Vector Database Storage & RAM Calculator
Find out how much disk, RAM, and monthly money your embeddings will cost to store and serve. Enter a vector count, model, and precision to see raw size, HNSW overhead, total RAM, and an estimated Pinecone, Qdrant, Weaviate, or self-hosted bill — no signup.
How it works
Vector search costs are mostly storage costs, and storage is just byte arithmetic. Every embedding is an array of numbers; this tool multiplies that out and adds the overhead each index type carries. All sizes use binary units — 1 GiB = 2³⁰ = 1,073,741,824 bytes.
- Bytes per dimensionfollow the precision, from Qdrant's quantization guide: float32 = 4 bytes, float16 = 2, int8 = 1, and binary = 0.125 (one bit).
- Raw vector storage = num_vectors × dimensions × bytes_per_dim. A 1536-dim float32 vector is 6,144 bytes; a million of them is 5.72 GiB.
- Metadata = num_vectors × metadata_bytes_per_vector — the IDs, text snippets, and tags you store alongside each vector.
- Index overhead. A Flat (exact) index adds nothing. An HNSW graph adds roughly 0.5 ×the raw vector footprint for its links, which is where Qdrant's capacity rule of thumb — memory ≈ 1.5 × num_vectors × dim × 4 for float32 — comes from.
- Total RAM = raw + metadata + overhead (what the engine holds in memory to serve queries). Total disk = raw + metadata (the graph is rebuilt or memory-mapped as needed).
- Managed cost. Each provider bills differently: Pinecone Serverless charges per GB of stored data ($0.33/GB-month), Qdrant Cloud is sized by RAM, and Weaviate Serverless bills per stored dimension ($0.05 per million dimensions-month). The tool applies the right basis per provider and converts to LKR using the editable CBSL indicative rate.
The float32 + HNSW path is cross-checked against Qdrant's published 1.5 × n × d × 4 identity to the byte, the same way a tax tool reconciles against the official table. Managed prices are storage / RAM tier only and exclude query, read, and write units — stated plainly so the estimate is never oversold.
Worked examples
Frequently asked questions
Sources & references
- Qdrant — Capacity planning (the 1.5× RAM rule of thumb)
- Qdrant — Quantization (int8 and binary byte sizes)
- pgvector — README (HNSW memory, vector / halfvec / bit storage)
- OpenAI — Embeddings guide (model output dimensions)
- Pinecone — Pricing (serverless storage rate)
- Qdrant Cloud — Pricing (managed RAM tiers)
- Weaviate — Pricing (per-dimension serverless rate)
Dimension constants, byte sizes, and provider rates were last cross-checked against these sources on 2026-06-06. Provider pricing is reviewed quarterly and after any vendor pricing change.
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Comments & feedback
Spotted a bug or want an improvement? Tell us — our team reviews every comment, and good ideas get built. Comments are public and anonymous.
Found a bug, edge case, or want a provider added?
Email me at [email protected] — most fixes ship within 24 hours.