RAG Vector Database Cost Calculator for Production AI Search
At meaningful query volume, embedding and vector DB cost routinely exceed LLM inference. Model it before you commit to a vendor β or watch re-embedding quietly dominate your bill.
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At meaningful query volume, embedding and vector DB cost routinely exceed LLM inference. Model it before you commit to a vendor β or watch re-embedding quietly dominate your bill.
GPU self-hosting wins on dollars-per-token at scale, but the break-even is almost always 5-20x higher than teams estimate β because they forget power, utilization, ops headcount, and quantization quality loss.
LLM inference cost is a non-linear function of token composition, model mix, and cache behavior β and almost no team models it before shipping. Plan it before the invoice arrives.