Browser Use vs Airtop: Which Tool Works Better? (February 2026)
The browser automation space keeps adding new tools, and Browser Use versus Airtop is the latest comparison everyone's asking about. Here's what actually matters: Browser Use gives you a self-hosted Python library with more control over deployment, while Airtop removes infrastructure headaches with managed cloud browsers. The choice seems simple until you run into authentication challenges, need to handle CAPTCHAs reliably, or scale past the point where manual session management becomes a daily problem.
TLDR:
- Browser Use requires Python coding and self-hosting while Airtop runs cloud-only
- Both tools struggle with 2FA and CAPTCHAs without extra infrastructure setup
- Skyvern uses computer vision to adapt when websites change, eliminating brittle selectors
- Skyvern includes native 2FA, CAPTCHA solving, and proxy networks out of the box
- Skyvern works self-hosted or cloud with simple API and transparent pricing
The Challenges of Browser Automation
Browser automation sounds straightforward until you actually try building reliable workflows. With 85% of organizations already integrating AI agents in at least one workflow, the demand for reliable automation has moved beyond experimentation into production necessity. The reality involves wrestling with authentication systems, adapting to website changes, managing infrastructure at scale, handling anti-bot detection, and building workflows that work across multiple sites. These challenges turn simple automation ideas into complex engineering projects.
Fragile Selectors Break When Websites Change
Most browser automation tools rely on CSS selectors or XPath expressions to identify elements on web pages. When a website updates its layout, changes class names, or restructures its HTML, these selectors break. Your automation stops working, and someone needs to manually update every affected selector. This maintenance burden scales with the number of websites you automate and how frequently they change.
Authentication Flows Create Persistent Headaches
Modern websites use complex authentication systems: OAuth flows, two-factor authentication, CAPTCHA challenges, and session management. Each adds layers of complexity to automation. Sessions expire, requiring credential refreshes. CAPTCHAs block automated access. Multi-factor authentication requires handling SMS codes or authenticator apps. Managing these authentication states across multiple automations becomes a full-time job.
Infrastructure Management Demands Technical Resources
Self-hosted browser automation means provisioning servers, managing Chrome instances, handling browser updates, and planning capacity for parallel execution. Running 50 simultaneous tasks requires handling 50 browser instances, each consuming memory and CPU. Scaling requires predicting resource needs and provisioning infrastructure before increasing load. This overhead diverts engineering resources from building actual automation workflows.
Anti-Bot Detection Systems Block Automated Access
Websites deploy sophisticated anti-bot systems that detect and block automated access. These systems analyze browser fingerprints, mouse movements, request patterns, and IP addresses. Bypassing these protections requires proxy networks, fingerprint randomization, and behavior simulation. Without these capabilities, your automations get blocked before completing their tasks.
Building Workflows That Work Across Multiple Websites
Creating automation that works on one website is manageable. Building workflows that operate across dozens or hundreds of different sites multiplies complexity. Each site has unique layouts, form structures, and interaction patterns. Traditional automation requires writing custom code for each site, making cross-site workflows impractical at scale.
How Browser Use and Airtop Tackle These Challenges
Browser Use and Airtop both tackle those challenges differently, reflecting their technologies and approaches to browser automation. While both tools advance browser automation beyond basic scripting, they both still require managing credentials, tracking session expiration, and handling edge cases in authentication flows. Neither completely removes the complexity of reliable authentication handling or provides complete solutions for CAPTCHA challenges without additional configuration.
Browser Use
Browser Use works well for teams comfortable with Python and AI model APIs who want code-level control over their automation. The tool uses AI models to interpret pages dynamically instead of relying on fixed selectors, which reduces brittleness when layouts change. You can describe tasks in natural language that AI models interpret and execute, cutting down on site-specific code requirements. The platform operates as a Python library on your own servers where you manage Chrome instances, server resources, and scaling capacity yourself, though they offer a cloud version that removes infrastructure management.
