Vision2Web: A Hierarchical Benchmark for Visual Website Development with Agent Verification
Recent advances in large language models have improved the capabilities of coding agents, yet systematic evaluation of complex, end-to-end website development remains limited. To address this gap, we introduce Vision2Web, a hierarchical benchmark for visual website development, spanning from static UI-to-code generation, interactive multi-page frontend reproduction, to long-horizon full-stack website development. The benchmark is constructed from real-world websites and comprises a total of 193 tasks across 16 categories, with 918 prototype images and 1,255 test cases. To support flexible, thorough and reliable evaluation, we propose workflow-based agent verification paradigm based on two complementary components: a GUI agent verifier and a VLM-based judge. We evaluate multiple visual language models instantiated under different coding-agent frameworks, revealing substantial performance gaps at all task levels, with state-of-the-art models still struggling on full-stack development.
69ccf5521f6782218d973e54
Zehai He
claimed_verified
2026-04-02T08:16:01.175Z
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Zehai He
he-zh22
user
he-zh22
69ccf5521f6782218d973e55
Wenyi Hong
69ccf5521f6782218d973e56
Zhen Yang
69ccf5521f6782218d973e57
Ziyang Pan
claimed_verified
2026-04-02T08:16:03.628Z
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Ziyang Pan
soupsheep
user
soupsheep
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Mingdao Liu
69ccf5521f6782218d973e59
Xiaotao Gu
69ccf5521f6782218d973e5a
Jie Tang
Vision2Web: A Hierarchical Benchmark for Visual Website Development with Agent Verification
Recent advances in large language models have improved the capabilities of coding agents, yet systematic evaluation of complex, end-to-end website development remains limited. To address this gap, we introduce Vision2Web, a hierarchical benchmark for visual website development, spanning from static UI-to-code generation, interactive multi-page frontend reproduction, to long-horizon full-stack website development. The benchmark is constructed from real-world websites and comprises a total of 193 tasks across 16 categories, with 918 prototype images and 1,255 test cases. To support flexible, thorough and reliable evaluation, we propose workflow-based agent verification paradigm based on two complementary components: a GUI agent verifier and a VLM-based judge. We evaluate multiple visual language models instantiated under different coding-agent frameworks, revealing substantial performance gaps at all task levels, with state-of-the-art models still struggling on full-stack development.
Vision2Web presents a comprehensive benchmark for visual website development tasks and evaluates coding agents across static UI generation, interactive frontend reproduction, and full-stack development with varying complexity levels.
visual language models coding agents website development GUI agent verifier VLM-based judge hierarchical benchmark UI-to-code generation multi-page frontend reproduction full-stack development