Model Marketplace

Qwen-Rerank

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Overview

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

Enable Partial Mode when calling the Qwen API to make the model continue strictly from your provided prefix text.View docs

Function Calling

Use function calling to connect large language models with external tools and systems.View docs

Cache

Context Cache stores shared prefixes for long-context requests to reduce repeated computation, improve latency, and lower cost.View docs

Structured Outputs

Structured Outputs help ensure the model returns a JSON string in the expected format.View docs

Batches

Asynchronously process requests in batches to reduce costs.View docs

Web Search

Enable web search so the model can answer with real-time retrieved data.View docs

Fine-tuning

Train models on sample data to better adapt them to specific tasks.View docs

Pricing

  • Text Input
    $0.1Per 1M tokens

Rate Limits & Context

  • Max Input
    32K
  • Context
    32K
  • TPMTokens Per Minute
    5B
  • RPMRequests Per Minute
    5K

API Reference

Call API
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curl --location 'https://dashscope-intl.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",
    "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"
    ],
    "top_n": 5,
    "return_documents": true
}'