Embedding Dimension Calculator (Storage + Memory)

Type the embedding dimension and number of documents — get the disk footprint, RAM cost, and approximate vector DB cost for storing the index. Compare costs across float32 (full precision), float16 (half), int8 (quantized), and binary (1-bit) — common quantization options that trade recall for size.

How to use the Embedding Dimension Calculator (Storage + Memory)

Pick the embedding dimension matching your model (or enter custom). Set the document count. The calculator shows raw float32 storage, then the savings from float16, int8, and binary quantization. Useful when sizing a vector DB cluster or estimating monthly cloud cost for an embedding index.