MedQ-Deg - Treatment Reasoning: leaderboard

Metric: Accuracy (%) on the Treatment 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-578.8#91
2Gemini 2.5 Pro59.6#145
3Claude Sonnet 4.553.9#138
4GPT-4o46.1#333
5Gemini 2.5 Flash46.1#237
6GPT-4.142.3#240
7GPT-4.1 Mini40.4#346
8GPT-5.138.5#131
9Gemma 3 4B26.9#1084
10MedGemma-4B25#731
11Gemma 3 27B19.2#596
12Mistral Small 3.119.2#600
13Qwen 3 VL 30B A3B Instruct19.2#365
14GPT-4o Mini15.4#588
15Qwen 3 VL 235B A22B Instruct15.4#264

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