PopAnesQA - General: leaderboard

PopAnesQA (Shin et al., MLHC 2026, PMLR 340): 623 four-option, scenario-based multiple-choice anesthesiology questions, each built around a patient profile. Unlike MedQA-style knowledge questions, it asks whether a model can make "action-oriented clinical management decisions that are correctly adapted to the target patient population"; the authors found pediatric anesthesia to be "only 0.2%" of five widely used medical QA sets. Answered without retrieval at temperature 0. Every item was generated with Gemini-3-Flash, which also scores highest. Score: accuracy (%) on the 159 general-population questions. Higher is better. Source: https://proceedings.mlr.press/v340/shin26a.html

Metric: Accuracy (%). Source: proceedings.mlr.press. Saturation forecast: Estimated already saturated. 9 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3 Flash92.45#103
2GPT-4o83.65#357
3Gemma 3 27B (IT)77.36#528
4Llama 3.1 8B Instruct71.07#1017
5Mixtral 8x7B Instruct69.81#1085

No result here: #3 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.

Interactive version: theaggregate.ai/benchmark?slug=popanesqa-general · How It Works · Data refreshed daily, snapshot 2026-11-05.