DDR-Bench - MIMIC - Item-Averaged Trajectory-Wise: leaderboard

Evaluates autonomous database exploration with SQL/Python tools on MIMIC, GLOBEM and 10-K. GPT-5 mini checks coverage of 2,058 checklist items across 291 task entities. Message-wise and trajectory-wise insights use sample- or item-averaging. Paper v1 scores are preserved; current repository defaults include a 100-turn safety cap. Released financial-trajectory labels resolve eight Qwen instruct/checkpoint identities; ambiguous Qwen3-30B-A3B and Kimi K2 snapshots remain explicit source-local rows. This series reports DDR-Bench - MIMIC - Item-Averaged Trajectory-Wise using Checklist Coverage Accuracy (%).

Metric: Checklist Coverage Accuracy (%). Source: arxiv.org. Saturation forecast: Around February 2028. 22 models tracked.

Top models

#ModelScoreOverall rank
1GPT-5.133.59#145
2Claude Sonnet 4.532.95#148
3GPT-5.230.49#115
4DeepSeek V3.228.29#210
5GPT-5 Mini26.36#193
6GLM-4.624.42#265
7MiniMax-M223.13#327
8Gemini 2.5 Flash22.22#255
9Qwen 3 Next 80B A3B Instruct20.8#381
10Gemini 3 Flash19.51#103
11Gemini 2.5 Pro18.48#159
12Gemini 2.5 Flash Lite17.18#432
13Qwen 3 4B 2507 Instruct17.18#768
14Qwen 2.5 72B Instruct15.5#469
15Qwen 2.5 14B Instruct13.44#654

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

Interactive version: theaggregate.ai/benchmark?slug=ddr-bench-mimic-item-averaged-trajectory-wise · How It Works · Data refreshed daily, snapshot 2026-11-05.