Break RAG spend into corpus embedding, query embeds, and generation. Useful when retrieval volume dwarfs chat traffic and you need a monthly envelope before building.
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Estimate RAG spend
Set corpus size, chunking, and query rate to project monthly $.
A RAG cost estimator projects monthly spend for a retrieval-augmented generation stack: embedding the corpus, embedding queries, and generating answers from retrieved chunks. It uses token volume and list prices. It does not include vector-database hosting, and it does not call your live index.
Use it when retrieval volume may dwarf chat traffic and you need an envelope before you build. Pair with GPU TCO if you plan to self-host the generator.
Break RAG spend into corpus embedding, query embeds, and generation. Useful when retrieval volume dwarfs chat traffic and you need a monthly envelope before building.
Enter document count, tokens per document, chunk size, overlap, embedding model, top-K, query rate, and generation model. The calculator splits setup embed, optional re-embed, per-query embed, and generation. Export the totals for planning. No live vector DB is required.
Enter document count and average tokens per document.
Set chunk size, overlap, embedding model, and top-K.
Add query RPS and generation model.
Review setup vs monthly embedding and generation totals.
People budget generation and forget corpus embedding, query embedding, and re-embeds when docs change. Top-K also inflates generation input. This page makes those lines explicit so a “cheap” chat model can still be expensive behind retrieval.
No. The estimate is tokens times list prices. Hosting, replicas, and egress are separate. Toggle monthly re-embed only if the corpus actually refreshes. Self-hosted generation belongs on GPU / vLLM TCO, not in this token table.
A RAG cost estimator projects monthly spend for a retrieval-augmented generation stack: embedding the corpus, embedding queries, and generating answers from retrieved chunks. It uses token volume and list prices. It does not include vector-database hosting, and it does not call your live index.
Corpus embedding (setup and optional monthly re-embed), per-query embedding, and generation input/output from your top-K retrieval pattern.
No. The calculator models token volume and list prices only | infrastructure hosting is separate.
Project monthly embedding + retrieval + generation spend for a RAG stack.
Keep measuring in the same cluster — or jump to the next decision.
RAG Cost Estimator lives at omnikitapp.net/tools/rag-cost-estimator. Break RAG spend into corpus embedding, query embeds, and generation. Useful when retrieval volume dwarfs chat traffic and you need a monthly envelope before building. Use it as an operator page, then confirm invoices, policies, or published facts on the source. OmniKit does not sell detector evasion or ranking guarantees.
