ModelRefs / Text Splitter — AI Glossary
Text Splitter — AI Glossary
A utility dividing long documents into chunks of appropriate size for embedding and retrieval, respecting semantic boundaries.
Overview
Text splitters: recursive character splitting (default), sentence-boundary splitting (NLTK, spaCy), semantic chunking (embed sentences, split at similarity drops), HTML/markdown-aware splitting (preserves structure), token-based splitting (respects model tokenizer limits). Chunk size (256–2048 tokens) and overlap are the primary parameters.
Reference details
| Topic | rag |
|---|---|
| Also known as | chunker, text chunker |
| Last reviewed | 2026-06-24 |
Related terms
Commonly confused with
The component that performs chunking, and the place the strategy actually lives: fixed-size, recursive by separator, or semantic. That distinction matters when debugging, because "our chunking is wrong" is usually a statement about which splitter is configured and with what separators, not about the chunk size everyone reaches for first.
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Frequently asked questions
What is Text Splitter?
A utility dividing long documents into chunks of appropriate size for embedding and retrieval, respecting semantic boundaries.
Is Text Splitter the same as chunker?
Yes — chunker, text chunker are common aliases for Text Splitter.
What concepts are related to Text Splitter?
Closely related concepts include chunk overlap, document loader, indexing pipeline.