Synthetic Hospital - Summarization: leaderboard
Metric: Finding-level F1 (%; whole-patient clinical summary scored against graph-defined key findings, ontology-grounded structured 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 2029. 10 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | Claude Opus 4.6 | 55 |
| 2 | Kimi K2.5 (Thinking) | 53.2 |
| 3 | GPT-5.3 | 48.9 |
| 4 | GLM-5 | 48.4 |
| 5 | Qwen 3.5 397B A17B | 42.5 |
| 6 | Llama 4 Scout | 40.3 |
| 7 | DeepSeek V3.2 | 39.9 |
| 8 | Gemma 3 27B | 38.5 |
Interactive version: theaggregate.ai/benchmark?slug=synthetic-hospital-summarization · How It Works · Data refreshed daily, snapshot 2026-09-26.