Crawl4AI vs Firecrawl
Two of the top data and scraping for ai, side by side: score, setup, license, activity and what each review found.
Crawl4AI
Python crawler that turns pages into LLM-ready markdown, with a Docker API
Firecrawl
Web scraping and crawling API that returns LLM-ready markdown
| What we compare | Crawl4AI | Firecrawl |
|---|---|---|
| Score parts, out of 100 | ||
| Adoption | 70, popular | 99, widely used |
| Freshness | 100, active | 100, active |
| Maintenance | 82, healthy | 45, patchy |
| Easy to run | 67, easy | 33, some setup |
| Agent-ready | 0, none | 70, partly |
| Facts from GitHub and the README | ||
| Stars | 85.2k | 190.3k |
| License | Apache-2.0 (permissive) | AGPL-3.0 (copyleft) |
| Last commit | Oct 2026 | Oct 2026 |
| Last release | Sep 2026 | Jun 2026 |
| Language | Not stated | Not stated |
| Docker | Yes | Yes |
| GPU | Not needed | Not needed |
| arm64 or Apple Silicon | Mentioned | Not stated |
Crawl4AI
Async Playwright crawler (pip install crawl4ai) that renders pages in Chromium, Firefox or WebKit and emits clean or filtered markdown, with CSS, XPath and regex extraction needing no LLM, or LLM extraction via any LiteLLM provider. Deep crawling (BFS, DFS, priority-scored) and adaptive crawling are built in. A Docker server on port 11235 exposes /md, /html, /crawl, /screenshot, /pdf and MCP behind an API token.
Who it is for: Developers building scrapers and RAG ingestion pipelines
Strengths
- Structured extraction with CSS, XPath or regex schemas needs no LLM or API key
- Docker server with REST, streaming crawl, MCP, dashboard and playground; amd64 and arm64
- Deep crawl strategies with crash recovery via resume_state
- Persistent browser profiles, CDP remote browsers and an undetected-browser adapter
Weaknesses
- Apache-2.0 but requires attribution (badge or text) in your project
- Docker server answers only inside the container until CRAWL4AI_API_TOKEN is set
- Web search and answer endpoints exist only in the paid cloud
- Runs full browsers; the docker run example allocates 1 GB shared memory
- no GPU
- Docker + Compose
- Needs Playwright Chromium (installed by crawl4ai-setup)
- Models: any LiteLLM provider for LLM extraction (OpenAI, Ollama and others)
- port 11235
Firecrawl
API that turns URLs into markdown, HTML, screenshots or schema-based JSON, with endpoints for search, scrape, crawl, map, batch scrape, page interaction and a prompt-driven agent. Handles JS-rendered pages and parses hosted PDFs and DOCX. SDKs for Python, Node, Go, Java, Elixir, Rust and Ruby plus an MCP server and CLI, for teams feeding web content to RAG pipelines and agents.
Who it is for: Teams feeding web content to RAG pipelines and agents
Strengths
- Seven SDKs plus CLI and MCP server; SDKs poll async crawl jobs automatically
- Crawl, map and batch-scrape endpoints return job IDs for large sites
- Scrape supports actions (click, scroll, write, wait) before extraction
- Compose file at the repo root for self-hosting
Weaknesses
- README is written around the hosted API and keys; self-hosting lives in separate docs
- AGPL-3.0 license; network use of a modified version triggers source obligations
- Agent endpoint runs the hosted spark-2 model, not a local LLM
- Proxy rotation and anti-bot handling are hosted-service features
- no GPU
- Compose