Benchmarked Graph-RAG vs. Graph-Free Multi-Hop RAG: The graph mostly bought us a massive rebuild bill, not accuracy.
We kept hitting the same wall building multi-hop RAG: the systems with the best accuracy (GraphRAG, HippoRAG 2, RAPTOR) all lean on a knowledge graph built offline - and that’s great numbers, until the moment your data changes! Every update means re-running an LLM indexing pass t
Why it matters
This story from Reddit r/LocalLLaMA is relevant to the Open Source branch of the AI ecosystem and may affect models, products, or research direction.
Technical breakdown
We kept hitting the same wall building multi-hop RAG: the systems with the best accuracy (GraphRAG, HippoRAG 2, RAPTOR) all lean on a knowledge graph built offline - and that’s great numbers, until the moment your data changes! Every update means re-running an LLM indexing pass to rebuild the graph. For a corpus that moves daily (prices, filings, tickets, news), you're paying that rebuild cost con
Business impact
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