EHRStruct (Synthea) - Addition: leaderboard

EHRStruct (Yang, Zhao and Shen, 2025) tests language models on structured electronic health record tables. This board is its D-R5 task on synthetic Synthea records: 100 zero-shot questions, each asking the model to add two numeric fields of a patient (for example income and healthcare expenses), rounded to two decimals from a table given as plain text. Exact-answer accuracy in percent, higher is better; models that produced no valid output are left out.

Metric: Accuracy (%; D-R5: 100 zero-shot questions on synthetic Synthea patient tables given as plain text, where each item asks to add two numeric fields of a patient (for example income and healthcare expenses), rounded to two decimals; an answer counts when it matches the reference exactly; the paper's check mark, a perfect score, reads 100, and its cross, no valid output, reads as missing). Source: arxiv.org. Saturation forecast: Estimated already saturated. 14 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 2.5 Flash100#453
2DeepSeek V390#716
3GPT-4.184#495
4Gemini 2.0 Flash67#704
5DeepSeek V2.552#1210
6GPT-3.5 Turbo24#2753
7Llama3-Med42-70B18#1769

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=ehrstruct-synthea-addition · How It Works · Data refreshed daily, snapshot 2026-11-13.