MedQ-Deg - Artifact Degradation: leaderboard

Metric: Accuracy (%) on MedQ-Deg items whose images carry imaging-artifact (for example MRI undersampling and sparse-view CT) degradations, pooled over the L1 (mild) and L2 (severe) severities, 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 June 2028. 40 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 2.5 Pro65.1#145
2Qwen 3 VL 235B A22B Instruct63.3#264
3GPT-563.1#91
4Qwen 3 VL 30B A3B Instruct61.4#365
5Gemini 2.5 Flash60.7#237
6GPT-4.160.6#240
7GPT-4.1 Mini60.5#346
8GPT-5.160.5#131
9GPT-4o58.3#333
10GLM-4.5V57.2#339
11Claude Sonnet 4.555.2#138
12Qwen 2.5 VL 72B Instruct53.6#364
13Qwen 2 VL 7B Instruct53#816
14Qwen 2.5 VL 32B Instruct52.3#443
15Gemma 3 27B51.4#596

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-artifact-degradation · How It Works · Data refreshed daily, snapshot 2026-10-11.