Introducing FigmaTrace: A comprehensive training dataset for Figma design workflows

FigmaTrace is an open-source dataset of 3,469 Figma design trajectories representing more than 200 hours of human work across 10 creative skills, including accessibility fixes, template corrections, prototyping, sketch conversion, and platform adaptation. It addresses the shortage of workflow data for training vision-language models on subjective design tasks by capturing the sequence of expert decisions rather than only final design artifacts. Researchers found that fine-tuning the open Qwen3.8-27B model on these trajectories improved both design and broader agentic navigation performance, surpassing Claude Opus 5 on GUI-Odyssey and AndroidControl while achieving gains on an in-domain creative benchmark. Segmenting long recordings according to design phases outperformed maximum-context-length sharding by 7.3 percentage points on average, suggesting that intent-based curation better preserves task context and teaches transferable skills. Manual analysis associated performance improvements with more accurate element selection, stronger coordinate understanding, and greater decisiveness in producing actions. The release includes 2,883 training trajectories, 586 evaluation trajectories, and the fine-tuned Qwen3.8-27B model.

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