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qwen3-rerank
Activeqwen/qwen3-rerank
基于Qwen LLM底座训练的文本排序模型，对输入的Query和候选Docs进行相关性排序，支持100+语种和长文本输入，适用于文本检索、RAG等场景，效果对齐开源Qwen3-Rerank系列模型
RerankQwen
Pricing
Pay as you go · priced in CNYPay as you go · priced in CNYPer query
Text input
¥0.700
/ 1M tokens
Image tokens
¥0.700
/ 1M tokens
Context length
30K
tokens
Rerank models are billed separately for text input and image tokens, in CNY per million tokens.
Providers and quotes
1 routes · pay as you go| Provider | Text input | Context length | Latency | Uptime | Status |
|---|---|---|---|---|---|
 dashscope dashscope/qwen3-rerank | ¥0.500 | 30K | — | 0.00% |
API examples
OpenAI compatibleEndpoint/rerankmodel: qwen/qwen3-rerank
python
import os
import requests
response = requests.post(
"https://api.openroute.cn/v1/rerank",
headers={
"Authorization": f"Bearer {os.environ['ONTOROUTE_API_KEY']}",
"Content-Type": "application/json",
},
json={
"model": "qwen/qwen3-rerank",
"query": "What is the capital of France?",
"documents": [
"Paris is the capital of France.",
"London is the capital of England.",
"Berlin is a city in Germany.",
],
"top_n": 2,
},
)
response.raise_for_status()
print(response.json())OpenRoute provides a Rerank API to score candidate documents by relevance to a query.
Request parameters
Calls (30d)
0
1 supply routes
Avg. latency
—
Time to first token
Usage trend
暂无调用数据