A developer building a PDF Q&A bot
- pip install llama-index-core and an LLM integration
- Load PDFs and build an index
- Query the index from the app
needs API key
LlamaIndex · Open-source framework and document parsing platform
LlamaIndex
Open-source framework for connecting LLMs to your data, plus the commercial LlamaParse document platform.
- Provider
- LlamaIndex
- Latest confirmed model
- Not applicable / not verified
- Pricing
- Free plan + paid
- Free plan
- Yes
- API
- Yes · free quota
- Status
- Generally available
- Last verified
- Oct 19, 2026
What is LlamaIndex?
LlamaIndex is an MIT-licensed Python framework with data connectors, indexes and retrieval tools for building agents over your own documents. The company's commercial product, LlamaParse, turns complex files such as PDFs into clean structured data using credit-based pricing. The maintainers say their main focus has shifted to LlamaParse.
Getting messy documents into a form that LLMs can search and reason over accurately.
Why use LlamaIndex?
Practical benefits
- Free open-source framework
- Many data connectors and integrations
- LlamaParse handles complex document layouts
- Free LlamaParse tier with 10K credits
Who it suits
- Developers building document Q&A
- Teams processing PDFs and reports
- RAG engineers
When another tool may fit better
- Simple chat apps without document data
- Teams avoiding Python
- Users wanting a fully open-source parser (LlamaParse is commercial)
- Learning curve
- Some experience helps
- Skills needed
- Python programming.
Example workflows
- pip install llama-index-core plus an LLM integration, load documents, build an index and query it
What can it do?
- Open-source frameworkConnectors, indices and retrieval interfaces; modular packages.
- WorkflowsOpen-source building blocks for agent workflows.
- LlamaParseCommercial parsing from about 1 credit per page; layout-aware agentic parsing costs more.
- IntegrationsSeparate packages such as llama-index-llms-openai.
Good for
- Document Q&A
- Extracting tables and data from PDFs
- Knowledge assistants
- Agentic document workflows
Where it runs
Pricing and plans
Free plan + paid The LlamaIndex framework is free under MIT. LlamaParse plans: Free with 10K credits, Starter $50/month (40K credits), Pro $500/month (400K credits) and custom Enterprise; 1,000 credits cost $1.25.
| Plan | Price | Billing | Free trial / tier | Usage limits | Main inclusions | Model access | API access | Restrictions |
|---|---|---|---|---|---|---|---|---|
| LlamaIndex open source | Free | per month | Free tier | — |
|
Any supported provider | N/A (library) | — |
| LlamaParse Free | Free | per month | Free tier | 10K credits/month |
|
— | Yes | No pay-as-you-go |
| LlamaParse Starter | $50/mo | per month | — | 40K credits included; pay-as-you-go up to 400K credits |
|
— | Yes | — |
| LlamaParse Pro | $500/mo Limited-time one-time 800K bonus credits for business emails | per month | — | 400K credits included; pay-as-you-go up to $5,000/month |
|
— | Yes | Bonus credits expire on downgrade |
| LlamaParse Enterprise | Contact provider | per month | — | Volume discounts |
|
— | Yes | — |
API and developer access
- Official API
- Yes
- Documentation
- API docs (opens in a new tab)
- Authentication
- API key (LlamaParse)
- Pricing model
- per credit (1,000 credits = $1.25)
- Free API quota
- LlamaParse Free: 10K credits per month
- Rate limits
- Not documented
- Context / input limits
- Not documented
- SDKs
- Python (llama-index-core)
- Streaming
- Not documented
- Batch processing
- Not documented
- Structured output
- Not documented
- Tool / function calling
- Not documented
- Commercial use
- MIT licence for the framework; LlamaParse is commercial
- Data retention & privacy
- See the provider privacy terms
Published API rates
| Item | Price | Unit |
|---|---|---|
| LlamaParse credits | $1.25 | per 1,000 credits |
A free LlamaIndex account is not the same thing as free API access. The API allowance above is the provider's documented developer quota.
Advantages and disadvantages
Advantages
- Strong focus on data and documents
- MIT licence
- Clear credit pricing ($1.25 per 1,000 credits)
Disadvantages
- LlamaParse is not open source
- Framework is no longer the company's main focus per its README
- Credit cost per page varies by parsing mode
Privacy: The framework runs in your environment; LlamaParse processes documents on LlamaIndex's service.
Real-world examples
An analyst parsing financial reports
- Sign up for LlamaParse Free (10K credits)
- Upload reports for parsing
- Export structured output
free plan works
A company processing large volumes
- Subscribe to Pro ($500/month, 400K credits)
- Run layout-aware parsing
- Feed results into a RAG pipeline
needs paid plan
LlamaIndex alternatives
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LlamaIndex vs LangChainCrewAI
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LlamaIndex vs CrewAIChroma
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LlamaIndex vs ChromaPinecone
Fully managed vector database for semantic search and retrieval-augmented generation.
LlamaIndex vs PineconeFrequently asked questions
Is LlamaIndex free?
The LlamaIndex framework is open source under the MIT licence and free to use. LlamaParse, the document parsing service, has a free tier of 10K credits.
What is LlamaParse?
A commercial, not open-source, platform that parses complex documents into structured data for AI use.
How much do LlamaParse credits cost?
1,000 credits cost $1.25. Basic parsing can be as low as 1 credit per page; advanced modes cost more.
How do I install LlamaIndex?
pip install llama-index-core, then add integration packages such as llama-index-llms-openai.
Is LlamaIndex still maintained?
Yes, but its README says the team's main focus has shifted to LlamaParse.