LlamaIndex
Data framework for connecting LLMs to private data with chunking, indexing, and retrieval primitives.
LlamaIndex is a data framework for connecting LLMs to private data with chunking, indexing, and retrieval primitives. Open-source framework that provides primitives for chunking, indexing, and retrieval to connect LLMs with private data.
About LlamaIndex
LlamaIndex is an open-source data framework that connects LLMs to private data using chunking, indexing, and retrieval primitives.
Through a unified interface it works with OpenAI GPT, Anthropic Claude, and Google Gemini, and it runs against local model runners such as Ollama for fully on-premise inference with no external API calls. It ships as Python and TypeScript SDKs plus a CLI (create-llama) for scaffolding new projects.
It is aimed at developers comfortable in Python or TypeScript, since it is a code framework rather than a no-code web interface. It runs on a bring-your-own-key model, so you supply and pay for your own LLM API credentials, and some managed features such as LlamaCloud parsing and ingestion are gated behind paid plans.
Rather than a finished app, it gives you retrieval building blocks to wire LLMs to your own data.
Sources: this listing
LlamaIndex pros and cons
Pros
- Open-source framework that provides primitives for chunking, indexing, and retrieval to connect LLMs with private data.
- Supports multiple LLM providers including OpenAI GPT, Anthropic Claude, and Google Gemini through a unified interface.
- Compatible with local model runners such as Ollama, allowing fully on-premise inference without external API calls.
- Available as Python and TypeScript SDKs and includes a CLI (create-llama) for scaffolding new projects.
Cons
- Operates on a BYOK (bring-your-own-key) model, so users must obtain and pay for their own LLM API credentials.
- Primarily a developer framework requiring Python or TypeScript proficiency rather than a no-code web interface.
- Some managed features such as LlamaCloud parsing and ingestion are gated behind paid plans.
Tagged
- Bring Your Own Key
- Supports Claude
- Supports GPT
- Supports Gemini
- Supports Local Models
- CLI
- Agentic Mode
- Freemium
- Open Source
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LlamaIndex pricing
Read off the vendor’s own pricing page on 2026-08-24.
| Plan | Price | Best for |
|---|---|---|
| Free | $0 / month | Evaluating the platform with low-volume parsing |
| Starter | $50 / month | Solo founders or small teams running steady parse workloads |
| Pro | $500 / month | Teams shipping agent pipelines that need priority Slack support and concurrency headroom |
| Enterprise | Custom | Organizations needing SSO, hybrid deployment, and dedicated support |
Full LlamaIndex pricing breakdown — limits, hidden costs, change log →
Related reading
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</a>Frequently asked questions
- What is LlamaIndex?
- LlamaIndex is a data framework for connecting LLMs to private data with chunking, indexing, and retrieval primitives.
- How much does LlamaIndex cost?
- LlamaIndex pricing, read from the vendor's page on 2026-08-24: Free — $0 / month; Starter — $50 / month; Pro — $500 / month; Enterprise — Custom.
- Is LlamaIndex free?
- Yes. LlamaIndex has a free plan (Free) — 10K credits included, 5 concurrent parse/extract/classify/split jobs, 1 concurrent sheets job, 5 indexes with 50 files each, 1 project, community support, file upload only. Verified against the vendor's pricing page on 2026-08-24.
- What platforms does LlamaIndex support?
- LlamaIndex runs on mac, win, linux, cli.
- What are the alternatives to LlamaIndex?
- Similar tools in AI Web Apps on vibedonalds: Zapier, Startup OG, speejax, Dottr.
- What are the downsides of LlamaIndex?
- Operates on a BYOK (bring-your-own-key) model, so users must obtain and pay for their own LLM API credentials. Primarily a developer framework requiring Python or TypeScript proficiency rather than a no-code web interface. Some managed features such as LlamaCloud parsing and ingestion are gated behind paid plans.