Chunking Strategies for RAG

In RAG systems, documents are rarely embedded as one giant block. They are split into smaller pieces called chunks, and the quality of those chunks has a major effect on retrieval accuracy.

Why Chunking Matters

If chunks are too small, they lose context. If they are too large, retrieval becomes noisy and expensive. Good chunking balances specificity with enough surrounding detail to make the information usable.

Common Approaches

• Fixed-size chunking: simple and fast, but can split ideas awkwardly.
• Sentence or paragraph chunking: preserves meaning better.
• Semantic chunking: groups text by topic shifts rather than character count.
• Hierarchical chunking: retrieves both local passages and broader sections.

Practical Advice

There is no universal chunk size. The best strategy depends on the document type, retriever, and questions users ask. In practice, chunking is one of the highest-leverage parts of RAG tuning.