Updated · Methodology: named formula library
RAG Retrieval Cost
Cost per RAG query: embedding + vector lookup + LLM completion.
100,000 queries × $0/querie = $1,200.
RAG Cost
Per query: embed query (~$0.0001), retrieve from vector DB (~$0.001), pass top-k results + question to LLM (~$0.01–$0.05 depending on model). Total: $0.012–$0.06 per query.
Worked Example
100000 queries at 0.012/querie
- usage
- 100000
- rate
- 0.012
- Result
- $1,200
100000 × 0.012 = $1,200.
When to Use This Calculator
- Budget production RAG systems
Limitations & Common Mistakes
- Results are estimates based on the inputs you provide.
- Always verify with current data and consult a professional for major decisions.
Frequently Asked Questions
How is RAG Retrieval Cost cost calculated?
Cost = queries × rate per querie. The default rate ($0.012/querie) reflects current U.S. average pricing. Replace with your actual contracted rate for an exact number.
What's the average querie cost?
The default of $0.012 per querie is the U.S. average as of 2026. Regional variation is significant — urban areas are typically 20–40% higher than rural; coastal states 10–25% higher than the Midwest.
How can I reduce this cost?
For utility bills: efficiency upgrades, off-peak usage, conservation. For SaaS/cloud: rightsize tier, audit for unused services, negotiate annual commitments for 15–25% off list price. For LLM API: prompt caching (90% off cached input), batch API (50% off async jobs), smaller models for simpler tasks.
Does this include taxes and fees?
No. Bills typically include 5–15% in taxes, surcharges, and regulatory fees on top of the metered rate. To get total cost from this estimate, multiply the result by 1.10 as a rough placeholder, or check your actual bill for itemized fees.
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