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RAG Pipeline Total Cost

Embed + Vector DB + LLM + Re-rank — all in one

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Learn more — how it works, FAQ & guide
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RAG Pipeline Total Cost Calculator

RAG (Retrieval Augmented Generation) cost = embeddings (one-time + delta) + vector storage + LLM call + optional re-rank. This calculator adds it all up so you see the real bill.

How to use this tool

  1. 1

    Size your corpus

    How many documents × avg tokens per doc?

  2. 2

    Set query workload

    Queries/month, top-K, optional re-ranker.

  3. 3

    See total stack cost

    Embeddings + vector DB + LLM + re-rank monthly.

Frequently Asked Questions

What does a vector DB really cost?
Pinecone serverless: ~$0.33/M vectors stored + $4/M queries. Weaviate Cloud: ~$25/month per 1M vectors. Chroma self-hosted: compute only. Costs blur at 100M+ vectors.
Do I need a re-ranker?
Cohere Rerank ($1/1K queries) boosts retrieval quality 20–40%. Worth it if your final-answer quality depends on top-3 chunks. Skip for casual chatbots.
Embedding model choice?
OpenAI text-embedding-3-small ($0.02/M tokens) is the default. Voyage and Cohere often beat it on domain text but cost 2–3×.

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