companies of all sizes
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.
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 casesPredictable pricing that scales
Firecrawl charges 1 credit per scrape. Standard covers 100,000 credits at $99/month billed monthly, or $83/month billed annually. 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 pricingSub-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 benchmarksFirecrawl leads on extraction quality.
And so much more.
Internally conducted benchmark, run Jan 13, 2026. Tested 1,000 URLs drawn from diverse public web domains (news, documentation, e-commerce, finance, and more) and measured whether each tool retrieved at least 10% of the expected content — defined as core page text, excluding navigation, ads, and footers. Dataset publicly available at the Firecrawl scrape-content-dataset-v1.
· Figures from the run of Jan 13, 2026
Measured performance
Published Firecrawl results, each with the dataset it was measured on and the date it was run. Follow a row to the run it comes from.
| Metric | Value | Dataset | Measured | Source |
|---|---|---|---|---|
| Coverage (success rate) | 96% | Scrape coverage and quality, 1,000 URLs | Jan 13, 2026 | Methodology |
| Extraction accuracy (F1) | 0.638 | Scrape coverage and quality, 1,000 URLs | Jan 13, 2026 | Methodology |
| Content recall | 0.639 | Scrape coverage and quality, 1,000 URLs | Jan 13, 2026 | Methodology |
| Latency (P95) | 3,387 ms | Scrape coverage and quality, 1,000 URLs | Jan 13, 2026 | Methodology |
Scrape coverage and quality scored against the public dataset firecrawl/scrape-content-dataset-v1, so the inputs are checkable. The harness is not published yet, so the run cannot be reproduced end to end.
Every benchmark Firecrawl runs is listed on /benchmarks.
Firecrawl is purpose-built for
AI agents and developers.
One API call to scrape, search, interact, and more - no browser agents needed.

“Firecrawl allows our customers to pull the web information they need directly in our product.”
“If your agent or LLM needs web content, Firecrawl delivers the best-formatted results.”
“What makes Firecrawl essential is how it turns messy web data into clean, AI-ready content.”
“It was just a matter of plugging in the Firecrawl API, feeding it a URL, and getting clean markdown in return.”
“Firecrawl is the easiest way to extract relevant content from a website.”
“We send over 15 million requests per month to Firecrawl, so every builder has the data they need to bring their app to life.”

















