Embedding Drift

Embedding drift occurs when the embedding model used to encode new documents or queries changes — either through model updates or model replacement — while older vectors in the index were produced by a different model version. Because the two model versions map content to different regions of vector space, mixed-model indexes produce degraded retrieval accuracy. Preventing embedding drift requires versioning the embedding model, storing the model identifier alongside each vector, and re-embedding the entire corpus whenever the model changes.