MedQ-Deg - Diagnostic Reasoning: leaderboard

Metric: Accuracy (%) on the Diagnosis questions of MedQ-Deg (capability dimension of the clinical reasoning 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
1GPT-562.1#91
2Gemini 2.5 Pro60.1#145
3GPT-5.147#131
4GPT-4.1 Mini44.4#346
5Gemini 2.5 Flash38.9#237
6GPT-4.138.4#240
7GPT-4o37.4#333
8Claude Sonnet 4.535.9#138
9Mistral Small 3.133.8#600
10Qwen 2.5 VL 32B Instruct32.3#443
11GLM-4.5V32.3#339
12Qwen 3 VL 30B A3B Instruct30.3#365
13Qwen 3 VL 235B A22B Instruct29.8#264
14GPT-4o Mini29.3#588
15Qwen 2.5 VL 72B Instruct28.8#364

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-diagnostic-reasoning · How It Works · Data refreshed daily, snapshot 2026-10-11.