores over time
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Sources: Official MedXpertQA-MM leaderboard and labs’ model cards
2 labs put it in a launch post in the last six months
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 | 80.4 | MedXpertQA-MM | |
| Jun 10, 2026 | 49 | MedXPertQA MM | |
| Jun 3, 2026 | 48.7 | MedXPertQA MM | |
| Jun 1, 2026 | 71 | MedXpertQA-MM | |
| Apr 28, 2026 | 79.6 | MedXpertQA-MM | |
| Apr 9, 2026 | 42.1 | MedXpertQA-MM | |
| Apr 8, 2026 | 78.4 | MedXpertQA (MM) | |
| Apr 2, 2026 | 28.7 | MedXPertQA MM | |
| Apr 2, 2026 | 23.5 | MedXPertQA MM | |
| Apr 2, 2026 | 58.1 | MedXPertQA MM | |
| Apr 2, 2026 | 61.3 | MedXPertQA MM | |
| Mar 30, 2026 | 54.7 | MedXpertQA-MM | |
| Mar 2, 2026 | 17.1 | MedXpertQA-MM 17.1/25.3 (with CI / without CI) | |
| Mar 2, 2026 | 26.9 | MedXpertQA-MM 26.9/19.1 (with CI / without CI) | |
| Mar 2, 2026 | 42.9 | MedXpertQA-MM | |
| Mar 2, 2026 | 49.9 | MedXpertQA-MM | |
| Feb 24, 2026 | 61.4 | MedXpertQA-MM | |
| Feb 24, 2026 | 62.4 | MedXpertQA-MM | |
| Feb 24, 2026 | 67.3 | MedXpertQA-MM | |
| Feb 16, 2026 | 70 | MedXpertQA-MM |
7 system cards report it, from 4 labs
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 |
|---|---|---|---|---|
| Oct 23, 2026 | | 26.9 | MedXpertQA Vision, reasoning, 23.10 non-reasoning (Table 8) | Health |
| Jul 24, 2026 | | 28.7 | MedXPertQA MM, max resolution, thinking (Table 6) | Capabilities |
| Jul 24, 2026 | | 23.5 | MedXPertQA MM, max resolution, thinking (Table 6) | Capabilities |
| Jul 24, 2026 | | 61.3 | MedXPertQA MM, thinking, max resolution (Table 6) | Capabilities |
| Jul 24, 2026 | | 58.1 | MedXPertQA MM, thinking, max resolution (Table 6) | Capabilities |
| Apr 17, 2026 | | 54.7 | MedXpertQA-MM (Table 6) | Health |
| Apr 9, 2026 | | 42.1 | MedXpertQA-MM (Table 2, Reasoning mode) | Health |
More in Law, finance and medicine
- 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%
- Legal Research Bench In use Agents answer US federal and state legal research questions with case-law and web tools. Expert rubrics, all-pass and weighted scores by LLM judge.
Gemini 4 Carbon 55.8%