LingxiDiagBench (Dynamic, APA-Guided) - 2-Class Accuracy: leaderboard

Metric: Accuracy (%, 0-100) on binary depression-versus-anxiety classification (cases without comorbidity) after the consultation; 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 five-phase APA-guided interview (screening, assessment, deep-dive, risk assessment, closure); higher is better. Source: arxiv.org. Saturation forecast: Not forecast. 13 models tracked.

Top models

#ModelScoreOverall rank
1DeepSeek V3.288.5#198
2Qwen 3 1.7B84.6#1186
3Qwen 3 8B82.7#667
4Qwen 3 4B82.7#823
5Gemini 3 Flash81.8#93
6Claude Haiku 4.581.8#271
7Grok 4.1 Fast81.8#208
8GPT-OSS-20B80.8#499
9Qwen 3 32B78.8#424
10Kimi K2 (Thinking)77.3#236 (Kimi K2)
11GPT-5 Mini75#176

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-apa-guided-2-class-accuracy · How It Works · Data refreshed daily, snapshot 2026-10-11.