datastores.ai

Embedding Cost Calculator

Estimate the cost of embedding and storing your documents in a vector database. Compare embedding models and database pricing side by side.

Embedding Cost
$1.30
One-time · 65.0M tokens
Storage Cost
$0.27/mo
0.59 GB · 1536d vectors
Est. Monthly Total
$0.37
Embedding amortized over 12 months + storage

Cost Breakdown

Documents100K
Tokens per document~650
Total tokens65.0M
Embedding dimensions1536
Storage required0.59 GB
Embedding cost (one-time)$1.30
Storage cost (monthly)$0.27/mo
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Frequently Asked Questions

How much does it cost to embed 1 million documents?

With OpenAI text-embedding-3-small ($0.02/1M tokens) and medium-length documents (~650 tokens each), embedding 1M documents costs approximately $13. Storage costs vary by database — Pinecone charges ~$0.45/GB/month while self-hosted options like Qdrant or pgvector are free.

Which embedding model is the most cost-effective?

For most use cases, OpenAI text-embedding-3-small offers the best balance of quality and cost at $0.02 per million tokens. For maximum savings, self-hosted open-source models (like sentence-transformers) are free but require GPU infrastructure.

How much storage do vector embeddings need?

Storage depends on dimensions and metadata. A 1536-dimensional vector (OpenAI small) uses ~6KB per document including metadata. 1 million documents require approximately 6GB of vector storage.