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

Metric: Checklist Coverage Accuracy (%). Source: arxiv.org. Saturation forecast: Around 2030. 22 models tracked.

Top models

#ModelScoreOverall rank
1GLM-4.641.56#265
2Claude Sonnet 4.540.13#148
3GPT-5.238.81#115
4DeepSeek V3.238.46#210
5GPT-5.138.31#145
6MiniMax-M237.07#327
7GPT-5 Mini35.86#193
8Qwen 3 Next 80B A3B Instruct35.75#381
9Gemini 3 Flash35.6#103
10Gemini 2.5 Pro33.77#159
11Qwen2.5-7B-Instruct-1M29.34#886
12Gemini 2.5 Flash29.06#255
13Qwen 2.5 72B Instruct28.83#469
14Qwen2.5-14B-Instruct-1M28.75#581
15Qwen 2.5 7B Instruct27.2#863

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-globem-sample-averaged-message-wise · How It Works · Data refreshed daily, snapshot 2026-11-05.