Browser Use vs Competitors: Side-by-Side Comparisons [2026]

The open-source Python library is fully free under the MIT license with no usage limits or feature gates. You run it locally with your own LLM API keys (OpenAI, Anthropic, Google) and a local browser installation. The cloud product — which adds managed browsers, stealth capabilities, CAPTCHA solving, Skill APIs, and premium proxies — starts with a pay-as-you-go model (minimum $50 credit purchase) and subscription plans from $40/month (Startup) to $2,500/month (Scaleup). The open-source core and the cloud product use the same Python codebase, so you can develop locally for free and only move to cloud when you need scaling or stealth features.

Browser Use reports that ChatBrowserUse models complete browser-specific tasks in approximately 40% fewer steps than GPT-4o on their internal evaluation suite. BU Mini handles routine tasks like form filling, navigation, and data extraction with fewer intermediate steps because the model is trained specifically on browser interaction patterns and generates tighter action sequences. BU Max targets complex multi-step workflows. However, these benchmarks are self-reported by Browser Use and have not been independently verified by third parties. Real-world performance varies depending on website complexity, task type, and page load times. For cost comparison, BU Mini runs at roughly $0.72/$4.20 per 1M input/output tokens versus GPT-4o at approximately $2.50/$10.00.

Yes, the open-source library works entirely locally with no cloud dependency. You provide your own LLM API keys and a local Chromium or Playwright browser. The same Python code that runs locally also runs on the cloud — you toggle one parameter (use_cloud=True) to switch. The open-source version includes the full agent framework, vision + DOM hybrid understanding, multi-LLM support, and all core automation capabilities. What you do not get locally is managed stealth infrastructure, CAPTCHA auto-solving, premium proxies, Skill APIs, and persistent cloud memory. The GitHub repository (55,000+ stars as of early 2026) has active community support for the open-source version.

Creating a skill costs $2.00 one-time, and each execution costs $0.02 thereafter. Skills run without per-step LLM costs because the workflow is pre-recorded after one validation pass, making them dramatically cheaper than running a full agent on every call. For example, a price-monitoring workflow that costs $0.15–$0.50 in LLM tokens as a full agent run would cost just $0.02 as a Skill execution. Pay-as-you-go plans support up to 5 active Skills, while Startup plans ($40/month) support up to 100. Skills are only available on the cloud product — the open-source version does not include Skill API functionality.

Yes, the cloud product includes CAPTCHA auto-solving on all plans including pay-as-you-go. Basic stealth — fingerprint randomization and human-like input patterns such as realistic mouse movements and typing cadence — is included on pay-as-you-go. Advanced stealth, available on Startup ($40/month) and above, adds agent-level behavioral mimicry, premium proxy pools covering 195+ countries, and more sophisticated fingerprint management. The open-source version running locally does not include CAPTCHA solving or stealth features — you would need to implement your own solutions or use third-party CAPTCHA services alongside the library.