Mastering RAG Chunking: Balancing Semantic Precision Against Cost Optimization

As RAG becomes essential infrastructure for modern LLM applications, chunking strategy directly determines both retrieval quality and operational cost. This analysis exposes critical trade-offs: sliding window approaches preserve semantic context and boost relevance but dramatically increase token consumption, while token-based methods optimize costs at the risk of losing context diversity—with TOON emerging as a structural solution to resolve this fundamental tension.