Claude Code for Free: Cut Your AI Costs by 95% With This Simple Proxy Setup

Claude Code is hands-down the best coding agent on the market right now. But it’ll run you anywhere between $20 to $200 a month — with rate limits that kick in right when you’re in the middle of something important, and quality that can feel inconsistent depending on what you’re building.

What if you could use the exact same Claude Code interface — same terminal, same commands, same workflow — but swap out the expensive Anthropic backend for something that costs a fraction of the price?

That’s exactly what this guide covers. We’re talking about 80–90% of the quality of Opus 4.7 for literally 2–5% of the cost.

Someone literally built a full habit-tracking app using this method for around $3. The same build would have cost $5–$10 using standard Anthropic credits. We’re talking several hundred times cheaper — and that’s not an exaggeration.

Here’s how it works and how to set it up yourself in under 15 minutes.

What Is “Free Claude Code” and How Does It Work?

Normally when you use Claude Code, every request goes straight to Anthropic’s API and you get billed based on token usage. The “free Claude Code” approach intercepts that request before it ever reaches Anthropic and reroutes it through a local proxy server on your computer.

That proxy then forwards your request to one of three alternative model providers:

• OpenRouter — Access to dozens of models starting as low as $0.14 per million tokens (vs $25/million for Opus)
• NVIDIA NIM — Free tier available using NVIDIA’s GPU infrastructure, including some models that are completely free with an account
• Ollama — Run models 100% locally on your own machine using your GPU, completely free forever

The Claude Code interface has absolutely no idea anything changed. It still looks the same, behaves the same, accepts the same commands. The only difference is the brain powering it is now DeepSeek, GLM 4.7, Gemma 4, or whatever model you choose — instead of Opus.

Before You Start — What You Need

• Claude Code installed on your machine
• A terminal (Mac/Linux: Terminal or iTerm; Windows: PowerShell)
• Git installed
• Node.js installed
• 10–15 minutes

No advanced technical experience needed. We’ll walk through every step.

Step 1: Clone the Free Claude Code Proxy Repo

The whole thing is built on an open-source repo called free-claude-code. It’s been blowing up recently — went from basically zero to thousands of stars in just a couple of months.

Important: The point here isn’t to get locked into this specific repo. It’s to understand the approach — a local proxy that intercepts Claude Code requests and reroutes them to cheaper models. There are several tools that do this. Once you understand it, you can swap any of them in.

Open your terminal and run these three commands one by one:

On Mac / Linux:

# Install dependencies (skip any you already have)
brew install node git

# Clone the repo
git clone https://github.com/Alishahryar1/free-claude-code.git

# Navigate into the folder
cd free-claude-code

On Windows (PowerShell):

# Clone the repo
git clone https://github.com/Alishahryar1/free-claude-code.git

# Navigate into the folder
cd free-claude-code

That’s honestly most of the setup done. You now have the proxy folder on your machine.

Step 2: Configure Your API Keys (The .env File)

Inside the folder there’s a hidden file called .env. This is where you paste in your API keys for whichever provider you want to use.

On Mac: Hidden files start with a dot and won’t show up by default. To reveal them in Finder, press Cmd + Shift + . (Command + Shift + Period). Press it again to hide them.

In Terminal: Use ls -a to see hidden files in your current directory.

Open .env in any text editor (VS Code, Notepad, TextEdit — anything works). You’ll see placeholder sections for OpenRouter, NVIDIA NIM, DeepSeek, and Ollama. Fill in whichever one you’re using.

Option A: Set Up OpenRouter (Recommended for Most People)

OpenRouter is the easiest drop-in replacement. Tons of model choices, pay-as-you-go, no subscription. DeepSeek V4 Flash is a great starting point at around $0.14 per million tokens.

Get Your OpenRouter API Key

1. Go to openrouter.ai and create a free account
2. Click your profile → API Keys
3. Click Create Key — give it a name, set an expiry if you want
4. Copy the key immediately — you won’t be able to see it again after closing the dialog

Pick Your Model

1. On OpenRouter, click Models → Browse All Models
2. Search for the model you want — e.g., deepseek v4 flash
3. Click the copy icon next to the model ID — it’ll look something like: deepseek/deepseek-v4-flash

Update Your .env File

Open your .env file and fill in two values in the OpenRouter section:

OPENROUTER_API_KEY=your_api_key_here
OPENROUTER_MODEL=deepseek/deepseek-v4-flash

Save the file.

Start the Proxy

Back in your terminal (make sure you’re in the free-claude-code directory), run:

npm run start

You should see something like: Proxy running on localhost:8082

Launch Claude Code Through the Proxy

Open a second terminal window and run:

ANTHROPIC_BASE_URL=http://localhost:8082 ANTHROPIC_AUTH_TOKEN=any-string claude

That’s it. Claude Code opens up and you’re now running DeepSeek V4 Flash instead of Opus. The interface is identical. The cost is a fraction.

You can verify it’s working by watching the first terminal window — every request that comes through will show up as a real-time log.

Fun fact: If you ask the agent “what model are you?” it’ll confidently say it’s Claude Opus 4.6. That’s because Claude Code’s system prompt is baked into every request and the model just runs with it. But if you check your OpenRouter logs, you’ll clearly see the requests going to DeepSeek — not Anthropic.

Option B: Set Up NVIDIA NIM (100% Free Tier Available)

NVIDIA NIM lets you run AI models on NVIDIA’s massive GPU infrastructure. Some models — including GLM 4.7 — are completely free with an account. No credit card needed.

