Complete pricing guide for LightRAG. Compare all plans, analyze costs, and find the perfect tier for your needs.
Not sure if free is enough? See our Free vs Paid comparison →
Still deciding? Read our full verdict on whether LightRAG is worth it →
forever
Developers and teams who want graph-enhanced RAG without licensing costs
Pricing sourced from LightRAG · Last verified March 2026
LightRAG is significantly lighter and cheaper to run. GraphRAG builds more comprehensive community summaries and handles global queries better, but costs 5-10x in indexing tokens. LightRAG is ideal when you want graph-enhanced retrieval without the heavy infrastructure and cost overhead.
Yes. LightRAG supports Ollama and other local LLM providers for both entity extraction during indexing and query-time processing. This means you can run the entire pipeline on-premise with zero API costs.
Higher than plain vector RAG because entity extraction requires LLM calls during indexing. Typically 2-3x the token count of source material for LightRAG vs near-zero LLM cost for basic vector RAG. With local models via Ollama, the monetary cost is essentially zero.
Yes. New documents can be added without re-indexing the entire collection. The knowledge graph is updated incrementally with new entities and relationships, though periodic full re-indexing can improve graph quality over time.
LightRAG supports Neo4j for production graph storage, NetworkX for lightweight in-memory graphs, OpenSearch as a unified backend for all four storage types (added in March 2026), and built-in lightweight stores for quick prototyping.
AI builders and operators use LightRAG to streamline their workflow.
Try LightRAG Now →Microsoft's graph-based retrieval augmented generation for complex document understanding and multi-hop reasoning.
Compare Pricing →LlamaIndex: Build and optimize RAG pipelines with advanced indexing and agent retrieval for LLM applications.
Compare Pricing →The industry-standard framework for building production-ready LLM applications with comprehensive tool integration, agent orchestration, and enterprise observability through LangSmith.
Compare Pricing →Open-source framework that builds knowledge graphs from your data so AI systems can analyze and reason over connected information rather than isolated text chunks.
Compare Pricing →