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Claude Code for FREE: Unlimited AI Coding (No GPU or Ollama Required)

Claude Code for FREE: Unlimited AI Coding (No GPU or Ollama Required)

Rashid Shahriar

Software Developer

The tech world is buzzing about Claude Code, Anthropic’s powerful terminal-based AI coding agent. However, most users are held back by expensive API costs or the slow performance of local models via Ollama.

What if you could run Claude Code with high-end models like DeepSeek V3 or GLM-4 for free, with almost no limits and lightning-fast speeds? Thanks to NVIDIA NIM APIs, you can. This guide will show you how to set up this "unlimited" alternative on Windows, Mac, and Linux.

Why This Method?

  • Zero Cost: Uses NVIDIA’s free NIM API credits.
  • No Heavy Hardware: Runs in the cloud; you don't need a powerful GPU or local Ollama setup.
  • High Performance: Access top-tier models (DeepSeek, GLM, MiniMax) that rival Claude 3.5 Sonnet.
  • Generous Limits: Supports up to 40 requests per minute—more than enough for intense coding sessions.

Step 1: Get Your NVIDIA NIM API Key

Before configuring your machine, you need access to the models.

  1. Visit the NVIDIA NIM API Portal.
  2. Sign up and verify your account with a phone number (mandatory for API access).
  3. Click on Generate API Key.
  4. Select an expiration (e.g., "Never Expire") and copy your key. Save this securely.

Step 2: Setup for Mac & Linux Users

Mac and Linux users can use a streamlined process using the uv package manager.

  1. Install UV: Open your terminal and run:
    Bash
    curl -LsSf https://astral.sh/uv/install.sh | sh
  2. Install Python 3.12+:
    Bash
    uv python install 3.12
  3. Download the NVIDIA NIM Bridge: Clone the necessary helper files (commands available at Compile Future):
    Bash
    git clone https://github.com/compile-future/nvidia-nim-bridge
    cd nvidia-nim-bridge
  4. Configure Environment:
    • Copy the example file: cp .env.example .env
    • Open .env and paste your NVIDIA API Key.
    • Choose a model (e.g., deepseek-ai/deepseek-v3) from the NVIDIA dashboard and update the MODEL field.
  5. Run the API Server:
    Bash
    uv run main.py
    Keep this terminal window open.

Step 3: Setup for Windows Users (WSL)

For the best development experience, Windows users should use WSL (Windows Subsystem for Linux).

  1. Install WSL: Open PowerShell as Administrator and type:
    PowerShell
    wsl --install
    Restart your PC after installation.
  2. Install Ubuntu: Download "Ubuntu" from the Microsoft Store, open it, and set your username/password.
  3. Follow Linux Steps: Once inside the Ubuntu terminal, follow the Mac & Linux instructions above (Install uv, clone the repo, and run the server).

Step 4: Launching Claude Code

Now that your local bridge is running and connected to NVIDIA’s cloud models, it’s time to start coding.

  1. Install Claude Code: Open a new terminal window and run:
    Bash
    npm install -g @anthropic-ai/claude-code
  2. Connect to the Local Bridge: Run this specific command to point Claude Code to your free NVIDIA-powered local host:
    Bash
    CLAUDE_BASE_URL=http://localhost:8000/v1 claude
  3. Verify Connection: Type /status in the Claude terminal. If you see localhost:8000, you are successfully using free NVIDIA models!

Real-World Performance

In testing, this setup successfully built a fully functional To-Do List application with a dark mode toggle and task filtering in just one prompt. The response time is significantly faster than local Ollama instances and provides "Sonnet-level" intelligence without the subscription fee.

Pro Tips:

  • Model Choice: Use deepseek-ai/deepseek-v3 for complex logic or glm-4-9b for fast, lightweight tasks.
  • Keep it Running: Remember, the terminal running uv run main.py must stay open while you use Claude Code.

Credits & Resources: