A focused specialist that takes two pieces of text and returns a relevance score rather than generated content. It operates as a cross-encoder, meaning it reads both query and passage together before scoring — a slower but more precise approach than embedding-based retrieval. Its Russian-language focus and MS MbenchmarksO training make it oriented toward search and ranking tasks in that language.