MUVERA: Two-Tier Retrieval (Cheap FDE Recall, Exact Rerank)

MUVERA serves multi-vector quality at single-vector speed by splitting retrieval into two tiers. Tier 1 is cheap and runs over all N documents: the query is FDE-encoded to one fixed vector and a standard single-vector ANN index (HNSW, IVF, or DiskANN) returns a top-K candidate set (K around 100–500) in milliseconds — each document is just one vector here. Tier 2 is expensive but only ever sees those K candidates: it reranks them with exact Chamfer / MaxSim over the ORIGINAL token vectors, producing the final ranking. The tradeoff most vendor posts gloss over is storage: you keep BOTH representations — the FDE vectors in the ANN index (one per document, serving tier 1) and the full ~100 token vectors per document on disk (served only for the K rerank candidates). Drop the second copy and you cannot rerank; keep it and your storage roughly doubles. Recall quality is bought with disk, not magic.