Comparison
Recursive Chunking vs Semantic Chunking
Recursive Chunking and Semantic Chunking are both common AI/LLM terms but cover different ideas. Here is a quick side-by-side.
When you would reach for Recursive Chunking
Recursive Chunking comes up when the question is fundamentally about agents & tools.
A 5000-character article: recursive splitter at 1000 chars with 100-char overlap → 6 chunks, each ending on a natural sentence boundary.
When you would reach for Semantic Chunking
When documents have variable topic density and recursive chunking is producing low-quality retrievals.
A meeting transcript: semantic chunker breaks on topic-change moments rather than arbitrary token windows.
Frequently asked
What is the difference between Recursive Chunking and Semantic Chunking?
Recursive Chunking: Recursive chunking splits text by trying progressively smaller separators — paragraphs, then sentences, then words — until each chunk fits the target size, preserving natural boundaries where possible. Semantic Chunking: Semantic chunking embeds each sentence and inserts a chunk boundary wherever consecutive embeddings diverge sharply — producing chunks that respect topic boundaries rather than character counts.
When should I use Recursive Chunking vs Semantic Chunking?
Recursive Chunking is the right concept when you are focused on agents & tools. When documents have variable topic density and recursive chunking is producing low-quality retrievals.
Are Recursive Chunking and Semantic Chunking the same thing?
No. Recursive Chunking is agents & tools; Semantic Chunking is agents & tools. They are related but address different parts of the AI stack.