MedQ-Deg - Anatomical Recognition: leaderboard

Metric: Accuracy (%) on the Anatomical Recognition questions of MedQ-Deg (capability dimension of the medical perception branch), pooled over the L1 (mild) and L2 (severe) degraded images, multiple-choice medical VQA items merged from OmniMedVQA, GMAI-MMBench and MedXpertQA, each image corrupted by modality-specific degradations whose severity three radiologists calibrated (24,894 QA pairs over 7 modalities and 18 degradation types), single-letter answer, temperature 1.0, mean of 3 runs; higher is better. Source: arxiv.org. Saturation forecast: Around January 2027. 40 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 2.5 Pro72#145
2Gemini 2.5 Flash71.2#237
3GPT-567.4#91
4Qwen 3 VL 235B A22B Instruct66.8#264
5Qwen 3 VL 30B A3B Instruct66.1#365
6GPT-5.165.8#131
7GPT-4.163.8#240
8GPT-4.1 Mini63.5#346
9GPT-4o61.9#333
10GLM-4.5V57.7#339
11Gemma 3 27B55.2#596
12GPT-4o Mini50.4#588
13MedGemma-4B48#731
14Qwen 2.5 VL 72B Instruct44.5#364
15Claude Sonnet 4.544.3#138

No result here: #3 Claude Opus 5.5, #5 GPT-6 Astra, #8 Claude Fable 5.1.

Interactive version: theaggregate.ai/benchmark?slug=medq-deg-anatomical-recognition · How It Works · Data refreshed daily, snapshot 2026-10-11.