Cosine Similarity Calculator

Compute cosine similarity between two vectors. Accepts raw JSON arrays (the format every embedding API returns) or comma-separated values. Returns the similarity score (-1 to 1; usually 0 to 1 for normalized embeddings) plus the dot product, magnitudes, and angle in degrees.

How to use the Cosine Similarity Calculator

Paste two vectors of equal length. Accepted formats: JSON array ([0.1, 0.2, ...]), comma-separated (0.1, 0.2, ...), or newline-separated. Most embedding APIs return normalized vectors where cosine similarity ranges 0-1; raw vectors range -1 to 1.

Interpretation

Cosine similarity measures the angle between two vectors, ignoring magnitude. For embeddings: 1.0 = identical meaning; ~0.8-0.95 = closely related; ~0.5-0.8 = topically related; near 0 = unrelated; negative = semantically opposite (rare with normalized embeddings).

Practical cutoffs are model-specific. For OpenAI text-embedding-3-small, ~0.85+ usually means "about the same topic." For Voyage models, the same threshold is closer to 0.75 because their distributions differ. Calibrate on your data.