CareTransition-Audit - Accuracy: leaderboard

Metric: Label accuracy (%) against the clinician labels on the 46-question DISCHARGED audit checklist applied to 50 MIMIC-IV discharge summaries (Yes, No, Unclear or N/A per question), zero-shot with six prompts per summary and an indirect chain-of-thought instruction; summary-question pairs with an N/A label or an unparseable output are left out; higher is better. Source: arxiv.org. Saturation forecast: Around January 2027. 11 models tracked.

Top models

#ModelScore
1Gemini 3 Flash (Preview)81.4
2Claude Sonnet 4.580.4
3GPT-5.477.2
4Nova 2.0 Lite (Non-reasoning)74.7
5DeepSeek V3.274.3
6GPT-4o72.8
7Grok 4.1 Fast72.1
8Llama 4 Maverick70.6
9Phi-464
10Qwen 2.5 7B Instruct62.3

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