Use Case

RAG Pipeline Cost Guide: Full Retrieval-Augmented Generation Cost Breakdown

The full cost of a RAG pipeline includes indexing, embedding, vector search, retrieval context, and generation. CostMyAI breaks down every component so you can forecast the real infrastructure cost before you build.

RAG cost components

  • Document indexing: one-time cost to embed your corpus. 50K docs with text-embedding-3-small: ~$128
  • Query embedding: each user query is embedded before retrieval. ~$0.00002 per query
  • Retrieval context: top-5 chunks (2,560 tokens) injected into every LLM request
  • Generation: the completion cost, with retrieval context as part of the input token count
  • Chunking strategy: smaller chunks reduce per-query context cost but may reduce answer quality
Calculate my RAG pipeline costs