crawl4ai vs llama_index
The two are close in size: 84.6k stars for crawl4ai, 52.4k for llama_index.
Neither one leads on the six capability axes, so the choice comes down to which of them fits the way you already work.
Stars and commit dates come from our own daily tracking. The six axes are read off each project's documentation by our review pipeline, so they describe what a project says about itself, not what we measured in its code.
Where they stand today
Open-source crawler that turns any website into LLM-ready Markdown with full browser control and optional hosted cloud + agent MCP integration.
- Stars
- 84.6k
- Tracked growth
- not tracked long enough
- Maturity
- ●●●●●
- Last commit
- 6d ago
- Language
- Python
- License
- Apache-2.0
- Cost to run
- Free to self-host; Crawl4AI Cloud is pay-as-you-go (first $10 free promotion)
A data-first RAG framework focused on document agents and agentic OCR with extensive indexing, retrieval, and 300+ integrations.
- Stars
- 52.4k
- Tracked growth
- +2.7%
- Maturity
- ●●●●●
- Last commit
- 2d ago
- Language
- Python
- License
- MIT
- Cost to run
- Your API key (or optional LlamaParse cloud)
Six axes, head to head
Each axis runs 0 to 5. The label under a score is what that project's own docs claim, not a category average.
| Axis | crawl4ai | llama_index |
|---|---|---|
Context depth How much of your codebase it sees before it answers: the open diff, the diff plus related files, or the whole repository. | ●●●●● Whole-site crawl | ●●●●● Whole-data ingestion |
Noise control How it keeps output volume down — severity thresholds, deduplication, incremental runs over new commits only. | ●●●●● Filters (BM25/LLM) | ●●●●● Rerankers + filters |
Customization How far it bends to your team: custom rules, prompts, style guides, per-path config. | ●●●●● Extensive configs | ●●●●● Highly extensible |
Privacy Whether your code stays on your own infrastructure: fully local, self-hostable, or cloud API only. | ●●●●● Fully local possible | ●●●●● Local model support |
Model freedom Whether you can point it at any provider, or it is wired to one. | ●●●●● Bring-your-own models | ●●●●● BYO models & keys |
Setup ease What it takes to get a first useful run out of it. | ●●●●● One-command setup | ●●●●● Config + API key |
Which one to pick
Pick crawl4ai if…
Privacy-first — self-host the browser and server to keep pages local while getting clean, LLM-friendly Markdown and structured extraction.
Pick llama_index if…
Document-agent focused — pick LlamaIndex when you need a flexible, extensible RAG/document-agent/OCR framework with strong local model and integration support.
What people want from each one
unclecode/crawl4ai
run-llama/llama_index
Questions people ask
Is crawl4ai better than llama_index?
Neither one leads on the six capability axes, so the choice comes down to which of them fits the way you already work. crawl4ai is worth picking when privacy-first — self-host the browser and server to keep pages local while getting clean, LLM-friendly Markdown and structured extraction.
Which of crawl4ai and llama_index keeps my code private?
crawl4ai: Fully local possible (5/5). llama_index: Local model support (5/5).
What does each one cost to run?
crawl4ai: Free to self-host; Crawl4AI Cloud is pay-as-you-go (first $10 free promotion). llama_index: Your API key (or optional LlamaParse cloud).
Full profiles: unclecode/crawl4ai and run-llama/llama_index. Everything else in RAG & retrieval.