What are Matryoshka embeddings?

Matryoshka embeddings are trained so that prefixes of the full embedding vector are themselves usable as lower-dimensional embeddings. For example, the first 256 dimensions of a 1536-dimensional Matryoshka embedding are still meaningful, allowing applications to choose dimensionality at query time. This enables flexible tradeoffs between accuracy, storage, and latency without retraining.