The main limitations show up in authentication and anti-bot handling. Browser Use requires manual browser profile management and session syncing through CLI commands. You track when sessions expire and refresh authentication as needed. Proxy network configuration works in self-hosted setups or through their cloud API, but requires additional infrastructure setup for reliable operation. Bottom line: Browser Use fits organizations with existing infrastructure and Python expertise who focus on deployment control over managed convenience.
Airtop
Airtop appeals to teams that prefer managed services without server responsibilities. Their AI agents interact with websites through natural language APIs, adapting to layout changes without manual selector updates. The service operates entirely in the cloud through API calls. You scale by increasing API usage instead of managing server capacity. Airtop handles browser updates and server management automatically, and includes proxy rotation and anti-bot detection systems as part of their managed cloud infrastructure. The platform integrates with LangGraph using subgraphs to build modular automation sequences, supporting both no-code interfaces for simple workflows and API access for complex integrations.
Where Airtop excels is authentication handling. The service manages OAuth and multi-factor authentication flows automatically through managed cloud browsers, maintaining browser sessions in the cloud for reuse across automation runs. This removes much of the manual credential management that plagues other tools. The tradeoff is complete dependency on their cloud infrastructure. There is no option to self-host or maintain direct control over browser instances. Bottom line: Airtop works for projects needing quick deployment without infrastructure setup, especially when authentication complexity is a primary concern.
How Skyvern Solves These Challenges Better
We built Skyvern to tackle those fundamental challenges that make browser automation fragile and hard to scale. Instead of building another tool with the same underlying limitations, we took a different approach. If you're new to our platform, check out our guide on getting started with Skyvern to see how quickly you can set up your first workflow.
Our computer vision-based system interprets websites the way humans do, eliminating the fragile selector problem entirely. When a button moves or a form layout changes, Skyvern adapts automatically. You don't maintain XPath expressions or CSS selectors that break with every website update. This cuts ongoing maintenance work dramatically compared to selector-based tools.
For authentication, we include native 2FA support, CAPTCHA solving, and proxy networks out of the box. You don't configure additional services or manually manage session persistence. Skyvern handles TOTP codes, solves CAPTCHAs automatically, and rotates through proxy networks with geographic targeting. These capabilities work from day one without extra infrastructure setup.
We offer deployment flexibility that Browser Use and Airtop don't match. Run our open source version on your own servers for complete control, or use our managed cloud service to eliminate infrastructure management. The API stays simple either way. You're not locked into cloud-only operation like Airtop, and you're not forced to manage infrastructure like self-hosted Browser Use.
Our vision-based approach makes cross-site workflows practical. A single Skyvern workflow operates across large numbers of websites without site-specific code. The system understands form structures, button locations, and navigation patterns regardless of how each site implements them. This makes scaling to hundreds of sites achievable instead of theoretical.
We provide transparent pricing with no hidden fees, parallel execution for scaling automations, and structured data extraction with JSON and CSV schema support. Most enterprises see 60-80% cost savings switching from traditional automation to AI-powered platforms, with median payback periods under 12 months.
For teams dealing with brittle scripts or manual workflows across multiple websites, Skyvern provides a more reliable solution that actually works in production.
