DermoBench - OOD Diagnosis - SNU134: leaderboard
Out-of-distribution skin-lesion diagnosis on the SNU134 clinical image set, 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
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Claude Sonnet 4.5 (Thinking) | 68.75 | #244 (Claude Sonnet 4.5) |
| 2 | Qwen 2.5 VL 72B Instruct | 66.67 | #845 |
| 3 | Gemini 2.5 Flash | 65.42 | #452 |
| 4 | QVQ-72B-Preview | 62.92 | #1173 |
| 5 | GPT-4o Mini | 59.17 | #1627 |
| 6 | GLM-4.5V | 57.08 | #739 |
| 7 | Qwen 3 VL 8B Instruct | 55.42 | #982 |
| 8 | Nemotron Nano 12B v2 VL | 52.08 | #2248 |
| 9 | Llama 3.2 90B | 49.58 | #1740 |
| 10 | Llama 3.2 11B | 42.92 | #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-snu134 · How It Works · Data refreshed daily, snapshot 2026-11-12.