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Building a RAG Chunking Benchmark With Realistic Queries

This story is from 2026-10-19. It is preserved in the archive; the latest stories are on the live feed.

Retrieval-augmented generation (RAG) systems depend on retrieving the right information before generating an answer. However, even a capable embedding model and a well-configured vector database can produce poor results when documents are divided into unsuitable chunks. Small chunks may lose contex…

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  1. 2026-10-19 15:11 · DEV Community — AI
    Building a RAG Chunking Benchmark With Realistic Queries

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