Skip to main content
Qwen3 Reranker 0.6B is Qwen’s open-weights reranking model. It reads a query and a document and returns the probability that the document is relevant. Use it to reorder the results of a keyword or embedding search before you show them or pass them to a language model. Prime Inference serves it on Prime infrastructure as a hosted model. The model scores each document in its own prompt, together with the query and an instruction. A request can rank up to 1,000 documents. See the model catalog or the Models API for current pricing and availability.

Use Prime Inference

The model doesn’t take Chat Completions requests. Create a Prime API key with Inference permission in the API keys guide, then call the Rerank API:
The response lists the documents most relevant first, each with its index in the request and a relevance_score from 0 to 1. To charge a team instead of your personal account, add -H "X-Prime-Team-ID: your-team-id". Keep API keys server-side.

Write an instruction

The model reads a one-line instruction with every document. The default, Given a web search query, retrieve relevant passages that answer the query, suits search. For a different task, set instruction in the same pattern, Given a <kind of query>, retrieve <kind of document> that <relation to the query>:
To change the rest of the prompt as well, format the prompts yourself and send them to the Classify API.