EHRBench - MIMIC-III: leaderboard

Metric: Accuracy (%) on the questions built from MIMIC-III records, EHR-grounded multiple-choice clinical decision questions (4, 5 and 6 options) built from MIMIC-III, MIMIC-IV and PROMOTE encounter trajectories with knowledge-base verification, JSON-constrained answers, deterministic decoding; higher is better. Source: arxiv.org. Saturation forecast: Around January 2027. 31 models tracked.

Top models

#ModelScore
1GPT-5.2 Instant71.5
2GPT-4.170.59
3GPT-5 Chat70.16
4GPT-5 Mini69.08
5Llama 3.3 70B Instruct68.74
6GPT-4.1 Mini68.58
7Qwen 3 32B68.48
8Mistral Small 367
9GLM-4 32B (0414)66.27
10Qwen 2.5 32B65.22
11Qwen 3 8B62.26
12Qwen 3 4B62.01
13GLM-4 9B (0414)61.92
14GPT-4.1 Nano61.59
15Yi 1.5 34B60.72

Interactive version: theaggregate.ai/benchmark?slug=ehrbench-mimic-iii · How It Works · Data refreshed daily, snapshot 2026-10-07.