Browser Use vs Stagehand: Which is Better? (February 2026)

Teams assessing Browser Use and Stagehand are usually trying to solve the same problem: traditional browser automation is brittle. DOM selectors drift. Layouts change. Authentication flows mutate. Scripts that worked yesterday fail silently today. AI-powered browser control promises resilience, but the way AI is integrated into the execution loop determines how each system behaves under real-world constraints. Browser Use and Stagehand are not simply different libraries. They represent two distinct architectural models for combining LLMs with browser automation. Understanding those models is critical before deploying either in production workflows.

TLDR:

• Browser Use offers autonomous Python agents while Stagehand adds AI to Playwright code
• Stagehand caches actions to cut costs on repeat runs; Browser Use uses live AI reasoning
• Both require code maintenance and model selection for each workflow
• Skyvern provides one API for browser automation without selectors or custom code
• Skyvern scored 85.8% on WebVoyager with built-in 2FA, CAPTCHA, and form filling

Execution Model: Continuous Agents vs Hybrid Determinism

The most fundamental difference between Browser Use and Stagehand lies in how they execute workflows. Browser Use is agent-first built around a Python library. You provide a goal in natural language, and the system enters a reasoning loop. It observes the page, determines the next action, executes it, and reassesses state. Each meaningful step depends on live LLM inference. The agent continuously plans and adapts until the objective is complete. This design favors flexibility and autonomy. If unexpected modals appear or page flows differ, the agent reasons its way forward without predefined control logic.

Stagehand, though, operates differently as a TypeScript extension. It takes a deterministic-first approach by extending Playwright instead of replacing it. Developers write standard Playwright automation for predictable flows such as navigation and login. When the script encounters dynamic or unknown elements, AI helper methods such as act, extract, or observe are invoked. The majority of the workflow remains explicit code, with AI selectively introduced where selectors might fail. The hybrid model preserves full access to the Playwright page object, offering capabilities that position it among modern alternatives to Selenium. You can combine page.click() and page.goto() with page.act() in the same script, making it simple to add AI capabilities to existing Playwright test suites without rewriting them as agent workflows.

LLM Integration Strategy and Model Flexibility

While both systems depend on LLMs, their integration philosophies differ. Browser Use, on one hand, integrates through LangChain and supports multiple providers, including OpenAI, Google, Anthropic, local models via Ollama, and its own optimized ChatBrowserUse model. Because the agent reasons continuously, model quality directly affects task success, latency, and cost. Model selection becomes a recurring decision, especially for high-volume workflows. Stagehand, though, is model-agnostic but structurally selective. It requires an LLM API key for its AI methods, yet inference occurs only when those methods are explicitly invoked or when cached interactions fail. Developers can choose models based on the complexity of specific workflow segments. Simpler extraction tasks can use lighter models, while complex reasoning can use more capable ones. In practice, Browser Use ties model performance directly to full workflow execution, whereas Stagehand localizes inference to specific moments inside a largely deterministic script.

Caching, Memory, and Adaptation to Layout Changes

When teams look to browser automation that is integrated with AI, it's usually because they are trying to tackle a common problem with browser automation: layout changes. Without AI, scripts based on DOM structures can break with simply layout changes. AI, though, can help reduce fragility caused by layout changes. But, Browser Use and Stagehand, while including AI, do so through different mechanisms.

To start, Browser Use does not rely on cached selectors. Instead, it re-reasons at every step. When a page layout changes, the agent simply observes the new structure and continues reasoning. This removes reliance on stored interaction patterns but keeps inference costs persistent across runs. Session persistence is maintained through cookies and authentication handling, yet action planning remains dynamic. Stagehand, on the other hand, introduces auto-caching as a core optimization. When an AI-driven action succeeds, the system records the selector path and replays it on subsequent runs without invoking the LLM. If replay fails due to a layout update, the AI re-engages, finds a new interaction strategy, and updates the cache. Over repeated executions, workflows become faster and less expensive, gradually angling toward Playwright-native performance.

So what's the bottom line here? Browser Use optimizes for dynamic reasoning on every run while Stagehand optimizes for cost reduction over time by changing AI-identified actions into deterministic replay.

Engineering Burden and Workflow Ownership

Although both tools reduce reliance on static XPath selectors, they still require engineering ownership and that can have a big impact on how much work it will require to maintain the tool. Browser Use requires developers to define goals, tune prompts, manage agent configuration, and select models. While it eliminates explicit selectors, it introduces agent orchestration complexity. Debugging involves understanding agent decision chains and prompt interactions. Stagehand, though, requires writing and maintaining Playwright scripts. Even though AI handles dynamic elements, deterministic code must still define navigation, structure, and execution boundaries. Changes in workflow logic require code updates. AI methods must be carefully inserted and tested. In both cases, teams are maintaining automation logic. The difference lies in whether that logic is expressed as agent prompts or deterministic scripts augmented with AI.

