Doc2DB-Bench - Dynamic Change: leaderboard

Metric: Cell-level F1 (%; relation-table cells annotated with the Dynamic Change capability of the inter-table taxonomy (Section 5.3); 203 synthesized long-document instances over 42 database schemas from BIRD and Spider in seven domain groups; identical prompts, greedy decoding at temperature 0; cells aligned by global maximum-weight tuple matching, a cell matching on exact numeric equality or at least 90 percent string similarity). Source: arxiv.org. Saturation forecast: Around December 2026. 8 models tracked.

Top models

#ModelScore
1GPT-5.479.27
2Gemini 2.5 Pro78.69
3Claude Opus 4.666.26
4Qwen 3 Max58.36
5GPT-4o58.11
6Llama 3.1 70B Instruct51.83
7DeepSeek V4 Flash46.93
8Qwen 2.5 14B Instruct36.51

Interactive version: theaggregate.ai/benchmark?slug=doc2db-bench-dynamic-change · How It Works · Data refreshed daily, snapshot 2026-09-29.