A focused retrieval specialist trained specifically on question-answer pairs, making it particularly attuned to matching queries with relevant passages. It uses dot-product similarity rather than cosine similarity, so vector magnitudes carry meaning — a subtle but important behavioral difference when building search systems. Compact and efficient, it trades raw language breadth for strong semantic alignment between questions and their answers.