WTM-Bench (Python): leaderboard

WTM-Bench (2026) gives a model a public Excel workbook with its derived artifacts removed and a concise level-3 request, and asks it to recreate the formulas, charts, pivot tables or conditional formatting by writing code in a tool loop of up to 10 turns; outputs are graded programmatically against the original workbook. Here the model drives Excel through Python with openpyxl. Score is the hard score, the share of tasks reproduced exactly, in percent; higher is better.

Metric: Hard score (%; share of tasks whose output workbook matches the target exactly, a perfect soft score; the model drives Excel through Python with openpyxl; 150 WTM-Bench tasks at query level 3 (concise, abstract requests); the authors' tool-calling loop that executes code against the workbook, shows the resulting workbook state and allows up to 10 turns; deterministic programmatic grading). Source: arxiv.org. Saturation forecast: Around January 2028. 6 models tracked.

Top models

#ModelScoreOverall rank
1GPT-5.420#123
2Claude Opus 4.618.7#102
3Claude Sonnet 4.516.7#250
4GPT-5.215.3#176
5Claude Haiku 4.510#568
6GPT-4.1 Mini7.3#779

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=wtm-bench-python · How It Works · Data refreshed daily, snapshot 2026-11-13.