Cost / Search
$0.009958
RAG Search Cost Calculator
Budget planner for CMO and CTO teams to estimate AI search costs per query and per month.
Knowledge Base and Indexing
Search Traffic and Runtime
Derived queries/day: 10,000
Infrastructure Unit Economics
Budget Output
Cost / 1K Searches
$9.96
Monthly Total
$2,987.54
Yearly Budget
$35,850.48
| Cost Component | Monthly Cost |
|---|---|
| Amortized Index Embedding | $0.2000 |
| Query Embedding | $0.1800 |
| LLM Input Tokens | $55.08 |
| LLM Output Tokens | $25.92 |
| Vector Search | $24.00 |
| Vector Storage | $2.16 |
| Reranking | $2,880.00 |
Corpus tokens: 60,000,000 | Estimated vectors: 120,000 | Monthly queries: 300,000 | LLM-served queries: 240,000
Scenario Comparison (Low / Base / High)
| Scenario | Queries / Day | Monthly Budget | Yearly Budget | Cost / Search |
|---|---|---|---|---|
| Low | 7,000 | $2,091.99 | $25,103.83 | $0.009962 |
| Base | 10,000 | $2,987.54 | $35,850.48 | $0.009958 |
| High | 15,000 | $4,480.13 | $53,761.56 | $0.009956 |
RAG Budget Planning Guide
This calculator helps leadership teams estimate AI search ROI and allocate budget between model usage and infrastructure. For CMO planning, translate search volume growth into projected monthly AI spend. For CTO planning, benchmark architecture choices like chunk size, cache strategy, and reranking depth.
How To Use For Quarterly Planning
- Model current traffic as baseline and create conservative and aggressive growth scenarios.
- Adjust cache hit rate and retrieved chunks to test optimization impact.
- Evaluate cost-per-search targets against conversion or retention goals.
- Use yearly output to prepare procurement and team budget approvals.