Embedding Similarity Calculator
Cosine, dot product and distance between two embedding vectors.
Vector A
Vector B
Similarity — Near duplicate — likely the same meaning.
About the Embedding Similarity Calculator
Paste two embeddings — raw arrays, comma separated numbers or a whole OpenAI embeddings response — and get cosine similarity, cosine distance, angle in degrees, dot product, Euclidean and Manhattan distance plus both vector norms, with a plain-English verdict on how related they are.
Examples
Two embeddings
[0.02, -0.11, 0.98] vs [0.01, -0.09, 0.97]Output
cosine 0.999 — near duplicateKeyboard shortcuts
- Copy the main outputCtrl / ⌘ + Shift + C
- Download the resultCtrl / ⌘ + S
- Share this toolCtrl / ⌘ + Shift + S
- Reset the inputsAlt + R
- Open the tool search paletteCtrl / ⌘ + K
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Frequently asked questions
Version 1.0.0 · Updated 2026-08-15 · Runs entirely in your browser