Run Claude Code Offline and for Free Using Local AI Models

Unlock the Power of Claude Code Without Paying a Dime

Are you tired of the high costs associated with using AI-powered tools and services? Look no further than Claude Code - a powerful AI automation platform that you can run completely offline and for free on your own computer. In this comprehensive guide, we'll walk you through the step-by-step process of setting up your own local AI model and integrating it with Claude Code to unlock its full potential without any API charges or internet connectivity requirements.

Video: https://youtu.be/gskReY3hTBI?si=pmHs5Enxk8zRXwsD

The Benefits of Running Claude Code Offline

Traditionally, using AI-powered tools like Claude Code has come with a hefty price tag due to the API charges and cloud computing costs associated with running these models on remote servers. However, with the ability to run Claude Code offline using a local AI model, you can enjoy a range of benefits:

• No API Charges: By running Claude Code with a local AI model, you eliminate the need to pay any API charges, allowing you to use the platform for free.

• Offline Functionality: With a local AI model, Claude Code can operate completely offline, without requiring an internet connection. This ensures your data and projects remain private and secure.

• Faster Performance: Running Claude Code on your own hardware can provide faster response times and more efficient processing compared to relying on remote cloud servers.

• Customization and Control: By using a local AI model, you have the ability to choose the specific model that best suits your needs and hardware capabilities, giving you more control over the performance and capabilities of Claude Code.

Hardware Requirements for Running Claude Code Offline

To run Claude Code offline with a local AI model, you'll need a decent piece of hardware that can handle the computational demands of the model. The specific hardware requirements will depend on the AI model you choose to use, but as a general guideline, the following specifications are recommended:

• Processor: A modern, multi-core CPU with good single-threaded performance, such as an Intel Core i5 or AMD Ryzen 5 or higher.

• Memory: At least 16GB of RAM, with 32GB or more being ideal for larger AI models.

• Storage: A fast solid-state drive (SSD) with at least 512GB of storage, as the AI models can be quite large.

• Graphics: While not strictly necessary, a dedicated graphics card can provide a significant performance boost for certain AI tasks.

The hardware requirements may vary depending on the specific AI model you choose to use. For example, the GPT-OSS 20 billion parameter model is well-suited for a high-end MacBook, while the Qwen Coder 3 or GPT-OSS 12 billion models may be more appropriate for mid-range systems, and the Qwen 2.5 Coder is a lighter option for lower-end hardware.

Setting Up Claude Code with a Local AI Model

Now that you understand the benefits and hardware requirements, let's dive into the step-by-step process of setting up Claude Code to run with a local AI model. We'll be following the instructions provided in the free setup document.

Step 1: Install Ollama

The first step is to install Ollama, a software that allows you to install and run local AI models on your computer. To do this, simply run the following command in your terminal:

pip install ollama

Once Ollama is installed, you can verify the installation by running the following command:

ollama version

Step 2: Pull Your Local AI Model

Next, you'll need to download and install the AI model you want to use with Claude Code. The GPT-OSS 20 billion parameter model is a great choice for high-end systems, while the Qwen Coder 3, GPT-OSS 12 billion, or Qwen 2.5 Coder models may be more suitable for mid-range or lower-end hardware.

To download and install the model of your choice, simply run the corresponding command from the setup document in your terminal:

ollama pull gpt-oss-20b

This will download and install the GPT-OSS 20 billion parameter model on your system. Once the installation is complete, you can verify that the model is available by running the following command:

ollama models

Step 3: Install Node.js

Claude Code is built on Node.js, so you'll need to have it installed on your system. You can download and install the latest version of Node.js from the official website: https://nodejs.org.

Step 4: Install Claude Code

With Ollama and Node.js set up, you can now install Claude Code using the following command:

npm install anthropic-cloud-code

This will install the Claude Code package on your system, allowing you to use it with your local AI model.

Step 5: Launch Claude Code with Your Local Model

Finally, you can launch Claude Code and start using it with your local AI model by running the following command:

ollama run anthropic-cloud-code --model gpt-oss-20b

This command will start the Claude Code server and connect it to the GPT-OSS 20 billion parameter model you installed earlier. You can now access the Claude Code interface by opening your web browser and navigating to http://localhost:8080.

Putting Claude Code to Work Offline

With Claude Code set up and running with your local AI model, you can now start using the platform to automate a wide range of tasks, all without the need for an internet connection or API charges. The creator demonstrates how to use Claude Code to build a simple Todo app entirely offline.

To try this yourself, simply enter the following prompt in the Claude Code interface:

Build me a basic Todo app in simple JavaScript

Claude Code will then use your local AI model to generate the necessary code to create a functional Todo app, all without relying on any external services or internet connectivity. You can then copy the generated code and use it in your own projects or continue to refine and expand the application as needed.

Switching Between AI Models

One important thing to keep in mind when using Claude Code with a local AI model is that the command to launch the platform may need to be adjusted depending on the specific model you're using. If you're using a different model like Qwen Coder or a different version of the GPT-OSS model, you'll need to update the --model flag accordingly.

For example, if you're using the Qwen Coder 3 model, the command to launch Claude Code would be:

ollama run anthropic-cloud-code --model qwen-coder-3

Be sure to refer to the setup document to ensure you're using the correct model name when launching Claude Code.

Running Claude Code in Visual Studio Code

In addition to running Claude Code directly in the terminal, you can also integrate it with Visual Studio Code (VS Code) for a more seamless development experience. To do this, simply open a folder in VS Code, launch the integrated terminal, and run the same command you used to start Claude Code earlier:

ollama run anthropic-cloud-code --model gpt-oss-20b

This will start the Claude Code server within the VS Code environment, allowing you to interact with the platform and generate code directly from the IDE.