Research-only reranking search results models
2 in the catalogue today, and the list grows as the market does. Every one with what it costs, who sells it and where it stands.
Models that take a handful of results a search already found and put them in the right order. They are the cheap second stage of retrieval: an embedding search casts a wide net fast, a reranker reads the candidates properly. Because they only ever see a few documents, they cost little per query, and they usually improve a weak search more than a better embedding model would.
Weights published for research and explicitly not for selling. They are here because they exist, are often excellent, and are worth knowing about — and because the cheapest way to learn this is not after you have shipped. If a model on this list is what you want, the maker will usually license it commercially on request; that is a conversation, not a download.