DDR-Bench - MIMIC - Sample-Averaged Message-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 - Sample-Averaged Message-Wise using Checklist Coverage Accuracy (%).

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

Top models

#ModelScoreOverall rank
1Claude Sonnet 4.536.07#148
2GPT-5 Mini30.02#193
3DeepSeek V3.228.98#210
4GPT-5.228.85#115
5GPT-5.128.37#145
6Gemini 3 Flash26.58#103
7MiniMax-M225.39#327
8GLM-4.625.03#265
9Gemini 2.5 Pro21.51#159
10Qwen 3 Next 80B A3B Instruct18.01#381
11Qwen 3 4B 2507 Instruct17.97#768
12Gemini 2.5 Flash Lite17.19#432
13Qwen2.5-14B-Instruct-1M16.75#581
14Gemini 2.5 Flash16.64#255
15Qwen 2.5 14B Instruct15.93#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-sample-averaged-message-wise · How It Works · Data refreshed daily, snapshot 2026-11-05.