Buying snapshot
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| Decision point | What Browser Use states |
|---|---|
License | The Python library is free and MIT-licensed. Model inference and hosted browsers are charged separately by the API provider or Browser Use Cloud. |
Deployment paths | Three paths: fully hosted Cloud (Browser Use runs the agent and browser), a CLI that gives an existing coding agent browser access, or the Python library in your own code. The CLI and library can each use a local or cloud browser. |
Self-hosting | You can host the Python library and browsers on your own infrastructure. An on-prem option runs browsers and agents inside your network. |
Installation | Python >= 3.11; install with uv add browser-use. |
Model choice | Providers directly through wrappers such as ChatOpenAI, ChatAnthropic and ChatGoogle with each provider's key; provider-prefixed models through the ChatBrowserUse gateway; or a local model through Ollama, subject to your hardware. |
Concurrency | 10 concurrent sessions to start, shared between agents and browsers. The limit rises with total paid per project: 50 at $100, 250 at $1,000, 500 at $5,000, 1,000 at $25,000; more on request. The limit never goes down. Projects created before tiers launched and AWS Marketplace subscriptions keep their existing limits. |
Compliance | Browser Use lists SOC 2 Type II and HIPAA; zero data retention is listed with its Enterprise offering. |
Our take
Choose Browser Use if your team writes Python and wants one agent codebase that can start on a local browser and later move to managed cloud browsers with a one-line change. If you need a fixed monthly price or guaranteed access to every site, test your own target pages on the $1 credit before you commit to prepaid top-ups.
Evaluate BU
Where it stands out
Local to cloud with one line. Setting Browser(use_cloud=True) runs the same agent on a cloud browser, with no Chrome to install, so it works in Docker, CI and serverless. Cloud browsers add stealth, residential proxies, CAPTCHA solving and a live view URL.
Works with your own agent too. Browser Infrastructure accepts your own agent, Playwright or Puppeteer over CDP, so you can rent browsers without adopting the Browser Use agent.
Replay without a model call per step. You can save a successful run and replay its clicks and typing with new values. Extract steps and the closing summary still call the model, so repeat jobs need fewer model calls.
Vendor-reported bot-wall results. In Browser Use's own test of 200 visits to 100 bot-protected sites, Headless Chrome got through on 3.0% and Browser Use on 90.5%. Treat this as the vendor's benchmark and check your own sites.
Active integration work. Release 0.13.13 (15 Oct) added an OpenAI browser-tool driver with 18 default browser tools, and the repository maintains Browser Use toolsets for Claude that implement 31 browser actions.
Product screenshot
Trade-offs to weigh
The costly traffic option is the default. Residential proxies are on by default, so traffic, not browser hours, can drive the bill. Switching to a direct connection or your own proxy changes the traffic rate, but your proxy provider may charge separately.
Parallel capacity is bought with prepayment. The published concurrency tiers count successful USD payments per project, net of refunds; free credits and disputed payments do not count. Size top-ups around the parallel sessions you need, or ask Browser Use for more than the tiers give.
No guaranteed access. Browser Use says results depend on the site and challenge, and no browser configuration guarantees that every CAPTCHA can be avoided or solved.
Cloud logins may need repeating. Profile sync transfers cookies, not local storage, IndexedDB or extensions, so some sites may ask you to sign in again.
Replays break when pages change. A replay raises RuntimeError at the first step it cannot match, and the steps before it have already run. Saved run files can still contain secrets in page snapshots and results, so keep them private.
Pricing and plan conditions
Browser Use is pay as you go: no subscription plans are offered, and you buy credits that never expire. New eligible Google, GitHub or Microsoft signups get a $1 free credit once per person, with no card required. The minimum top-up is $5 and unlocks every model. Browser time is rounded up to whole minutes with a 1-minute minimum. For hosted agents, the vendor's worked example is $1 in model tokens + 20% service fee → $1.20, and browser time and traffic are extra. If you bring your own model key, you pay your provider directly and Browser Use charges 20% of published token rates, including cached rates, plus browser time and traffic. Existing legacy subscribers can still manage billing.
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| Charge | Published price | What it covers |
|---|---|---|
Cloud browsers | $0.02 / hour | Browser time, plus proxy traffic |
Residential proxy traffic | $5 / GB | On by default; routes traffic through another IP |
Direct or your own proxy | $0.20 / GB | Used instead of residential proxies; your proxy provider may charge separately |
Web agents | Model + 20% | Hosted agent runs; browser time and traffic are extra. Per-model token prices (API V4, USD per 1M tokens) already include the 20% fee |
Custom model API (BU 2.0) | $0.60 input, $0.06 cached input, $3.50 output per 1M tokens | Use the Browser Use model with your own agent |
Public signals
About these signals
Verified factual signals from public sources. They indicate observable activity or interest, not total adoption, product quality, or cost.
