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Firecrawl vs. Browser Use

Browser Use automates browsers.
Firecrawl automates data extraction.

Scrape, search, and interact with the web to get clean data for AI agents and apps.
No multi-step agents to orchestrate, per-step LLM costs, or browser sessions to manage.

Trusted by 80,000+
companies
of all sizes
[ 01 / 08 ]
·
Why Firecrawl

See why teams choose Firecrawl over Browser Use.

When comparing Firecrawl vs Browser Use, the difference comes down to getting structured data from one API call instead of orchestrating multi-step browser agents.

apple.com
Endpoint
Scrape
Status
Success
Started
Mar 16, 2026
2:51 PM
Formats
Markdown
JSON

Clean, structured data from any URL

Firecrawl returns LLM-ready markdown and structured JSON in one API call — no multi-step agent needed. Browser Use orchestrates AI agents that control browsers and return task completion status, which adds latency and LLM cost to every extraction.

See use cases
Pages scraped
Last 7 days
1.2M
Mar 12
48,200 credits
03/0903/1203/16

Predictable pricing that scales

Firecrawl charges one credit per scrape with plans from $83/mo for 100k credits. Browser Use bills per agent step (LLM cost), plus task initialization, browser session time, and proxy bandwidth — making costs hard to predict at scale.

See pricing
URL
Crawl
Scrape
acme.com/pricing
312ms
287ms
docs.example.io
445ms
391ms
blog.corp.dev/ai
528ms
462ms
shop.store/items
376ms
341ms
news.site/latest
489ms
418ms
app.saas.co/api
298ms
264ms

Sub-second response times

Firecrawl returns data in milliseconds, built for real-time pipelines. Browser Use agents take 3-8 seconds per step, and most extraction tasks require multiple steps — adding up to 15-80 seconds for workflows that Firecrawl handles in one call.

See benchmarks
[ 02 / 08 ]
·
Benchmarks

Firecrawl leads on extraction quality.
And so much more.

Coverage
0%
success rate
Quality
0.000
F1 score for accuracy
Recall
0.000
content recall rate
Speed
0ms
P95 latency
[ 03 / 08 ]
·
Firecrawl vs. Browser Use

Firecrawl is purpose-built for AI agents and developers.

One API call to scrape, search, interact, and more - no browser agents needed.

JS / React rendering
Firecrawl
Browser Use
Browser actions
Firecrawl
Browser Use
Open source + self-hostable
Firecrawl
Browser Use
LLM-ready output by default
Clean markdown & structured JSON on every request, no post-processing
Firecrawl
Browser Use
Crawl entire websites
One API call crawls thousands of pages with automatic sitemap discovery
Firecrawl
Browser Use
Search + extract in one API call
Unified pipeline for web search with full content extraction
Firecrawl
Browser Use
Predictable credit-based pricing
1 credit per scrape, plans from $83/mo for 100k credits
Firecrawl
Browser Use
Sub-second data extraction
Returns structured data in milliseconds, built for real-time pipelines
Firecrawl
Browser Use
Simple setup, one API call
Get data from any URL with a single API call — no agent orchestration needed
Firecrawl
Browser Use
Browser interaction (interact endpoint)
Click, fill forms, and navigate pages programmatically before scraping
Firecrawl
Browser Use
AI agent self-onboarding
Agents choose their integration path and are ready after a single authorization
Firecrawl
Browser Use
[ 04 / 08 ]
·
Customer Testimonials
[ 05 / 08 ]
·
FAQs

Frequently asked questions

The core difference between Firecrawl and Browser Use is scope and approach. Browser Use is a browser automation framework — AI agents interpret natural language instructions to control a Chrome browser, which is powerful for interactive workflows but returns task completion results rather than clean data. Firecrawl is purpose-built for AI data extraction: every request returns clean LLM-ready markdown or structured JSON, with crawling, search, and browser interaction all under one API key. If you compare Firecrawl and Browser Use for bulk data extraction or AI pipelines, Firecrawl delivers structured output in a single call without per-step LLM costs or browser session management.
Yes. AI agents can self-onboard to Firecrawl by choosing the integration path that fits the task — replacing native fetch and search with Firecrawl's scrape, search, and interact endpoints, or embedding the API directly into the app they're building. Once you authorize, they're ready to go. Browser Use requires configuring an LLM provider, defining agent tasks, and managing browser sessions for each workflow, which adds significant setup friction compared to Firecrawl's single-call model.
Yes. Firecrawl returns clean markdown and structured JSON on every request with no post-processing needed. Browser Use is designed for browser automation — its agents interact with web pages and return task completion results, but structured data extraction requires configuring agent steps and output schemas.
Firecrawl uses credit-based pricing starting at 1 credit per page for standard scrapes, with plans from $83/month for 100k credits. Browser Use charges per-step LLM costs ($0.002-$0.05/step depending on model), plus $0.01 per task initialization, $0.06/hour for browser sessions, and $10/GB for proxy bandwidth. For data extraction at scale, Firecrawl's flat per-page pricing is simpler to predict.
Yes. Firecrawl's Browser endpoint supports clicks, form fills, scrolling, and multi-step interactions through a simple API — no LLM agent needed. Browser Use takes a different approach by using AI agents that interpret natural language instructions to control browsers, which is powerful for complex workflows but adds latency and cost per step.
Yes. Firecrawl is fully open source under the AGPL-3.0 license and can be self-hosted with Docker for complete control over your data, compliance, and infrastructure. Browser Use is also open source under the MIT license with self-hosting support, though their cloud features like stealth browsers and CAPTCHA solving require the managed service.
Yes. Firecrawl's crawl endpoint processes thousands of pages with a single API call, with automatic sitemap discovery, depth control, and path filtering. Browser Use does not have a crawling API — agents navigate pages one at a time, which makes large-scale site crawling impractical.
Firecrawl returns data in sub-second response times, optimized for real-time pipelines. Browser Use agents take 3-8 seconds per step, and most tasks require multiple steps. For a simple data extraction that Firecrawl handles in one API call, Browser Use might need 5-10 agent steps taking 15-80 seconds total.
Firecrawl is purpose-built for AI data pipelines. It returns clean markdown ready for chunking and embedding, with structured extraction via natural language prompts or JSON Schema, plus site-wide crawling for building comprehensive knowledge bases. Browser Use is optimized for browser automation tasks like form filling and workflow automation, not bulk data extraction.
If you're using Browser Use primarily for data extraction, migrating is straightforward. Replace your agent task configuration, LLM provider setup, and multi-step extraction logic with a single Firecrawl API call. For example, a Browser Use task that navigates to a URL and extracts content across multiple agent steps becomes one call to Firecrawl's /scrape endpoint that returns clean markdown. Firecrawl offers SDKs for Python, Node.js, Go, Rust, and Java. Most teams complete the migration in under a day.
Yes. Firecrawl is SOC 2 Type II compliant with GDPR compliance and DPA available. Enterprise plans include zero data retention and 99.9% SLA. You can self-host for air-gapped environments or use the managed cloud. Over 500,000 developers and 80,000+ companies use Firecrawl.
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