DermoBench - OOD Diagnosis - Derm1M: leaderboard

Out-of-distribution skin-lesion diagnosis on the Derm1M educational split, part of DermoBench (DermoGPT paper, Ru et al., 2026): four-option multiple-choice questions written in the dataset's own label space rather than the benchmark's unified ontology. Accuracy in percent; higher is better.

Metric: Accuracy (%; 4-way MCQA in the source dataset's own label space, out-of-distribution). Source: arxiv.org. Saturation forecast: Around February 2027. 18 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 2.5 Flash66.33#452
2QVQ-72B-Preview60.53#1173
3Qwen 2.5 VL 72B Instruct54.63#845
4Claude Sonnet 4.5 (Thinking)53.64#244 (Claude Sonnet 4.5)
5Qwen 3 VL 8B Instruct52.67#982
6GPT-4o Mini52.12#1627
7GLM-4.5V45.51#739
8Llama 3.2 90B44.76#1740
9Nemotron Nano 12B v2 VL44.12#2248
10Llama 3.2 11B25.5#6434

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=dermobench-ood-diagnosis-derm1m · How It Works · Data refreshed daily, snapshot 2026-11-12.