---
title: qwen3-embedding-0.6b
description: The Qwen3 Embedding model series is the latest proprietary model of the Qwen family, specifically designed for text embedding and ranking tasks. 
image: https://developers.cloudflare.com/dev-products-preview.png
---

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![Qwen logo](https://developers.cloudflare.com/_astro/qwen.CVqFFn5h.svg) 

#  qwen3-embedding-0.6b 

Text Embeddings • Qwen 

`@cf/qwen/qwen3-embedding-0.6b` 

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[ ↗](https://developers.cloudflare.com/workers-ai/glossary/) | 8,192 tokens              |
| Unit Pricing                                                               | $0.012 per M input tokens |

## Usage

* [  TypeScript ](#tab-panel-5269)
* [  Python ](#tab-panel-5270)
* [  curl ](#tab-panel-5271)

```
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 osimport 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())
```

Terminal window

```
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"] }'
```

OpenAI compatible endpoints 

Workers AI also supports OpenAI compatible API endpoints for `/v1/chat/completions` and `/v1/embeddings`. For more details, refer to [Configurations ](https://developers.cloudflare.com/workers-ai/configuration/open-ai-compatibility/). 

## Parameters

* [ Input ](#tab-panel-5272)
* [ Output ](#tab-panel-5273)

▶queries

`one of`

instruction

`string`default: 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 [ ](https://developers.cloudflare.com/workers-ai/models/qwen3-embedding-0.6b/schema-input.json "Open") [ ](https://developers.cloudflare.com/workers-ai/models/qwen3-embedding-0.6b/schema-input.json "Download") 

Output [ ](https://developers.cloudflare.com/workers-ai/models/qwen3-embedding-0.6b/schema-output.json "Open") [ ](https://developers.cloudflare.com/workers-ai/models/qwen3-embedding-0.6b/schema-output.json "Download")

```json
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```