KorMedMCQA-V - Three or More Images: leaderboard

Metric: Accuracy (%) on the 39 questions with three or more images (KorMedMCQA-V: image-based five-option questions from the Korean Medical Licensing Examination 2012-2023 (doctor track, R-type items excluded), each with one or more clinical images; zero-shot, closed-book, answer label parsed from JSON; open-source models averaged over three seeds); higher is better. Source: arxiv.org. Saturation forecast: Estimated already saturated. 51 models tracked.

Top models

#ModelScoreOverall rank
1GPT-592.3#91
2Gemini 3 Flash92.3#93
3Gemini 3 Pro87.2#77
4GPT-5 Mini (2025-08-07)87.2#165
5GPT-5.284.6#105
6GLM-4.6V80.3#309
7Qwen 3 VL 32B (Thinking)76.9#287 (Qwen 3 VL 32B)
8Ministral-3-14B-Reasoning-251269.2#519
9Qwen 3 VL 30B A3B (Thinking)67.5#338 (Qwen 3 VL 30B A3B)
10Qwen 3 VL 8B (Thinking)65.8
11Qwen 3 VL 30B A3B Instruct62.4#365
12Qwen 3 VL 32B Instruct61.5#276
13Ministral-3-8B-Reasoning-251259#694
14Gemma 3 27B (IT)56.4#509
15Qwen 2.5 VL 32B Instruct54.7#443

No result here: #3 Claude Opus 5.5, #5 GPT-6 Astra, #8 Claude Fable 5.1.

Interactive version: theaggregate.ai/benchmark?slug=kormedmcqa-v-three-or-more-images · How It Works · Data refreshed daily, snapshot 2026-10-11.