@N01ennn: Microsoft ran its graph system against vector RAG on 8k, 120k, and a full million token context window, and the million…

X AI KOLs Timeline 08/02/26, 08:46 PM Tools

microsoft-research lazygraphrag rag graph-rag benchmark long-context open-source

Summary

Microsoft Research's LazyGraphRAG outperformed vector RAG on data-local questions across 8k, 120k, and million-token contexts, winning 92/90/91% at a tenth of the cost, and is now open-sourced on GitHub.

Microsoft ran its graph system against vector RAG on 8k, 120k, and a full million token context window, and the million token giant lost Jonathan Larson from Microsoft Research put up the numbers → LazyGraphRAG won 92, 90, and 91 percent of data-local questions, the exact place plain RAG was supposed to be strong → and did it at a tenth of the cost of the million token run the lesson buried in the benchmark → a bigger context window is not memory, structured memory is throwing more tokens at the problem was just the expensive way to be wrong open source on GitHub, the lesson a $1500 course would charge you for

Original Article

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Cached at: 08/03/26, 01:43 PM

Microsoft ran its graph system against vector RAG on 8k, 120k, and a full million token context window, and the million token giant lost

Jonathan Larson from Microsoft Research put up the numbers → LazyGraphRAG won 92, 90, and 91 percent of data-local questions, the exact place plain RAG was supposed to be strong → and did it at a tenth of the cost of the million token run

the lesson buried in the benchmark → a bigger context window is not memory, structured memory is

throwing more tokens at the problem was just the expensive way to be wrong

open source on GitHub, the lesson a $1500 course would charge you for

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