Create Your NVIDIA NIM Account

1. Go to build.nvidia.com
2. Sign up with your email (you’ll need a phone number for verification)
3. Once logged in, click Generate API Key
4. Copy it immediately

Pick a Free Model

1. In the NVIDIA NIM dashboard, click Models
2. Look for GLM 4.7 — it’s currently free and performs well for coding tasks
3. The model ID you’ll need is: nvidia/nim/z-ai/glm-4.7

Update Your .env File

NVIDIA_NIM_API_KEY=your_nvidia_api_key_here
NVIDIA_NIM_MODEL=nvidia/nim/z-ai/glm-4.7

Save, restart the proxy (Ctrl+C to stop, then npm run start again), and launch Claude Code the same way as before.

Heads up: Some Claude Code features like “fast mode” aren’t supported by these models. If you get an API error mentioning unsupported parameters, just make sure fast mode is turned off in your Claude Code settings before sending requests.

Option C: Set Up Ollama (100% Local, 100% Free Forever)

Ollama runs AI models entirely on your own hardware — your GPU, your computer, no internet required after the initial download. Everything is private and completely offline.

The tradeoff: speed. If you don’t have a powerful GPU, responses will be slow. But for experimenting or privacy-sensitive work, it’s unbeatable.

Install Ollama

1. Go to ollama.com
2. Download and install the app for your OS (Mac, Windows, Linux all supported)
3. Once installed, open your terminal and type ollama to confirm it’s running

Download a Model

You can download models directly from the Ollama app’s UI or via terminal. For a solid balance of quality and speed, Gemma 4 is a good choice (around 10 GB download):

ollama pull gemma4

For lighter-weight options on older hardware, try:

ollama pull llama3.2

Once the download finishes, start the Ollama server:

ollama serve

Update Your .env File

OLLAMA_BASE_URL=http://localhost:11434
OLLAMA_MODEL=ollama/gemma4:latest

Always prepend the model name with ollama/ in the config file.

Restart the proxy and launch Claude Code as usual. You’ll hear your laptop fan spin up — that’s your computer doing all the AI matrix math locally. Pretty wild feeling the first time it happens.

The Orchestration Strategy — How to Get the Best of Both Worlds

Here’s where things get really interesting for people who want to optimize both cost and quality.

The concept: use a smart model as the orchestrator and a cheap model as the worker.

Think of it like a senior developer and a junior developer on a team:

• The orchestrator (e.g., Claude Opus) takes your high-level request, breaks it down, gives clear instructions, reviews the output, and decides what to do next
• The worker (e.g., DeepSeek V4 Flash) receives those clear instructions and does the actual heavy lifting — writing code, refactoring, generating files

Anthropic actually tested this internally — pairing Opus 4.5 with Sonnet 4.5 as sub-agents improved performance by around 15% compared to using one model for everything. What this approach does is take that same idea but uses a model that’s hundreds of times cheaper for the sub-agent work.

Real-world example: Someone used Opus 4.6 as the orchestrator to plan and direct a calorie tracker app build, then had it send the actual coding tasks to DeepSeek V4 Flash through the proxy. The result was a fully functional, good-looking app — built at a fraction of the cost of doing everything through Opus alone.

You can also reset context every ~50,000 tokens. Past that point, response quality tends to drop off noticeably. Opening a fresh Claude Code instance every 50K tokens keeps quality consistent throughout long build sessions.

Which Models Are Worth Using?

Here’s a quick reference based on what’s available right now:

Ollama also has a huge library of community fine-tuned models — specialized for accounting, payroll, legal, medical, and more. Worth browsing if you’re building for a specific industry.

Troubleshooting — Common Issues

The Business Angle — Why This Matters Beyond Just Saving Money

If you’re building AI agents or automation systems for clients, this changes your entire cost structure.

Right now, a lot of developers building with Claude Code treat API costs as a fixed overhead. At $25 per million tokens, a complex agent build with lots of back-and-forth can easily run $50–$100+ in API costs alone. That eats into margins fast, especially on smaller projects.

With this approach:

• You can prototype freely without watching your API spend
• You can run longer context sessions without cutting corners
• You can build internal tools and demos at near-zero cost
• You can pass savings on to clients and price more competitively
• You can use the smarter (pricier) models only when they’re actually needed — complex architecture decisions, tricky debugging, final QA passes

The ideal workflow for client work looks something like this: Opus for strategy and review, DeepSeek (or similar) for implementation. You get near-Opus output quality at a fraction of the price, and your clients never know the difference.

Quick Start Cheatsheet

# 1. Clone the repo
git clone https://github.com/Alishahryar1/free-claude-code.git
cd free-claude-code

# 2. Edit .env with your API key and model choice
# (See sections above for each provider)

# 3. Start the proxy (Terminal window 1)
npm run start

# 4. Launch Claude Code through the proxy (Terminal window 2)
ANTHROPIC_BASE_URL=http://localhost:8082 ANTHROPIC_AUTH_TOKEN=free claude

Wrapping Up

The core insight here is simple: Claude Code is a harness, not just a model. The interface, the commands, the agent behavior — that’s all the harness. The actual intelligence powering it is swappable. And right now, there are some genuinely impressive open models available that can do 80–90% of what Opus does at a tiny fraction of the cost.

That gap will only close over time as open models keep improving. Getting comfortable with this setup now means you’re ahead of the curve when it comes to building cost-efficient AI systems.

Try it out. Build something. See how far you can get before you actually need to reach for a frontier model.

Found this useful? Drop a comment below with what you end up building — and share this with anyone who’s been put off by Claude Code’s pricing. At GTAVille.com we cover practical AI tools and automation for builders who want to move fast without burning money. Hit subscribe so you don’t miss the next one.