Side-by-Side Comparison
Feature | Browser Use | Airtop | Skyvern |
|---|---|---|---|
Technical Approach | Python library using AI models to control browsers through natural language; supports OpenAI, Google, Anthropic, or local models through Ollama | Cloud-based service with natural language APIs; AI agents interpret and execute browser tasks through managed infrastructure | Computer vision + LLM system that interprets websites like humans do; eliminates selector dependencies while maintaining AI capabilities |
Deployment Options | Self-hosted on your infrastructure or cloud service for production deployments | Cloud-only through API calls | Open source self-hosted or managed cloud service with identical API |
Selector Maintenance | Reduces brittleness through AI interpretation but still uses underlying browser automation that can break with layout changes | AI agents adapt to layout changes through natural language understanding | Zero selector maintenance; computer vision adapts automatically to any layout change |
Authentication Handling | Manual browser profile management and CLI session syncing; you track expiration and refresh credentials | Automatic OAuth and 2FA flow handling through managed cloud browsers; maintains sessions automatically | Native 2FA, TOTP, and CAPTCHA solving built-in; automatic session management with no manual intervention |
CAPTCHA Support | Requires additional infrastructure setup; not included natively | Managed through cloud service layer but may require configuration | Built-in CAPTCHA solving that works out of the box |
Proxy Networks | Configure in self-hosted setup or through cloud API | Managed proxy rotation through service layer | Native proxy network with geographic targeting (country, state, ZIP) included |
Infrastructure Management | You provision servers, manage Chrome instances, handle updates, and plan scaling capacity | Fully managed; no server management required | Choose your deployment: manage yourself or use managed cloud with anti-bot detection |
Setup Complexity | Install SDK, configure AI model, write Python integration code, manage error handling and retry logic | API calls with natural language descriptions; LangGraph integration for complex workflows | Simple API with YAML-based workflow definitions; works immediately without custom integration code |
Cross-Site Workflows | Natural language task descriptions reduce site-specific code but still require configuration per site | Modular sequences through LangGraph; works across sites but may need adjustments | Single workflow operates across unlimited websites without site-specific modifications |
Parallel Execution | Manual capacity planning required; running N tasks means managing N browser instances | Scale through API usage; infrastructure handles parallelization automatically | Built-in parallel execution in managed cloud; configure based on needs in self-hosted |
Cost Model | Self-hosted: infrastructure costs + local model costs; Cloud: per-session usage fees | API usage-based pricing; scales with automation volume | Transparent pricing with no hidden fees; self-hosted option eliminates per-session costs |
Ideal For | Teams comfortable with Python and AI model APIs wanting code-level control; organizations with existing infrastructure for self-hosting | Teams preferring managed services without server responsibilities; projects needing quick deployment without infrastructure setup | Companies with brittle automation scripts, manual workflows across multiple websites, or needing production-ready automation that adapts to website changes |
Final Thoughts on Browser Use vs Airtop
Browser Use works well if you want code-level control and already run Python infrastructure, while Airtop fits teams that prefer managed cloud services without server responsibilities. Both tools advance browser automation beyond basic scripting, but vision-based detection matters more than most teams realize until their selectors break for the third time this month. But, we designed Skyvern around that reality with built-in authentication handling and automatic adaptation to layout changes. The difference shows up in production environments where website updates don't break your workflows and authentication challenges don't require constant manual intervention. Book time with us if you want to discuss how this fits your automation needs.
FAQ
What's the main difference between Browser Use and Airtop?
Browser Use is a Python library you install and run on your own servers, giving you control over infrastructure but requiring you to manage browsers and scaling yourself. Airtop runs entirely in the cloud through API calls, removing infrastructure management but creating dependency on their service.
Which tool is better for handling authentication workflows?
Airtop handles OAuth and multi-factor authentication flows automatically through managed cloud browsers, while Browser Use requires manual browser profile management and session syncing through CLI commands. Both still require you to track session expiration and refresh credentials when needed.
How do deployment requirements differ between these tools?
Browser Use requires provisioning your own servers, managing Chrome instances, and planning capacity for parallel execution. Running 50 tasks means handling 50 browser instances. Airtop eliminates server management by running everything through their cloud API, letting you scale by increasing API usage instead of managing compute resources.
Can I run these tools without writing code?
Browser Use requires Python code to connect AI models to browser automation and build workflows. Airtop offers both a no-code interface for non-technical users and API access for developers building production integrations.
Which tool costs less to run at scale?
Browser Use lets you run local models through Ollama for cost control and supports self-hosted deployment to avoid per-session cloud fees, though you handle infrastructure costs. Airtop pricing depends on API usage volume, which can increase quickly with parallel automations but removes server expenses.