Master Browser Use with our step-by-step tutorial, detailed feature walkthrough, and expert tips.
Explore the key features that make Browser Use powerful for browser automation workflows.
Purpose-built LLMs trained on browser automation patterns. BU Mini handles routine tasks cost-efficiently (~$0.72/$4.20 per 1M tokens), while BU Max tackles complex multi-step workflows (~$3.60/$18.00 per 1M tokens). Both generate tighter action sequences than general-purpose models, reducing step counts and total cost per task.
Combines screenshot analysis with DOM tree extraction to identify page elements. Unlike pure selector-based tools that break when layouts change, the hybrid approach adapts to redesigns automatically. The agent sees the page visually and structurally, making element identification robust across different sites.
Record a browser workflow once and expose it as a callable API endpoint. Each skill costs $2.00 to create and $0.02 per execution. Eliminates per-step LLM costs for repetitive tasks, providing API-level reliability with browser automation flexibility. Supports up to 100 active skills on subscription plans.
Cloud-hosted browsers with fingerprint randomization, human-like mouse movements and typing patterns, CAPTCHA auto-solving, and premium proxy pools covering 195+ countries. Advanced stealth on subscription plans adds agent-level behavioral mimicry and bring-your-own-proxy support.
The complete agent framework is open source on GitHub with an active community. Run locally for development, testing, or production without any licensing costs. Same codebase works with local browsers or cloud infrastructure — toggle use_cloud=True to switch.
Works with ChatBrowserUse models, OpenAI GPT-4, Anthropic Claude, Google Gemini, and any LangChain-compatible LLM. Switch models per task to optimize cost and capability — use cheaper models for simple navigation and premium models for complex reasoning.
The open-source Python library is free under the MIT license with no usage limits. You run it locally with your own LLM API keys and browser. The cloud product (managed browsers, stealth, Skills) starts at $40/month for subscriptions or pay-as-you-go credit purchases from $50.
Browser Use reports 3-5x faster task completion measured in step count. A task that takes GPT-4 twelve steps might complete in four with a ChatBrowserUse model. Actual speed depends on task complexity — simple form fills see the biggest improvements.
Yes. The open-source library works entirely locally. You provide your own LLM API keys (OpenAI, Anthropic, Google, etc.) and browser installation. The cloud is optional for teams that want managed infrastructure, stealth, and scaling.
Creating a skill costs $2.00. Each execution costs $0.02. Skills run without per-step LLM costs since the workflow is pre-recorded, making them dramatically cheaper than running a full agent for repetitive tasks. Pay-as-you-go allows 5 active skills; subscriptions allow up to 100.
You need working knowledge of Python and async programming (asyncio). Browser Use is a code-first library — there is no drag-and-drop or no-code interface. Familiarity with LLM APIs and browser automation concepts helps but is not strictly required.
The cloud product includes CAPTCHA solving on all plans. Basic stealth (fingerprint randomization, human-like inputs) is included on pay-as-you-go. Advanced stealth (agent-level behavioral mimicry, premium proxies, bring-your-own-proxy) requires a subscription plan.
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Tutorial updated March 2026