How to Use Claude Code FREE & UNLIMITED (No GPU, No Limits!) 2026

The Problem With Claude Code’s Pricing

Claude Code is hands-down one of the most powerful AI coding tools available right now. It writes real, working code. It understands your entire project context. It refactors, debugs, and builds entire features autonomously. Developers who’ve used it describe it as having a senior engineer at their side 24/7.

There’s just one problem: it’s expensive.

Claude Code runs on Anthropic’s API, which charges per token. Heavy daily use can rack up $20–$100+ per month depending on your project size. For individual devs, students, or hobbyists, that’s a real barrier.

So what do most people try instead?

Why Local Models Don’t Cut It

The obvious workaround is running local models — tools like Ollama or LM Studio let you run open-source LLMs on your own machine. Free, private, and always available. Sounds perfect, right?

Not quite. Here’s the reality:

Smaller local models (7B, 13B) are fast, but they produce mediocre code, miss bugs, and lack the reasoning ability needed for real software projects. You end up babysitting the model more than writing code.

There had to be a better way — and there is.

The Solution: NVIDIA NIM + Proxy Server

Here’s the trick nobody talks about enough: NVIDIA NIM offers a free-tier API that gives you access to powerful hosted AI models — including frontier-class ones — completely free of charge (with generous rate limits for personal use).

The catch? Claude Code only talks to Anthropic’s API. It doesn’t know what NVIDIA NIM is.

This is where the proxy server comes in. We spin up a lightweight local server that:

1. Accepts requests from Claude Code (formatted as Anthropic API calls)
2. Translates and forwards them to NVIDIA NIM (or OpenRouter / DeepSeek)
3. Returns the response back to Claude Code in the format it expects

Claude Code thinks it’s talking to Anthropic. In reality, it’s routing through a free API. No GPU needed. No subscription. Just a running proxy on your machine.

Step 1 — Install Claude Code CLI

Claude Code is a CLI tool you install globally via npm. Open your terminal and run:

bash / terminal

npm install -g @anthropic-ai/claude-code

Once installed, verify it worked:

claude --version

You should see a version number like 1.x.x printed in your terminal. If you see “command not found,” make sure your npm global bin directory is in your PATH.

Step 2 — Install UV + Python

UV is a blazing-fast Python package manager written in Rust. It’s what we’ll use to run the proxy server cleanly, without polluting your system Python environment.

macOS / Linux

curl -LsSf https://astral.sh/uv/install.sh | sh

Windows (PowerShell)

powershell -c "irm https://astral.sh/uv/install.ps1 | iex"

After installing UV, verify Python is accessible:

uv python install 3.11

UV will download and manage Python 3.11 for you — no manual installation needed.

Step 3 — Clone the Proxy Repository

The proxy we’re using is an open-source project that acts as a middleware between Claude Code and free AI APIs. Clone it and set it up:

bash

# Clone the repository
git clone https://github.com/1rgs/claude-code-openai-proxy.git

# Move into the project folder
cd claude-code-openai-proxy

# Copy the example environment file
cp .env.example .env

Now open the .env file in your text editor. You’ll see placeholder values for your API keys — we’ll fill those in next.

Windows (PowerShell)

git clone https://github.com/1rgs/claude-code-openai-proxy.git
cd claude-code-openai-proxy
Copy-Item .env.example .env

Step 4 — Get Your Free API Keys

This is where the magic happens. You’ll need at least one free API key. Here are the three best options, ranked by recommendation:

Setting Up NVIDIA NIM (Primary)

1. Go to build.nvidia.com and create a free account.
2. Navigate to API Keys in your dashboard.
3. Click Generate API Key and copy it.
4. Paste it into your .env file as NVIDIA_API_KEY=your_key_here

Step 5 — Configure Model Mappings

Claude Code internally refers to models as Opus, Sonnet, and Haiku. Our proxy needs to know which free model to substitute for each. Open your .env file and configure:

.env

# Primary provider
NVIDIA_API_KEY=nvapi-xxxxxxxxxxxxxxxxxxxx

# Optional providers
OPENROUTER_API_KEY=sk-or-xxxxxxxxxxxxxxxxxxxx
DEEPSEEK_API_KEY=sk-xxxxxxxxxxxxxxxxxxxx

# Model mappings
BIG_MODEL=nvidia/llama-3.1-nemotron-70b-instruct
SMALL_MODEL=nvidia/llama-3.1-8b-instruct

Here’s what each Claude model maps to under the hood:

You can customize these mappings to any model your API keys support. Check each provider’s documentation for available model IDs.

Step 6 — Run the Proxy Server

Now we’ll start the proxy server. This runs a local HTTP server on port 8082 that Claude Code will connect to.

bash / terminal — from inside the cloned folder

# Install dependencies (first time only)
uv sync

# Start the proxy server
uv run uvicorn server:app --port 8082 --host 0.0.0.0

You should see output like:

INFO:     Uvicorn running on http://0.0.0.0:8082 (Press CTRL+C to quit)
INFO:     Application startup complete.

Step 7 — Run Claude Code

Now open a new terminal window (keep the proxy running in the previous one) and run Claude Code with these environment variables pointing it at your local proxy:

macOS / Linux (bash)

ANTHROPIC_BASE_URL=http://localhost:8082 \
ANTHROPIC_API_KEY=dummy-key \
claude

Windows (PowerShell)

$env:ANTHROPIC_BASE_URL = "http://localhost:8082"
$env:ANTHROPIC_API_KEY = "dummy-key"
claude

Claude Code will launch in your terminal. The dummy-key is intentional — the proxy handles real authentication with NVIDIA NIM using the key in your .env file. Claude Code just needs any non-empty string to start.

Pro Tips: Sandbox & Safety

Claude Code can autonomously edit files, run commands, and make real changes to your project. Before you let it loose, here are four things every user should know:

Example Use Case: Build a Tic-Tac-Toe Game

Let’s see this in action. With your proxy running and Claude Code launched, navigate to an empty folder and try this prompt:

Here’s what happens next — and it will blow your mind the first time you see it:

1. Claude Code thinks for a few seconds, then proposes a plan.
2. It creates index.html with full game logic.
3. It runs the file to verify there are no obvious errors.
4. It reports back: “Game created successfully. Open index.html in your browser.”

You now have a working tic-tac-toe game. Total cost: $0.00. Total time: under 60 seconds.

From here, you can say things like “Add an AI opponent that plays optimally” or “Make the design dark mode with animations” — and Claude Code will iterate on the file autonomously.