LangChain
Open-source frameworks for building LLM agents, plus the commercial LangSmith platform for tracing, evaluation, and deployment
FREEMIUM Verified JUL 12, 2026
LlamaIndex
Open-source data framework for LLM apps, plus the commercial LlamaCloud platform for parsing, extracting, and indexing complex documents
LlamaIndex ships a free, MIT-licensed data framework for building RAG systems and agents, plus LlamaCloud — the commercial document platform behind LlamaParse and LlamaExtract. LlamaCloud is credit-billed at $1.25 per 1,000 credits: the free tier includes 10,000 credits/month (~1,000 pages), Starter is $50/month for 40,000 credits, and Pro is $500/month for 400,000. Best for teams turning messy PDFs, tables, and charts into structured data for LLM pipelines.
Verified JUL 16, 2026 FREEMIUM Live
What is LlamaIndex?
LlamaIndex began as an open-source “data framework” for LLM apps — connectors to pull in APIs, PDFs, documents, and SQL; indices and graphs to structure that data; and retrieval interfaces to feed it back into prompts. The framework is MIT-licensed, sees roughly 25 million package downloads a month, and carries 50,000+ GitHub stars. On its own it is a library rather than a product, and the company’s commercial bet sits one layer up.
That commercial layer is LlamaCloud, and its centerpiece is document understanding. LlamaParse uses vision-language models to convert genuinely hard documents — nested tables, charts, scanned scans, handwritten annotations — into clean structured output, with an auto-correction loop to catch its own errors. LlamaExtract pulls records against a schema you define, LlamaCloud Index provides managed chunking and embedding, and Workflows orchestrates multi-step agent processes. Billing runs on credits at $1.25 per 1,000, with parsing modes priced by difficulty: 1 credit per page for plain text, 45 for the most thorough agentic pass. The company reports 1 billion documents processed and 300,000 LlamaParse users, and the platform carries HIPAA, GDPR, and SOC 2 compliance.
Who is it for?
LlamaIndex fits teams whose RAG quality problem is really a parsing problem. If your source documents are clean text, the free framework plus any embedding store is enough and the paid platform is overkill. The value shows up when documents are messy — financial filings with nested tables, scanned contracts, scientific papers with figures — and naive extraction quietly produces garbage that poisons every downstream answer.
- AI engineers building document-heavy RAG who have hit the accuracy ceiling of basic PDF text extraction and need table and chart fidelity.
- Teams in regulated industries — legal, insurance, healthcare, finance — that need HIPAA or SOC 2 coverage and, at the Enterprise tier, hybrid deployment.
- Startups and solo builders who want to prototype for free on the MIT-licensed framework and the 10,000-credit monthly allowance before committing spend.
- Data and platform teams that would rather buy a managed chunking, embedding, and extraction pipeline than build and maintain one in-house.
How much does LlamaIndex cost?
Starting price: $50/mo · Free tier: yes · Model: freemium
Pricing verified JUL 16, 2026
Price history tracked from June 2026
| Plan | Price | Includes |
|---|---|---|
| Free | Free | 10,000 credits/month (~1,000 pages of agentic parsing) · Full open-source LlamaIndex framework and Workflows · Agentic OCR and structured extraction · 1 project, up to 5 indexes · Community support |
| Starter | $50/mo | 40,000 credits included per month · Pay-as-you-go up to 400,000 credits/month · 1 project, up to 50 indexes · Basic email support |
| Pro | $500/mo | 400,000 credits included per month · Pay-as-you-go up to 4,000,000 credits/month · 5 projects, up to 100 indexes · 5x higher rate limits · Priority support via Slack Connect |
| Enterprise | Custom | Volume discounts on credits, custom limits · SaaS or hybrid cloud deployment · Enterprise SSO and MFA · Dedicated account manager |
What are LlamaIndex's key features?
