WebVoyager
Overview
An LMM-powered web agent completing user instructions end-to-end by interacting with real-world websites.
Best For Professions:
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.
Product overview
Capabilities, pricing and fit
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.
Information as of July 30, 2026
What it can do
- Agent application development
The WebVoyager repository contains the implementation and task data for a multimodal agent that completes instructions by interacting with real websites through Selenium.[1]
Where it fits best
- Studying or reproducing multimodal web-agent evaluation.[1]
Pricing and availability
Access: Source repository[1]
Sources (1)
Autonomy level
80/100
Our subjective rating of how independently the product carries out its documented tasks, considering the human setup, input, approval and review it needs. This is not a measured success rate.
Comparisons
Custom Comparisons
Some of the use cases of WebVoyager:
- Automating web-based tasks without human intervention.
- Interacting with dynamic web content using multimodal inputs.
- Developing AI agents capable of real-world web navigation.
- Researching advancements in large multimodal model applications.
- Benchmarking web agents on diverse, real-world tasks.
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Pricing model:
Code access:
Popularity level: 69%
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