LlamaIndex
Document OCR and data framework for the agentic stack
Overview
LlamaIndex earned its reputation as one of the two dominant open-source frameworks (alongside LangChain) for building RAG applications, and its 25M+ monthly downloads reflect that it's still widely used for free, self-hosted data pipelines. The newer LlamaParse/LlamaCloud layer addresses a genuinely hard problem — reliably parsing messy real-world documents like scanned PDFs and tables — as a managed, credit-based service so teams don't have to build that parsing logic themselves.
The tradeoff is that the commercial document-OCR pitch now dominates the homepage, which can make it look like LlamaIndex pivoted away from being a free framework entirely — it hasn't, but you'll want to go to the GitHub repo or docs rather than the marketing site if you just want the open-source library. For teams specifically needing document parsing at scale, the LlamaCloud credit system is straightforward, but costs can climb quickly with complex, high-volume documents.
Key Features
Open-source framework: Free Python/TypeScript library for building RAG and agentic data pipelines.
LlamaParse: Layout-aware document parsing for 50+ file types, including tables, charts, and handwriting.
Structured extraction: Schema-based agents pull structured data out of unstructured documents.
LlamaCloud: Managed hosting for indexing, retrieval, and document agents with enterprise SLAs.
Broad integrations: Connects to major vector databases and LLM providers out of the box.
Pricing
Starting price
Free open-source framework; LlamaCloud free tier (10,000 credits/mo), paid from $50/mo
Open-source framework: Free to install and self-host (pip install llama-index).
Free (LlamaCloud): $0/month, 10,000 credits (~1,000 pages), up to 100 users.
Starter: $50/month, 40,000 included credits, pay-as-you-go up to 400,000 additional credits.
Pro: $500/month, 400,000 included credits, pay-as-you-go up to 4,000,000 additional credits.
Enterprise: Custom pricing, volume discounts, 5x higher rate limits, SSO, SaaS or hybrid cloud deployment.
Disclaimer: pricing may change, confirm on LlamaIndex's own pricing page before buying.
Pros
Free open-source core: The underlying framework remains free, well-documented, and widely adopted.
Strong document parsing: LlamaParse handles complex real-world documents (handwriting, tables, multi-page layouts) better than many DIY solutions.
Scales from free to enterprise: Clear path from free tier to paid credits to full enterprise deployment.
Large, active ecosystem: High download numbers and broad integration support with vector databases and LLMs.
Cons
Marketing-heavy homepage: The commercial LlamaParse pitch can obscure that a free OSS framework still exists.
Credit costs scale with complexity: Agentic parsing of complex documents consumes credits fast, and costs can add up for high-volume use.
Competitive framework space: Overlaps significantly with LangChain and Haystack for the core RAG-framework use case.
What Makes It Unique
Document parsing specialization: Where most RAG frameworks treat document ingestion as an afterthought, LlamaIndex built a dedicated, VLM-powered parsing product (LlamaParse) around it.
Kay Score
7.4
/ 10
Tool Information
Pricing
Free open-source framework; LlamaCloud free tier (10,000 credits/mo), paid from $50/mo
Category
Coding & Development
Platform
Web / iOS / Android
Last Updated
