Partnering with Browserbase to Train Browser and Computer Use Agents

Partnering with Browserbase, the initiative aims to enhance training experiences for browser and computer use agents by utilizing scalable browser infrastructure previously employed in projects like Microsoft's Fara-7B and Google's Gemini 2.5 CUA. This infrastructure is now accessible to a broader audience through BrowserEnv, which facilitates training against real websites by managing tasks such as running browsers at scale, handling sessions, and overcoming anti-bot protections. To demonstrate the capabilities of their full stack, they fine-tuned the Qwen3-VL-8B-Instruct model on 600 real web tasks, proving its ability to navigate and extract information from live sites such as Amazon and GitHub. BrowserEnv offers two modes, CUA for vision-language models and DOM for text-only models, both operating on Browserbase's infrastructure and compatible with the same datasets and evaluation criteria. Users can either start with pre-built example environments or dive into the WebVoyager benchmark, with the flexibility to extend these setups for custom tasks and workflows. Additional resources and guides are available at BrowserEnv.com.

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