Synthetic Hospital - Patient Diagnosis: leaderboard
Metric: Severity-weighted F1 (%; reconstruction of the patient longitudinal problem list as ICD-10 codes with acuity, chart-neutral scoring, chain-of-thought prompting; public split of 200 synthetic longitudinal patients (1,268 in all, built from USMLE-style questions with ontology-grounded labels); single-turn, one prompting strategy locked per task for every model; graph-derived deterministic scoring). Source: arxiv.org. Saturation forecast: Around December 2026. 10 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | Kimi K2.5 (Thinking) | 73.2 |
| 2 | GPT-5.3 | 70.3 |
| 3 | DeepSeek V3.2 | 66 |
| 4 | GLM-5 | 65.7 |
| 5 | Qwen 3.5 397B A17B | 65.3 |
| 6 | Claude Opus 4.6 | 61.5 |
| 7 | Llama 4 Scout | 53.6 |
| 8 | Gemma 3 27B | 28.7 |
Interactive version: theaggregate.ai/benchmark?slug=synthetic-hospital-patient-diagnosis · How It Works · Data refreshed daily, snapshot 2026-09-26.