Embedding Storage

Estimate raw and indexed storage for an AI embedding collection.

How this calculator works

Enter number of vectors, dimensions per vector, bytes per component, index and metadata overhead (%). Select Calculate to apply the displayed formula and review the labeled results.

Formula / method

Storage = vectors × dimensions × bytes per component × (1 + overhead ÷ 100)

Worked example

One million 1,536-dimensional float32 vectors use 6.144 GB raw and about 7.99 GB with 30% overhead.

Assumptions and limitations

All vectors have equal dimensions and use the selected fixed-width representation.

Vector databases vary widely in index structure, compression, replicas, metadata, alignment and temporary build space.