- Open-source, MIT-licensed LlamaIndex framework for data ingestion, indexing, and retrieval
- LlamaParse — VLM-powered document parsing with tiered modes from 1 credit/page (Fast) to 45 credits/page (Agentic Plus)
- LlamaExtract for schema-based structured data extraction from unstructured files
- LlamaCloud Index — managed chunking, embedding, and retrieval pipeline
- Workflows for orchestrating multi-step, stateful agent processes
- LiteParse — local, open-source parsing for PDFs, Office docs, and images
- Support for 130+ file formats and 80+ languages
- HIPAA, GDPR, and SOC 2 compliance on the commercial platform
What people use LlamaIndex for
- 01 Parsing complex PDFs with nested tables, charts, and handwritten text into clean markdown for RAG ingestion
- 02 Extracting structured records (invoices, contracts, scientific papers) against a defined schema with LlamaExtract
- 03 Building stateful, multi-step agent pipelines with the open-source Workflows framework
- 04 Standing up a managed chunking and embedding pipeline via LlamaCloud Index instead of self-hosting one
- 05 Connecting LLM apps to APIs, SQL databases, and document stores through the framework's data connectors
Pros and cons
| Pros | Cons |
|---|---|
| Core framework is free and MIT-licensed, with roughly 25M monthly package downloads and 50k+ GitHub stars | Credit billing gets expensive fast on hard documents: Agentic Plus at 45 credits/page works out to roughly $0.056 per page, so 10,000 complex pages costs well over $500 |
| Parsing quality on hard documents — nested tables, charts, scanned and handwritten pages — is the product's genuine differentiator | The $500/month jump from Starter to Pro is steep, and Starter's pay-as-you-go ceiling caps you at 400,000 credits/month |
| Free tier includes 10,000 credits/month, enough to evaluate on ~1,000 pages before paying | The open-source framework alone is a library, not a product — the managed parsing, indexing, and deployment surface is where the paid lock-in sits |
| Tiered parsing modes let you pay 1 credit/page for simple text and reserve expensive agentic modes for hard pages | Overlapping products (LlamaParse, LlamaExtract, LlamaCloud Index, Workflows, LlamaAgents) make the stack harder to navigate than a single-purpose tool |
What are the best LlamaIndex alternatives?
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How people make money with LlamaIndex
- Build document-processing pipelines for law firms, accounting practices, or insurers — prototype free on the open-source framework and the LlamaCloud free credit allowance, then bill clients for a managed pipeline once volume pushes you onto the Starter or Pro tier
- Offer RAG accuracy audits as a consulting service: parsing quality on tables, charts, and scanned pages is the usual failure point in enterprise RAG, and the Enterprise tier's hybrid deployment is a natural upsell for regulated clients
Frequently asked questions
Is LlamaIndex free?
The LlamaIndex framework is open-source and MIT-licensed, so it is free to use and self-host. The commercial LlamaCloud platform has a free tier that includes 10,000 credits per month — roughly 1,000 pages of agentic parsing — along with 1 project and up to 5 indexes.
How much does LlamaCloud cost?
Credits are priced at $1.25 per 1,000. The free tier includes 10,000 credits/month, Starter is $50/month for 40,000 credits, and Pro is $500/month for 400,000 credits. Enterprise is custom with volume discounts. Starter and Pro both allow pay-as-you-go beyond the included allotment, up to 400,000 and 4,000,000 credits per month respectively.
What is the difference between LlamaIndex and LlamaParse?
LlamaIndex is the open-source data framework for building RAG systems and agents. LlamaParse is a commercial document-parsing service inside LlamaCloud that converts complex PDFs, tables, charts, and handwritten pages into clean structured output. You can use LlamaParse as the ingestion step for a LlamaIndex pipeline, or on its own via API.
How many credits does parsing a page cost?
On the v2 API it depends on the mode: Fast is 1 credit per page, Cost-effective is 3, Agentic is 10, and Agentic Plus is 45. Extras are billed separately — layout extraction adds 3 credits, spreadsheets cost 1 credit per sheet, and audio runs 3 credits per minute.
How does LlamaIndex compare to LangChain?
Both pair an open-source framework with a commercial platform, but they optimize for different things. LangChain's LangSmith focuses on agent tracing, evaluation, and deployment, billed per trace from $39/seat/month. LlamaIndex's LlamaCloud focuses on document parsing, extraction, and indexing, billed per credit. Teams building document-heavy RAG often reach for LlamaIndex; teams needing agent observability reach for LangSmith.
Can LlamaIndex be self-hosted?
The open-source framework and LiteParse run entirely locally. The commercial LlamaCloud services are hosted, though the Enterprise tier adds SaaS or hybrid cloud deployment options for teams with data-residency or security requirements.
Is LlamaIndex still actively maintained?
Yes. The framework had a release in June 2026 across roughly 495 total releases, and the company remains independent after a $19M Series A led by Norwest Venture Partners, plus strategic investments from Databricks and KPMG.