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Want to experience the power of large models but struggle with limited local computer performance? Typically, we deploy models locally using tools like ollama, but due to computer resource constraints, we often can only run smaller-scale models such as 1.5b (1.5 billion), 7b (7 billion), or 14b (14 billion). Deploying a large model with 70 billion parameters is a huge challenge for local hardware.

Now, you can use Cloudflare's Workers AI to deploy large models like 70b online and access them via the internet. Its interface is compatible with OpenAI, meaning you can use it just like OpenAI's API. The only downside is the limited daily free quota, with additional usage incurring costs. If you're interested, give it a try!

Preparation: Log in to Cloudflare and Bind a Domain ​

If you don't have your own domain, Cloudflare provides a free account domain. However, note that this free domain may not be directly accessible in some regions, and you might need to use some "magic" to access it.

First, go to the Cloudflare website (https://dash.cloudflare.com) and log in to your account.

Step 1: Create Workers AI ​

  1. Find Workers AI: In the left navigation bar of the Cloudflare dashboard, find "AI" -> "Workers AI", then click "Create from Worker Template".

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  2. Create Worker: Next, click "Create Worker".

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  3. Enter Worker Name: Input a string of English letters, which will serve as your Worker's default account domain.

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  4. Deploy: Click the "Deploy" button in the bottom right corner to complete the Worker creation.

Step 2: Modify Code to Deploy Llama 3.3 70b Large Model ​

  1. Enter Code Editor: After deployment, you'll see the interface as shown below. Click "Edit Code".

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  2. Clear Code: Delete all preset code in the editor.

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  3. Paste Code: Copy and paste the following code into the code editor:

    Here, we are using the llama-3.3-70b-instruct-fp8-fast model, which has 70 billion parameters.

    You can also find other models to replace it on the Cloudflare Models Page, such as Deepseek open-source models. Currently, llama-3.3-70b-instruct-fp8-fast is one of the largest and most effective models available.

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    javascript
    const API_KEY='123456';
export default {
  async fetch(request, env) {

    let url = new URL(request.url);
    const path = url.pathname;

    const authHeader = request.headers.get("authorization") || request.headers.get("x-api-key");
    const apiKey = authHeader?.startsWith("Bearer ")  ? authHeader.slice(7)  : null;
                         
    if (API_KEY && apiKey !== API_KEY) {

      return new Response(JSON.stringify({
        error: {
            message: "Invalid API key. Use 'Authorization: Bearer your-api-key' header",
            type: "invalid_request_error",
            param: null,
            code: "invalid_api_key"
        }
      }), {
          status: 401,
          headers: {
              "Content-Type": "application/json",
          }
      });
    }

    if (path === "/v1/chat/completions") {
      const requestBody = await request.json();
       // messages - chat style input
      const {message}=requestBody
      let chat = {
        messages: message
      };
      let response = await env.AI.run('@cf/meta/llama-3.3-70b-instruct-fp8-fast', requestBody);
     
      let resdata={
        choices:[{"message":{"content":response.response}}]
      }    
      return Response.json(resdata);
    }  
    
  }
};

  4. Deploy Code: After pasting the code, click the "Deploy" button.

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Step 3: Bind a Custom Domain ​

  1. Return to Settings: Click the back button on the left to return to the Worker management page, then find "Settings" -> "Domains and Routes".

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  2. Add Custom Domain: Click "Add Domain", then select "Custom Domain" and enter the subdomain you've already bound to Cloudflare.

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Step 4: Use with OpenAI-Compatible Tools ​

After adding a custom domain, you can use this large model in any tool that is compatible with the OpenAI API.

  • API Key: This is the API_KEY you set in the code, defaulting to 123456.
  • API Address: https://your-custom-domain/v1

Thanks to Cloudflare's powerful GPU resources, the experience will be very smooth.

Important Notes ​

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