406 GitHub commits 90d120.4k GitHub stars0 vulnerabilities across 1 package
See all signals from 5 sources
PyPI · browser-use-sdk@3.12.1
Alternatives to BU
Where BU sits against the products teams weigh it up with.
See detailed alternatives analysis
If you are exploring BU alternatives, you are likely looking for AI agent platforms that can automate browser-based tasks, manage terminal operations, or maintain persistent context across sessions. BU offers a compelling approach to deploying fully autonomous agents with browser access, terminal capabilities, and built-in integrations for tools like Slack, Gmail, and Linear. However, depending on your specific workflow requirements, infrastructure preferences, or budget constraints, several other platforms in the AI agents space may be a better fit.
We have evaluated the leading alternatives across architecture, pricing, and use-case fit to help you make an informed decision.
Top Alternatives Overview
LangChain is the most established platform in the AI agent engineering space, offering a comprehensive suite of open-source frameworks (LangChain, LangGraph, deepagents) alongside LangSmith, its commercial observability and deployment platform. LangChain provides native tracing, evaluation pipelines, prompt management, and a scalable deployment runtime with support for human-in-the-loop interactions. It is model-agnostic and supports Python, TypeScript, Go, and Java SDKs, making it one of the most flexible options available.
Granary by Speakeasy takes a fundamentally different approach as a CLI-based context hub built in Rust. It focuses on session tracking, task orchestration, and structured handoffs between agents. Granary is entirely local-first, storing all state in SQLite with no network dependency, which makes it attractive for teams that need data to stay on their machines. It supports concurrent agent workflows through lease-based task claiming.
LedgerMind specializes in autonomous memory management for AI agents. Built on SQLite and Git with a reasoning layer, it provides self-healing memory that resolves conflicts, distills experience into rules, and evolves without human intervention. This makes it particularly suited for multi-agent systems and on-device deployments where memory persistence and conflict resolution are critical.
Architecture and Approach Comparison
Browser Use presents two cloud offerings: Browser Use Agents, which complete assigned tasks, and Browser Infrastructure, which powers an agent or automation connected to managed browsers. The official documentation describes browser agents that can receive a task and return completed work, alongside browser infrastructure for managed browsers.
The open-source Browser Use library can also be installed locally for browser automation. Its repository describes agents opening pages, clicking, typing, and filling forms, and identifies the library as free and open source under the MIT License.
The public documentation does not provide equivalent architecture details for the other alternatives in this comparison. A like-for-like assessment of their execution environments, integrations, memory, coordination, or observability capabilities therefore cannot be made from the available evidence.
Pricing Comparison
Browser Use starts free and then bills pay as you go. Browser Infrastructure is listed at $0.02 per browser hour.
Browser Use sells no subscription plans. Usage draws on prepaid credits, bought from $5, that never expire. Residential proxy traffic is billed at $5 per GB, or $0.20 per GB on a direct or bring-your-own proxy.
The public documentation does not provide current pricing or licensing details for the other alternatives in this comparison, so it cannot support a reliable price comparison. Buyers should confirm which Browser Use service they need, whether their expected usage is billed as agent tasks or browser hours, applicable credit and overage terms, concurrency limits, and the conditions for any displayed per-task figure.
When to Consider Switching
Consider moving away from BU if your primary need is building custom agent logic with fine-grained control over execution flows. LangChain's framework approach gives developers extensive control over how agents reason, branch, and recover from errors, and its sizable open-source community means a wide range of integrations, tutorials, and third-party tooling are available.
If your agents operate in multi-agent environments where coordination and context sharing are the bottleneck, Granary provides purpose-built infrastructure for session management and task orchestration that general-purpose agent platforms typically lack.
Teams running agents on-device or in air-gapped environments should evaluate LedgerMind for its autonomous memory management and Granary for its local-first architecture. Both tools keep all data on your machine with no external network calls.
Migration Considerations
Moving from BU to another agent platform requires careful planning around three areas: workflow logic, integrations, and state management.
If you have built workflows that rely on Browser Use browser automation and website interaction, you will need to find equivalent browser tooling in your target platform. LangChain supports browser tools through its ecosystem but requires explicit setup. Granary and LedgerMind do not provide browser access at all, as they focus on coordination and memory respectively.
For teams using BU's built-in integrations with services like Slack, Gmail, and Linear, verify that your target platform supports the same connectors or that you can build them. LangChain has the broadest integration ecosystem.
Persistent memory and file system state in BU will need to be mapped to the equivalent in your new platform. LedgerMind's autonomous memory system provides the most sophisticated alternative for long-lived agent state, while Granary's session tracking handles run-to-run context handoffs. LangSmith's deployment layer offers durable checkpointing and memory threading for production agent deployments.
We recommend running a parallel evaluation period where you test your most critical workflows on the new platform before fully committing to a migration. Start with a single workflow, validate the output quality and reliability, and expand from there.