CodeClinic: leaderboard
Clinical reasoning agents based on large language models (LLMs) aim to automate tasks such as intensive care unit (ICU) monitoring and patient state tracking from electronic health records (EHRs). Existing systems typically rely on manually curated clinical tools or skills for concepts such as sepsis detection and organ failure assessment. However, maintaining these tool libraries requires substan
Metric: Overall (self-reported). Source: benchmarklist.com. Saturation forecast: Around May 2027. 8 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Claude Sonnet 4.6 | 53.1 | #90 |
| 2 | Gemini 3.1 Pro (Preview) | 53 | #58 |
| 3 | GPT-5.4 | 49.6 | #79 |
| 4 | Gemma 4 31B | 43.4 | #200 |
| 5 | GPT-OSS-120B | 36.1 | #341 |
| 6 | Qwen 3.5 27B | 34.2 | #187 |
| 7 | Qwen 3.5 4B | 21 | #475 |
| 8 | Qwen 3.5 9B | 20.2 | #379 |
No result here: #3 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.
Interactive version: theaggregate.ai/benchmark?slug=codeclinic · How It Works · Data refreshed daily, snapshot 2026-10-20.