Your Knowledge Graph Is Wasting 70% of Its Tokens
Article summary
Quick briefing — cleaned from the original RSS feed
Everyone building GraphRAG tunes the same three dials: the retriever, the chunk size, the re-ranker. Then the retrieved subgraph gets serialized into the prompt with json.dumps() — and nobody measures what that step costs. I did. It costs more than everything else you tuned. The benchmark I compared 10 graph serialization formats — JSON, GraphML, RDF variants, edge lists, and others — on three axes: Token count for the same property graph Traversal QA accuracy (can the model correctly walk the…
1Key Takeaways
- Everyone building GraphRAG tunes the same three dials: the retriever, the chunk size, the re-ranker.
- Then the retrieved subgraph gets serialized into the prompt with json.dumps() — and nobody measures what that step costs.
- It costs more than everything else you tuned.
- The benchmark I compared 10 graph serialization formats — JSON, GraphML, RDF variants, edge lists, and others — on three axes: Token count for the same property graph Traversal QA accuracy (can the model correctly walk the….
2AIWedia Score
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — AI reports that everyone building GraphRAG tunes the same three dials: the retriever, the chunk size, the re-ranker.
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