LlamaIndex vs PrivateGPT

A side-by-side look at pricing, capabilities, pros, cons, and our editorial scores.

	LlamaIndex RAG	PrivateGPT RAG
Tagline	Data framework for connecting LLMs to your data.	Production-ready, air-gapped RAG framework for querying your documents with local LLMs.
Category	RAG	RAG
Pricing	Freemium· Free open-source; LlamaCloud paid	Freemium· OSS free; Zylon enterprise contract (contact sales)
Model	BYO (Claude / GPT / open)	Multi-model (BYO local LLM)
Editorial score	8.7 / 10	—
Use cases	RAGdata ingestionindexing	private-ragchat-with-documentson-premises-llmair-gapped-aienterprise-knowledge-base
Pros	Focused on retrieval (not general agent stuff) Many ingestion connectors Strong production patterns LlamaCloud for managed ingestion	Fully local and air-gapped; data never leaves your infrastructure OpenAI-compatible API makes integration straightforward Massive OSS community (57k+ stars) with proven deployments Model-agnostic across llama.cpp, Ollama, vLLM, and Qdrant
Cons	API surface is large Documentation can be hard to navigate	No public pricing for the enterprise Zylon platform OSS repo cadence has slowed since the commercial pivot Operating at scale still requires meaningful DevOps effort
Website	www.llamaindex.ai	www.zylon.ai

Pick LlamaIndex if

Pick PrivateGPT if