Alibaba (Qwen) / qwen3-rerank

Qwen3 Rerank

Qwen3 Rerank reranks search candidates by relevance, improving retrieval quality for RAG and search.

Search & rerank

Context

tokens

Input

$0.120

/ search

Output

$0.036

/ search

Quality

#77

Elo 1150

Overview

What this model is good for

Qwen3 Rerank reranks search candidates by relevance, improving retrieval quality for RAG and search.

Model capabilities

Streaming

Supports streamed responses for chat, assistants, and interfaces that need visible incremental output.

Model maker

Model maker and access

This section shows the model maker, SeaLink model ID, protocol, and pricing information.

Alibaba (Qwen)

Called through SeaLink's unified account, balance, and OpenAI-compatible API.

Protocol

OpenAI-compatible Chat Completions

Base URL: https://test.sealink.io/v1

Pricing

Pricing and cost sense

Prices come from the current model catalog. Simple estimates help users judge whether the model fits production volume.

Input$0.120/ search

Output$0.036/ search

Actual billing follows usage logs and billing records; caching and media pricing depend on the endpoint.

API

Copy into your code

The model page should make it clear which model to copy, which base URL to use, and where to get an API Key.

model

qwen3-rerank

base_url

https://test.sealink.io/v1

Auth

Bearer $SEALINK_API_KEY

cURL

curl https://test.sealink.io/v1/rerank \
  -H "Authorization: Bearer $SEALINK_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen3-rerank",
    "query": "What is the capital of France?",
    "documents": [
      "Paris is the capital of France.",
      "London is the capital of the UK."
    ]
  }'

Python (OpenAI SDK)

import requests

url = "https://test.sealink.io/v1/rerank"
headers = {"Authorization": f"Bearer {api_key}"}
payload = {
    "model": "qwen3-rerank",
    "query": "What is the capital of France?",
    "documents": [
        "Paris is the capital of France.",
        "London is the capital of the UK.",
    ],
}
resp = requests.post(url, json=payload, headers=headers)
data = resp.json()
for r in data["results"]:
    print(f"score={r['relevance_score']} doc={r['document']['text']}")

Node.js (OpenAI SDK)

const resp = await fetch("https://test.sealink.io/v1/rerank", {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${process.env.SEALINK_API_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    model: "qwen3-rerank",
    query: "What is the capital of France?",
    documents: [
      "Paris is the capital of France.",
      "London is the capital of the UK.",
    ],
  }),
});
const data = await resp.json();
data.results.forEach(r => console.log(`score=${r.relevance_score} doc=${r.document.text}`));