qwq-32b

Text Generation • Qwen

@cf/qwen/qwq-32b

  • Cloudflare-hosted
  • LoRA
  • Reasoning

QwQ is the reasoning model of the Qwen series. Compared with conventional instruction-tuned models, QwQ, which is capable of thinking and reasoning, can achieve significantly enhanced performance in downstream tasks, especially hard problems. QwQ-32B is the medium-sized reasoning model, which is capable of achieving competitive performance against state-of-the-art reasoning models, e.g., DeepSeek-R1, o1-mini.

Model Info
Context Window ↗ 24,000 tokens
Reasoning Yes
LoRA Yes
Unit Pricing $0.66 per M input tokens, $1.00 per M output tokens

Playground

Try out this model with Workers AI LLM Playground. It does not require any setup or authentication and is an instant way to preview and test a model directly in the browser.

Launch the LLM Playground

Usage

export interface Env {
  AI: Ai;
}

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

    const messages = [
      { role: "system", content: "You are a friendly assistant" },
      {
        role: "user",
        content: "What is the origin of the phrase Hello, World",
      },
    ];

    const stream = await env.AI.run("@cf/qwen/qwq-32b", {
      messages,
      stream: true,
    });

    return new Response(stream, {
      headers: { "content-type": "text/event-stream" },
    });
  },
} satisfies ExportedHandler<Env>;
export interface Env {
  AI: Ai;
}

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

    const messages = [
      { role: "system", content: "You are a friendly assistant" },
      {
        role: "user",
        content: "What is the origin of the phrase Hello, World",
      },
    ];
    const response = await env.AI.run("@cf/qwen/qwq-32b", { messages });

    return Response.json(response);
  },
} satisfies ExportedHandler<Env>;
import os
import requests

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

prompt = "Tell me all about PEP-8"
response = requests.post(
  f"https://api.cloudflare.com/client/v4/accounts/{ACCOUNT_ID}/ai/run/@cf/qwen/qwq-32b",
    headers={"Authorization": f"Bearer {AUTH_TOKEN}"},
    json={
      "messages": [
        {"role": "system", "content": "You are a friendly assistant"},
        {"role": "user", "content": prompt}
      ]
    }
)
result = response.json()
print(result)
curl https://api.cloudflare.com/client/v4/accounts/$CLOUDFLARE_ACCOUNT_ID/ai/run/@cf/qwen/qwq-32b \
  -X POST \
  -H "Authorization: Bearer $CLOUDFLARE_AUTH_TOKEN" \
  -d '{ "messages": [{ "role": "system", "content": "You are a friendly assistant" }, { "role": "user", "content": "Why is pizza so good" }]}'

OpenAI compatible endpoints

Workers AI also supports OpenAI compatible API endpoints for /v1/chat/completions and /v1/embeddings. For more details, refer to Configurations .

Parameters

Input

prompt

stringrequiredminLength: 1The input text prompt for the model to generate a response.

guided_json{}

objectJSON schema that should be fulfilled for the response.

raw

booleandefault: falseIf true, a chat template is not applied and you must adhere to the specific model's expected formatting.

stream

booleandefault: falseIf true, the response will be streamed back incrementally using SSE, Server Sent Events.

max_tokens

integerdefault: 256The maximum number of tokens to generate in the response.

temperature

numberdefault: 0.15minimum: 0maximum: 5Controls the randomness of the output; higher values produce more random results.

top_p

numberminimum: 0maximum: 2Adjusts the creativity of the AI's responses by controlling how many possible words it considers. Lower values make outputs more predictable; higher values allow for more varied and creative responses.

top_k

integerminimum: 1maximum: 50Limits the AI to choose from the top 'k' most probable words. Lower values make responses more focused; higher values introduce more variety and potential surprises.

seed

integerminimum: 1maximum: 9999999999Random seed for reproducibility of the generation.

repetition_penalty

numberminimum: 0maximum: 2Penalty for repeated tokens; higher values discourage repetition.

frequency_penalty

numberminimum: 0maximum: 2Decreases the likelihood of the model repeating the same lines verbatim.

presence_penalty

numberminimum: 0maximum: 2Increases the likelihood of the model introducing new topics.

Output

<details>

<summary>Synchronous — Send a request and receive a complete response</summary>

response

<code>string</code>The generated text response from the model

▶usage{}

<code>object</code>Usage statistics for the inference request

▶tool_calls[]

<code>array</code>An array of tool calls requests made during the response generation

</details>

<details>

<summary>Streaming — Send a request with stream: true and receive server-sent events</summary>

type

<code>string</code>

contentType

<code>text/event-stream</code>

format

<code>binary</code>

</details>

API Schemas (Raw)

SynchronousInput Open Download

SynchronousOutput Open Download

StreamingInput Open Download

StreamingOutput Open Download

Was this helpful?

YesNo

On this page

qwq-32b - 图1Docs

{"@context":"https://schema.org","@type":"TechArticle","@id":"https://developers.cloudflare.com/workers-ai/models/qwq-32b/#page","headline":"qwq-32b","description":"QwQ is the reasoning model of the Qwen series. Compared with conventional instruction-tuned models, QwQ, which is capable of thinking and reasoning, can achieve significantly enhanced performance in downstream tasks, especially hard problems. QwQ-32B is the medium-sized reasoning model, which is capable of achieving competitive performance against state-of-the-art reasoning models, e.g., DeepSeek-R1, o1-mini.","url":"https://developers.cloudflare.com/workers-ai/models/qwq-32b/","inLanguage":"en","image":"https://developers.cloudflare.com/og-docs.png","publisher":{"@type":"Organization","name":"Cloudflare","description":"One platform for your apps, agents, and workforce. Build, secure, and scale without managing infrastructure","url":"https://www.cloudflare.com/","sameAs":["https://github.com/cloudflare","https://www.linkedin.com/company/cloudflare","https://x.com/cloudflare"],"logo":{"@type":"ImageObject","url":"https://developers.cloudflare.com/logo.svg"},"address":{"@type":"PostalAddress","streetAddress":"101 Townsend St","addressLocality":"San Francisco","addressRegion":"CA","postalCode":"94107","addressCountry":"US"},"contactPoint":[{"@type":"ContactPoint","contactType":"Customer Support","url":"https://support.cloudflare.com/","availableLanguage":["English"]},{"@type":"ContactPoint","contactType":"Sales","url":"https://www.cloudflare.com/contact/","availableLanguage":["English"]}]},"isPartOf":{"@type":"WebSite","@id":"https://developers.cloudflare.com/#website","name":"Cloudflare Docs","url":"https://developers.cloudflare.com/"}}


description: Stable Diffusion Inpainting is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input, with the extra capability of inpainting the pictures by using a mask. title: stable-diffusion-v1-5-inpainting image: https://developers.cloudflare.com/og-docs.png


Skip to content

Documentation Index
Fetch the complete documentation index at: https://developers.cloudflare.com/llms.txt
Use this file to discover all available pages before exploring further.

RunwayML logo