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RAG Chunking Strategies: Semantic Chunking, Overlapping, Recursive Splitting

Introduction

Document chunking is the foundation of any RAG system. How you split documents into chunks directly determines retrieval quality: chunks that are too small lose context, chunks that are too large dilute relevance, and naive splits break semantic units mid-thought. This article covers the major chunking strategies and when to use each.

Naive Fixed-Size Chunking

The simplest approach splits text every N characters or tokens:

def fixed_size_chunks(text: str, chunk_size: int = 512, overlap: int = 64) -> list[str]:

chunks = []

start = 0

while start < len(text):

end = start + chunk_size

chunk = text[start:end]

chunks.append(chunk)

start = end - overlap

return chunks

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Fixed-size chunking is fast and predictable.…