About the Embedding Cost Calculator
Embedding a large document corpus for RAG has two cost components people underestimate: the one-time embed pass over the full corpus, and the recurring cost of re-embedding as documents change. This calculator projects both, plus the raw vector storage footprint your chosen model's dimensionality implies — before you commit to a vector database sizing decision.
Key Features
- Covers OpenAI text-embedding-3, ada-002, Gemini, Cohere embed-v3, and Voyage-2.
- One-time embed cost, monthly re-embed cost, and raw vector storage size (float32).
- Pairs well with the Connection Pool Sizer and other Architecture Suite tools when planning a RAG pipeline.