Qwen3-Rerank - Qwen Cloud

Qwen-Rerank

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Overview

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A text-ranking model trained on the Qwen LLM foundation performs relevance ranking for input queries and candidate documents. It supports over 100 languages and long-text inputs, and is suitable for applications such as text retrieval and RAG. Its performance is aligned with the open-source Qwen3-Rerank series models.

Input

Text

Output

Text

Features

Prefix Completion

Function Calling

Cache

Structured Outputs

Batches

Web Search

Pricing

Text Input
$0.1Per 1M tokens

Context

32.76K

Max Input

32.76K

Max Output

Rate Limits

RPMRequests Per Minute
5.40K
TPMTokens Per Minute
5B

API Reference

Get API Key

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curl --location 'https://dashscope.aliyuncs.com/api/v1/services/rerank/text-rerank/text-rerank' \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header 'Content-Type: application/json' \
--data '{
    "model": "qwen3-rerank",
    "input":{
         "query": "What is a text rerank model",
         "documents": [
         "Text rerank models are widely used in search engines and recommendation systems. They sort candidate texts based on text relevance",
         "Quantum computing is a cutting-edge field in computer science",
         "The development of pre-trained language models has brought new progress to text rerank models"
         ]
    },
    "parameters": {
        "return_documents": true,
        "top_n": 5
    }
}'

curl --location 'https://dashscope.aliyuncs.com/api/v1/services/rerank/text-rerank/text-rerank' \
--header "Authorization: Bearer $DASHSCOPE_API_KEY" \
--header 'Content-Type: application/json' \
--data '{
    "model": "qwen3-rerank",
    "input":{
         "query": "What is a text rerank model",
         "documents": [
         "Text rerank models are widely used in search engines and recommendation systems. They sort candidate texts based on text relevance",
         "Quantum computing is a cutting-edge field in computer science",
         "The development of pre-trained language models has brought new progress to text rerank models"
         ]
    },
    "parameters": {
        "return_documents": true,
        "top_n": 5
    }
}'