qwen3-embedding-0.6b

Text Embeddings • Qwen • Hosted

The Qwen3 Embedding model series is the latest proprietary model of the Qwen family, specifically designed for text embedding and ranking tasks.

Model Info
Context Window ↗	8,192 tokens
Unit Pricing	$0.012 per M input tokens

Usage

export interface Env {
  AI: Ai;
}

export default {
  async fetch(request, env): Promise<Response> {

    // Can be a string or array of strings]
    const stories = [
      "This is a story about an orange cloud",
      "This is a story about a llama",
      "This is a story about a hugging emoji",
    ];

    const embeddings = await env.AI.run(
      "@cf/qwen/qwen3-embedding-0.6b",
      {
        text: stories,
      }
    );

    return Response.json(embeddings);
  },
} satisfies ExportedHandler<Env>;

import os
import requests


ACCOUNT_ID = "your-account-id"
AUTH_TOKEN = os.environ.get("CLOUDFLARE_AUTH_TOKEN")

stories = [
  'This is a story about an orange cloud',
  'This is a story about a llama',
  'This is a story about a hugging emoji'
]

response = requests.post(
  f"https://api.cloudflare.com/client/v4/accounts/{ACCOUNT_ID}/ai/run/@cf/qwen/qwen3-embedding-0.6b",
  headers={"Authorization": f"Bearer {AUTH_TOKEN}"},
  json={"text": stories}
)

print(response.json())

curl https://api.cloudflare.com/client/v4/accounts/$CLOUDFLARE_ACCOUNT_ID/ai/run/@cf/qwen/qwen3-embedding-0.6b  \
  -X POST  \
  -H "Authorization: Bearer $CLOUDFLARE_API_TOKEN"  \
  -d '{ "text": ["This is a story about an orange cloud", "This is a story about a llama", "This is a story about a hugging emoji"] }'

Parameters

Input
Output

▶queries

one of

instruction

stringdefault: Given a web search query, retrieve relevant passages that answer the queryOptional instruction for the task

▶documents

one of

▶text

one of

▶data[]

array

▶shape[]

array

API Schemas (Raw)

Input

Output