Equation 25 · Naive, Graph, and Agentic: A Systems Comparison of RAG Architectures
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is also the family’s most visible weakness, and the project’s own subsequent work treats it as one worth solving rather than downplaying, which is worth reading as a vendor’s own admission of the problem’s severity. Microsoft’s follow-up post introducing LazyGraphRAG reports — as a vendor claim about the vendor’s own systems, not an independently audited benchmark — that the original approach’s indexing cost was steep enough to motivate a redesign, and states that LazyGraphRAG’s indexing cost is on par with plain vector-based RAG and roughly one part in a thousand of full GraphRAG’s, while its global-search query cost is reported as roughly seven hundred times lower than the…
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is also the family’s most visible weakness, and the project’s own subsequent work treats it as one worth solving rather than downplaying, which is worth reading as a vendor’s own admission of the problem’s severity. Microsoft’s follow-up post introducing LazyGraphRAG reports — as a vendor claim about the vendor’s own systems, not an independently audited benchmark — that the original approach’s indexing cost was steep enough to motivate a redesign, and states that LazyGraphRAG’s indexing cost is on par with plain vector-based RAG and roughly one part in a thousand of full GraphRAG’s, while its global-search query cost is reported as roughly seven hundred times lower than the original for comparable answer quality, or about four percent of the original’s query cost at a stated evaluation budget [ 6 ] . Read alongside the amortised-cost model above, this is a description of the same term being pushed down by engineering rather than by amortisation, which is a different lever entirely and one the other four families do not have available in the same form, since none of them pays a comparable fixed cost to begin with.
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