KorMedMCQA-V: leaderboard

Metric: Accuracy (%) on all 1,534 questions (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
1Gemini 3 Flash96.9#93
2Gemini 3 Pro96.9#77
3GPT-593.9#91
4GPT-5.293.9#105
5GPT-5 Mini (2025-08-07)90.1#165
6Qwen 3 VL 32B (Thinking)83.7#287 (Qwen 3 VL 32B)
7Qwen 3 VL 30B A3B (Thinking)80.4#338 (Qwen 3 VL 30B A3B)
8GLM-4.6V78.7#309
9Qwen 3 VL 32B Instruct76.5#276
10Qwen 3 VL 8B (Thinking)74.2
11Ministral-3-14B-Reasoning-251272.7#519
12Qwen 3 VL 30B A3B Instruct71.7#365
13Qwen 3 VL 4B (Thinking)65.9#471 (Qwen 3 VL 4B)
14Ministral-3-8B-Reasoning-251265.1#694
15Qwen 2.5 VL 32B Instruct63#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 · How It Works · Data refreshed daily, snapshot 2026-10-11.