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Chunking Strategies

Text chunking strategies for RAG: fixed-size, semantic, recursive, and document-aware chunking with performance comparisons.

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Chunking Strategies

Chunking decides what your retriever can even find. Bad chunking is a good retriever searching a broken haystack — and there is no universal best strategy, only the right fit for your docs, queries, and embedding model.

THE CENTRAL IDEA

An embedding can only represent what lands inside one chunk. If the sentence that answers the question is split across a chunk boundary, neither half retrieves well — the answer becomes invisible to search. Chunking is therefore the highest-leverage knob in ingestion: get the boundaries right and mediocre retrieval suddenly works.

Chunking determines what your retriever can find. Bad chunking = good retriever searching in a broken haystack. There is no universal best strategy — it depends on your documents, queries, and embedding model.

Chunking Strategy Comparison

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