Use the CLI if you already have an agent (Claude Code, Codex, Cursor, Hermes, OpenClaw, etc.) that you want to complete browser tasks for you. The agent installs the skill once (see Quickstart) and can then control the browser. Examples:

• "Upload this video to YouTube"
• "Compare these three laptops and give me a table with prices"
• "Fill in this job application with my resume"

Use the Python library when you are building software that automates the web. Examples:

• Run many tasks on a schedule or in parallel (scraping, monitoring, QA)
• Embed a browser agent into your own product
• Custom tools, custom system prompts, structured output, fine-grained browser control

Rule of thumb: one-off tasks through an agent → CLI. Repeatable automation in code → Python library.

We optimized ChatBrowserUse() specifically for browser automation tasks. On avg it completes tasks 3-5x faster than other models with SOTA accuracy.

For pricing and other LLM providers, see our supported models documentation.

Yes. ChatBrowserUse accepts provider-prefixed model ids, so a single BROWSER_USE_API_KEY reaches all of them — no separate OpenAI/Anthropic/Google keys required:

from browser_use import Agent, ChatBrowserUse

llm = ChatBrowserUse(model='anthropic/claude-sonnet-4-6')  # or 'openai/gpt-5.5', 'google/gemini-3-pro'
agent = Agent(task='...', llm=llm)

For the best speed and cost we still recommend the default bu-* models.

Yes. If you use ChatBrowserUse(model='browser-use/bu-30b-a3b-preview') with a normal Agent(...), Browser Use still sends its default agent system prompt for you.

You do not need to add a separate custom "Browser Use system message" just because you switched to the open-source preview model. Only use extend_system_message or override_system_message when you intentionally want to customize the default behavior for your task.

If you want the best default speed/accuracy, we still recommend the newer hosted bu-* models. If you want the open-source preview model, the setup stays the same apart from the model= value.

Yes! You can add custom tools to extend the agent's capabilities:

from browser_use import Tools

tools = Tools()

@tools.action(description='Description of what this tool does.')
def custom_tool(param: str) -> str:
    return f"Result: {param}"

agent = Agent(
    task="Your task",
    llm=llm,
    browser=browser,
    tools=tools,
)

Yes! Browser-Use is open source and free to use. You only need to choose an LLM provider (like OpenAI, Google, ChatBrowserUse, or run local models with Ollama).

This open-source library is licensed under the MIT License. For Browser Use services & data policy, see our Terms of Service and Privacy Policy.

Check out our authentication examples:

• Using real browser profiles - Reuse your existing Chrome profile with saved logins
• If you want to use temporary accounts with inbox, choose AgentMail
• To sync your auth profile with a remote browser, install profile-use for your platform from the official releases, then follow the profile sync guide.

These examples show how to maintain sessions and handle authentication seamlessly.

For CAPTCHA handling, you need better browser fingerprinting and proxies. Use Browser Use Cloud which provides stealth browsers designed to avoid detection and CAPTCHA challenges.

Chrome can consume a lot of memory, and running many agents in parallel can be tricky to manage.

For production use cases, use our Browser Use Cloud API which handles:

• Scalable browser infrastructure
• Memory management
• Proxy rotation
• Stealth browser fingerprinting
• High-performance parallel execution