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

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

Top models

#ModelScoreOverall rank
1Claude Sonnet 4.538.72#148
2DeepSeek V3.238.46#210
3GPT-5.238.15#115
4GLM-4.637.6#265
5MiniMax-M236.81#327
6Gemini 3 Flash36.74#103
7GPT-5.135.79#145
8Gemini 2.5 Pro35.62#159
9Qwen 3 Next 80B A3B Instruct33.06#381
10GPT-5 Mini31.54#193
11Gemini 2.5 Flash28.44#255
12Qwen 3 4B 2507 Instruct27.55#768
13Qwen 2.5 14B Instruct26.47#654
14Qwen 2.5 32B Instruct25.88#509
15Qwen2.5-7B-Instruct-1M25.68#886

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-trajectory-wise · How It Works · Data refreshed daily, snapshot 2026-11-05.