RAG economics

Calculate retrieval, embedding and generation costs together.

Model ingestion frequency, chunk overlap, retrieved context and monthly query volume in one transparent workflow.

RAG workload

Use an exact corpus token count for a billing-grade estimate.

End-to-end

Sample corpus text optional

Exact corpus tokens

Embedding model

Chunk size (tokens)

Chunk overlap (%)

Corpus refreshes / month

Queries / month

Retrieved chunks / query

Query tokens

System tokens

Output tokens / query

Generation model

Service tier

Pricing date

Costs not included by default

Vector database storage and query operations.
Reranking APIs, OCR, parsing and document extraction.
Metadata filters, network egress and observability.
Re-embedding caused by model migration.

Most common optimization

Reduce retrieved context only after measuring answer quality. Smaller chunks do not automatically mean lower total cost: overlap can materially increase ingestion tokens.