Graph-Based Retrieval Slashes Tokens While Outpacing Traditional RAG

This benchmark demonstrates that GraphRAG—which structures knowledge as an explicit graph of relationships—uses significantly fewer tokens and costs less than traditional vector-based RAG while delivering higher-quality answers. For organizations deploying LLMs at scale, where token consumption directly impacts operational costs, GraphRAG's ability to model multi-document relationships offers a practical path to both superior performance and reduced expenses.