Embedding storage & query calculator
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About Embedding storage & query calculator
Vector retrieval stacks have two different wallets: object storage or disk for the embedding matrix, and embedding API meters for ingest and query-time encoding. This page estimates raw float32 footprint (with a crude index overhead multiplier) and applies a single user-supplied dollars-per-million-tokens price to both ingest and query traffic using a very approximate "tokens ≈ vectors × dimensions / 4" heuristic. It will not match any vendor’s tokenizer; it exists so teams remember both CapEx-style storage and OpEx-style embedding calls.
Key Features
- Vector count and dimensionality
- Query volume per month
- User-editable $/M token price
- GB estimate with index overhead knob
Use Cases
- RAG cost narratives for architecture reviews
- Back-of-envelope before Pinecone/Vertex bills arrive
Pro Tips
- Add disk $/GB from your cloud console separately — we don’t guess provider storage tariffs.
Frequently Asked Questions
Why dims/4 for tokens?
It is a coarse English-text heuristic; replace with logged token counts when you have them.