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

{
  "type": "object",
  "properties": {
    "queries": {
      "oneOf": [
        {
          "type": "string",
          "description": "A single query string",
          "minLength": 1
        },
        {
          "type": "array",
          "description": "An array of query strings",
          "items": {
            "type": "string",
            "minLength": 1
          },
          "maxItems": 32
        }
      ]
    },
    "instruction": {
      "type": "string",
      "default": "Given a web search query, retrieve relevant passages that answer the query",
      "description": "Optional instruction for the task"
    },
    "documents": {
      "oneOf": [
        {
          "type": "string",
          "description": "A single document string",
          "minLength": 1
        },
        {
          "type": "array",
          "description": "An array of document strings",
          "items": {
            "type": "string",
            "minLength": 1
          },
          "maxItems": 32
        }
      ]
    },
    "text": {
      "oneOf": [
        {
          "type": "string",
          "description": "Alias for documents: a single text string",
          "minLength": 1
        },
        {
          "type": "array",
          "description": "Alias for documents: an array of text strings",
          "items": {
            "type": "string",
            "minLength": 1
          },
          "maxItems": 32
        }
      ]
    }
  }
}

{
  "type": "object",
  "properties": {
    "data": {
      "items": {
        "items": {
          "type": "number"
        },
        "type": "array"
      },
      "type": "array"
    },
    "shape": {
      "items": {
        "type": "integer"
      },
      "type": "array"
    }
  }
}