
An LMM-powered web agent completing user instructions end-to-end by interacting with real-world websites.
WebVoyager is an innovative Large Multimodal Model (LMM) powered web agent designed to autonomously accomplish web tasks online from start to finish, managing the entire process without human intervention. It integrates textual and visual information to navigate and interact with real-world websites, effectively handling complex tasks such as locating specific information, making selections, and completing transactions. WebVoyager has been evaluated on a benchmark comprising tasks from 15 popular websites, achieving a 59.1% task success rate, significantly surpassing the performance of other models. The project is open-source, with code and data available for further development and research.
AI Agent Store research
WebVoyager is best understood as a web-agent research implementation rather than a general agent-development framework. The WebVoyager repository contains the implementation and task data for a multimodal agent that completes instructions by interacting with real websites through Selenium.
Last reviewed July 30, 2026
The WebVoyager repository contains the implementation and task data for a multimodal agent that completes instructions by interacting with real websites through Selenium.[1]
Deployment: Source repository[1]
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