DDR-Bench - 10-K - 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 - 10-K - Sample-Averaged Trajectory-Wise using Checklist Coverage Accuracy (%).

Metric: Checklist Coverage Accuracy (%). Source: arxiv.org. Saturation forecast: Around February 2027. 22 models tracked.

Top models

#ModelScoreOverall rank
1Claude Sonnet 4.560.58#148
2GPT-5.144.25#145
3GPT-5.241.09#115
4DeepSeek V3.238.15#210
5GPT-5 Mini37.12#193
6GLM-4.636.02#265
7Qwen 3 Next 80B A3B Instruct30.82#381
8MiniMax-M226.88#327
9Gemini 3 Flash21.24#103
10Qwen 3 4B 2507 Instruct19.76#768
11Gemini 2.5 Flash16.06#255
12Gemini 2.5 Pro15.57#159
13Qwen 2.5 72B Instruct13.42#469
14Qwen 2.5 14B Instruct10.6#654
15Qwen2.5-14B-Instruct-1M10.13#581

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-10-k-sample-averaged-trajectory-wise · How It Works · Data refreshed daily, snapshot 2026-11-05.