Firecrawl CLI gives agents the complete web data toolkit for scraping, searching, and browsing. Try it now →
Trusted by 80,000+
companies of all sizes
companies of all sizes
[ 01 / 08 ]
·
Why Firecrawl
See why teams choose
Firecrawl over Jina AI.
When comparing Firecrawl vs Jina AI, the difference comes down to clean data, a complete web data toolkit, and predictable pricing.
apple.com
Endpoint
Scrape
Status
Success
Started
Mar 16, 2026
2:51 PM
Formats
Markdown
JSON
Clean, reliable data for AI pipelines
Turn any URL into clean, structured data that your AI agents and apps can use.
See use casesScrape
Search
Crawl
Agent
Browse
The complete web data toolkit
Search, scrape, browse, and more with a single API. No stitching tools together.
See docsPages scraped
Last 7 days
1.2M
Mar 12
48,200 credits
03/0903/1203/16
Predictable pricing that scales
One credit per scrape. No variable token costs that change with page length.
See pricing[ 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. Jina AI
Firecrawl is purpose-built for
AI agents and developers.
The best Jina AI alternative is one that goes beyond single-page reading to deliver scraping, search, and browser automation in one unified API.
Firecrawl
LLM-ready markdown output
Clean markdown on every request, no post-processing
Markdown via Reader API with configurable style options
JS / React rendering
Cloud browsers included at no extra cost on every plan
Headless Chrome rendering
Structured JSON extraction
LLM-powered extraction with JSON Schema or prompts
Supported via ReaderLM-v2 model with JSON schema input
Cloud browser sessions
Managed browsers with Playwright, Live View, and persistent profiles
No browser automation; requires external tools for page interaction
Web search with full extraction
Multi-source search (web, news, images) with configurable results
Limited to 5 web-only results
Predictable credit-based pricing
From $83/mo for 100k credits; 1 credit per standard scrape
Token-based billing; cost per page varies by content length
URL discovery (map)
Ultra-fast URL discovery for entire websites in one call
Single-URL only; no site-wide URL discovery
[ 04 / 08 ]
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Customer Testimonials
“Firecrawl allows our customers to pull the web information they need directly in our product.”
Andrew Gardner
Sr. Engineer
“If your agent or LLM needs web content, Firecrawl delivers the best-formatted results.”
Zhen Li
Staff AI Engineer
“What makes Firecrawl essential is how it turns messy web data into clean, AI-ready content.”
Steven Tey
Founder & CEO
[ 05 / 08 ]
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FAQs
Frequently asked questions
Yes. Every Firecrawl request returns clean markdown and structured JSON with no post-processing needed. Jina's Reader API also produces quality markdown, powered by their ReaderLM-v2 model. The key difference is that Firecrawl pairs markdown output with crawling, search, and browser automation in one platform, while Jina Reader handles single-page extraction only.
Firecrawl uses credit-based pricing starting at 1 credit per page, with plans from $83/month for 100k credits. Jina uses token-based billing at $0.050 per 1M tokens (Prototype) or $0.045 per 1M tokens (Production). Because Jina charges by output tokens, the cost per page varies with content length, making it harder to predict costs at scale.
Yes. Firecrawl is fully open source under the AGPL-3.0 license with 90k+ GitHub stars and can be self-hosted for complete control over your data and infrastructure. Jina's Reader API is also open source under Apache-2.0 with 10k+ stars and supports self-hosting. Both offer strong open-source options, though Firecrawl's community is significantly larger.
Most developers are productive in minutes. Firecrawl offers SDKs for Python, Node.js, Java, and a CLI, plus a playground for testing. Jina's Reader API also has a fast onboarding path with its simple URL-prefix pattern (r.jina.ai/). Both tools prioritize developer experience, though Firecrawl covers more use cases from a single integration.
Firecrawl is optimized for speed with caching that delivers up to 5x faster responses. Jina's Reader API reports an average latency of 7.9 seconds per request. In independent benchmarks using 1,000 URLs, Firecrawl achieved a 96% coverage rate with a 0.638 F1 accuracy score.
Yes. Firecrawl's /search endpoint combines web search with full content extraction across web, news, and image sources with configurable result counts and filtering. Jina offers web search via s.jina.ai that returns the top 5 results with full markdown, but it is limited to web-only results with no source type or result count configuration.
Firecrawl is purpose-built for AI pipelines. It returns clean markdown ready for chunking and embedding, with crawl support for ingesting entire documentation sites and search for grounding agents with live web data. Jina's Reader API produces high-quality markdown for individual pages, but for RAG workflows that need to ingest many pages from a site, you would need to build your own crawling logic on top of Reader.
Replace your Jina Reader API calls (r.jina.ai/) with Firecrawl's /scrape endpoint, and your s.jina.ai search calls with Firecrawl's /search endpoint. Firecrawl SDKs for Python, Node.js, and Java make swapping straightforward. You also gain access to crawl, map, and browser endpoints that have no Jina equivalent, so workflows you previously built with external tools can be consolidated into Firecrawl.
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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