What is Chunking?
Verified 5 August 2026
Embedding models have input limits, and retrieving a whole document when one paragraph is relevant wastes context. Chunking splits documents into retrievable units — the trade being that too-small chunks lose context and too-large ones dilute the embedding.
Chunking on structural boundaries — sections, paragraphs — generally beats fixed token counts, because it respects the document's own units of meaning.
Common questions
What is Chunking?
Chunking splits documents into passages small enough to embed and retrieve independently.
How does Chunking work in practice?
Chunking on structural boundaries — sections, paragraphs — generally beats fixed token counts, because it respects the document's own units of meaning.
See it working
The free tier is 10,000 requests a month with no card — enough to test any of this against your own queries.