What is the best chunk size for RAG Q&A?

For Q&A, chunk sizes between 256 and 512 tokens are recommended to balance precision and context.

How does overlap affect retrieval relevance?

Overlap (0-50%) preserves context across chunks, improving relevance scores by up to 15% in simulated evaluations.

Which embedding model is most cost-effective?

text-embedding-3-small (1536d) offers a good balance of dimension and cost; ada-002 is similar but slightly more expensive per token.

RAG Chunk Size Optimizer — Find the Best Chunk Size for Your Data

📄 Document & Model

Paste sample text or enter average document length (tokens) Embedding model

Total document count

Avg tokens/doc

Chunk size (tokens): 512

512

Overlap (%): 20%

20%

📊 Estimated Outputs

Total chunks—

Embedding cost (USD)—

Storage size (MB)—

Avg. retrieval relevance (sim.)—

⚡ Recommended chunk sizes

Q&A 256–512

Summarization 1000–2000

Code 500–1000

📎 Chunk preview (first ~3 chunks)

Adjust parameters to see preview…

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