LingxiDiagBench (Dynamic, Symptom-Tree) - Consultation Quality: leaderboard

Metric: Consultation quality (1-6): mean of five Likert dimensions (clinical accuracy and competence, ethical and professional conduct, assessment and response, therapeutic relationship, communication quality), each the mean of three LLM judges (Gemma-3-27B, GPT-OSS-20B, Qwen3-30B-A3B); LingxiDiagBench-Dynamic on LingxiDiag-16K cases: the model leads a multi-turn consultation with a Qwen3-32B patient agent built from the case EMR, then diagnoses; doctor strategy: the MDD-5K symptom decision-tree strategy; higher is better. Source: arxiv.org. Saturation forecast: Around 2032. 13 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3 Flash3.6#93
2Kimi K2 (Thinking)3.59#236 (Kimi K2)
3GPT-5 Mini3.56#176
4DeepSeek V3.23.54#198
5Qwen 3 32B3.5#424
6GPT-OSS-20B3.36#499
7Claude Haiku 4.53.24#271
8Qwen 3 4B3.17#823
9Qwen 3 8B3.15#667
10Grok 4.1 Fast2.98#208
11Qwen 3 1.7B2.93#1186

No result here: #3 Claude Opus 5.5, #5 GPT-6 Astra, #8 Claude Fable 5.1.

Interactive version: theaggregate.ai/benchmark?slug=lingxidiagbench-dynamic-symptom-tree-consultation-quality · How It Works · Data refreshed daily, snapshot 2026-10-11.