UI-Bench: A Benchmark for Evaluating Design Capabilities of AI Text-to-App Tools

Sam Jung, Agustin Garcinuno, Spencer Mateega
8/28/2025
cs.CL

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Abstract

AI text-to-app tools promise high quality applications and websites in minutes, yet no public benchmark rigorously verifies those claims. We introduce UI-Bench, the first large-scale benchmark that evaluates visual excellence across competing AI text-to-app tools through expert pairwise comparison. Spanning 10 tools, 30 prompts, 300 generated sites, and 4,000+ expert judgments, UI-Bench ranks systems with a TrueSkill-derived model that yields calibrated confidence intervals. UI-Bench establishes a reproducible standard for advancing AI-driven web design. We release (i) the complete prompt set, (ii) an open-source evaluation framework, and (iii) a public leaderboard. The generated sites rated by participants will be released soon. View the UI-Bench leaderboard at https://uibench.ai/leaderboard.

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Cite this paper

@article{jung2025uibench,
  title  = {UI-Bench: A Benchmark for Evaluating Design Capabilities of AI Text-to-App Tools},
  author = {Sam Jung and Agustin Garcinuno and Spencer Mateega},
  year   = {2025},
  eprint = {2508.20410},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2508.20410v3}
}

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