Production Infrastructure Challenges and Constraints

The biggest differences often come up in production environments instead of in development demos. That's where outlier use cases or complications can arise. Just consider this: Rreal-world browser automation frequently requires handling two-factor authentication, time-based one-time passwords, CAPTCHA challenges, proxy routing, structured schema-based extraction, file downloads, session management, and parallel execution. These capabilities are not purely interaction problems. They are infrastructure problems.

With regard to these two choices, there is a difference. Browser Use focuses primarily on agent-level browser control. While it supports authentication persistence and flexible model integration, broader production features often require additional tooling or custom integration. But, Stagehand focuses on Playwright augmentation. It integrates well with cloud browser infrastructure such as Browserbase, but concerns like CAPTCHA handling, advanced proxy routing, and structured data pipelines typically sit outside the core framework.

Production browser automation demands more than flexible clicking. It demands resilient authentication handling, schema validation, scalable execution, and observability.

Skyvern’s Architecture: Production-Focused Abstraction

Skyvern approaches browser automation from a different architectural angle. instead of exposing an agent library or a framework extension, it provides a single API designed for cross-site generalization without per-site scripting.

The system combines LLM reasoning with computer vision to interact with rendered page elements instead of relying on DOM selectors. Its Planner–Actor–Validator architecture decomposes workflows into planned steps, executes them through vision-guided interaction, and validates outcomes before proceeding. This validation layer reduces cascading failures and unnecessary inference loops while preserving adaptability to layout changes.

Skyvern scored 85.8% on the WebVoyager benchmark, showing strong task completion across previously unseen websites. More importantly, the system integrates production capabilities directly into its architecture, including native 2FA and TOTP authentication, CAPTCHA support, proxy networks with geographic targeting, structured schema-based data extraction, automated file downloads to cloud storage, live viewport streaming, and parallel execution. It can be deployed as a managed cloud service with anti-bot protections or self-hosted through its open-source distribution that includes sophisticated authentication handling.

Where Browser Use focuses on agent autonomy and Stagehand focuses on hybrid cost optimization, Skyvern stands on production reliability across heterogeneous sites with minimal per-workflow engineering overhead.

Side-by-Side Comparison

Final Thoughts on Selecting Between Agent Libraries and Playwright Extensions

The correct choice between Browser Use and Stagehand for browser automation depends on your primary constraint. If you value autonomous reasoning and exploratory flexibility, continuous agent execution may align with your needs. If you already maintain Playwright infrastructure and want to introduce AI selectively while reducing repeated inference costs, a hybrid model may be pragmatic. If your challenge is production-grade automation across many unfamiliar systems with authentication, file handling, and reliability embedded in the system, an API-driven abstraction reduces long-term maintenance complexity. The deeper question is not which system uses AI. All of them do. The question is where intelligence lives in the execution stack and how much automation logic you want to own over time. Set up a quick call if you want to see how Skyvern's computer vision approach handles this without agents or code.

FAQ

What's the main difference between Browser Use and Stagehand?

Browser Use is a Python library that uses autonomous AI agents to control browsers through natural language instructions, while Stagehand is a TypeScript framework that adds AI methods to existing Playwright code. Browser Use plans and executes entire workflows through continuous LLM inference, while Stagehand lets you write standard Playwright code and invoke AI only when needed.

Which tool is better for teams with existing Playwright test suites?

Stagehand is the better choice if you already use Playwright. It preserves full access to the Playwright page object and lets you combine standard methods like page.click() with AI-powered methods like page.act() in the same script, so you can add AI capabilities without rewriting existing automation.

How does Stagehand's caching reduce costs compared to Browser Use?

Stagehand records successful actions during initial runs and replays them without LLM calls on subsequent visits, cutting API costs and latency for repeated tasks. Browser Use requires LLM inference at every step of every run, making it more expensive for workflows you execute frequently.

Can I run Browser Use without connecting to cloud LLM providers?

Yes, Browser Use supports local models through Ollama for self-hosted deployments. You can also use their optimized ChatBrowserUse model, OpenAI, Google, or Anthropic depending on your privacy and cost requirements.

When should I choose Skyvern over Browser Use or Stagehand?

Choose Skyvern when you need production-ready automation across multiple sites without writing custom code for each one. Skyvern provides a single API endpoint that works across unfamiliar websites, includes built-in features like 2FA handling and CAPTCHA solving, and adapts to layout changes without maintenance.