What is the total cost per RAG query?

Typical RAG query: embed query ($0.000002) + vector search ($0.000005) + LLM with 2K context ($0.04-0.08 for GPT-4) = $0.04-0.08 total. The LLM dominates RAG costs, not retrieval.

How can I reduce RAG costs without losing quality?

Reduce LLM costs by: trimming retrieved context to 3-5 chunks, using GPT-3.5/Claude Haiku for simple queries, caching answers for common questions, and using semantic caching.

Is RAG cheaper than fine-tuning for domain-specific AI?

RAG is almost always cheaper for knowledge-intensive tasks: no training cost, easy to update, and requires no GPU infrastructure. Fine-tuning is better for style/format consistency at scale.

RAG Pipeline Cost Per Query Calculator

Calculate the total end-to-end cost of a RAG (Retrieval-Augmented Generation) pipeline per query, including embedding, retrieval, context building, and LLM generation.

AI & SaaS Tools

SaaS Metrics

AI Compute

AI ROI

LTV:CAC Ratio

ARPU ($/month)

Monthly Churn %

CAC ($)

Gross Margin %

LTV

$3500

LTV:CAC

11.67

Payback

2.9 mo

Health

Healthy ✓

Benchmark: LTV:CAC ≥ 3 is healthy. Payback under 12 months is excellent. Under 1 means you lose money on each customer.

How to Use

Enter the values for the scenario you are assessing. Calculate the total end-to-end cost of a RAG (Retrieval-Augmented Generation) pipeline per query, including embedding, retrieval, context building, and LLM generation. Use the rag pipeline cost result to inform your calculation.

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AI & Tech

Embedding Cost

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GPT-4 Cost

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RAG Pipeline Cost Per Query Calculator

LTV:CAC Ratio

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Frequently Asked Questions

What is the total cost per RAG query?

How can I reduce RAG costs without losing quality?

Is RAG cheaper than fine-tuning for domain-specific AI?