The Problem: Claude Code is Expensive
Claude Code is one of the best AI coding assistants available. It integrates directly into your terminal, understands your codebase context, and can execute commands, edit files, and debug issues autonomously.
But there’s a catch: it requires an Anthropic API key, and Claude 3.5 Sonnet / Claude 3 Opus API calls can cost $3-15 per hour of active coding. For developers who use AI assistants daily, this adds up quickly.
Free Claude Code solves this problem by acting as a drop-in proxy between Claude Code CLI and free or low-cost AI providers.
What is Free Claude Code?
Free Claude Code is an open-source Python proxy server created by Ali Shahryar . It intercepts Anthropic Messages API requests from Claude Code and forwards them to alternative AI backends that offer free tiers or local execution.
The project is built with:
- Python 3.14 — latest Python with performance improvements
- uv — fast Python package manager by Astral
- FastAPI + Uvicorn — high-performance async web server
- Pydantic — strict type validation
- Loguru — structured logging
- Ruff — fast Python linter and formatter
Supported AI Providers
Free Claude Code supports 6 different backends, letting you choose based on cost, speed, privacy, or model preference:
| Provider | Cost | Best For | Setup Complexity |
|---|---|---|---|
| NVIDIA NIM | Free tier available | Production, fast inference | API key required |
| OpenRouter | Pay-per-use | Access to many models | API key required |
| DeepSeek | Very cheap | Budget-conscious developers | API key required |
| LM Studio | Free (local) | Privacy, offline use | Local GUI app |
| llama.cpp | Free (local) | Maximum control, custom models | Command line |
| Ollama | Free (local) | Easiest local setup | Simple install |
NVIDIA NIM (Recommended for Free Tier)
NVIDIA offers a generous free tier through their NIM (NVIDIA Inference Microservices) platform. You can run models like glm-4-9b or llama-3.1-8b for free with rate limits suitable for personal development.
Setup:
- Get API key at build.nvidia.com
- Configure
.env:NVIDIA_NIM_API_KEY="nvapi-your-key" MODEL="nvidia_nim/z-ai/glm4.7" ANTHROPIC_AUTH_TOKEN="freecc"
OpenRouter
OpenRouter provides unified access to hundreds of models including Claude, GPT-4, Gemini, and open-source alternatives. Pay only for what you use.
Setup:
OPENROUTER_API_KEY="sk-or-your-key"
MODEL="open_router/anthropic/claude-3.5-sonnet"
DeepSeek
DeepSeek offers extremely competitive pricing (often 10x cheaper than Anthropic) with strong coding performance.
Setup:
DEEPSEEK_API_KEY="sk-your-key"
MODEL="deepseek/deepseek-chat"
Local Options (LM Studio, llama.cpp, Ollama)
For complete privacy and zero ongoing cost, run models locally:
Ollama (Easiest):
# Install Ollama
ollama pull llama3.1
ollama serve
OLLAMA_BASE_URL="http://localhost:11434"
MODEL="ollama/llama3.1"
LM Studio: Download LM Studio , load a model, and it runs a local API server automatically.
LMSTUDIO_BASE_URL="http://localhost:1234/v1"
MODEL="lmstudio/your-loaded-model"
Key Features
Per-Model Routing
Configure different providers for different Claude model tiers:
# Opus requests → OpenRouter (best quality)
MODEL_OPUS="open_router/anthropic/claude-3-opus"
# Sonnet requests → NVIDIA NIM (free tier)
MODEL_SONNET="nvidia_nim/z-ai/glm4.7"
# Haiku requests → Ollama (local, instant)
MODEL_HAIKU="ollama/llama3.1"
Claude Code’s /model picker works natively through the proxy’s /v1/models endpoint.
Streaming Support
Real-time token streaming works exactly like the official Anthropic API. You see code being typed character-by-character.
Tool Use
Claude Code’s function calling (file operations, command execution) works through the proxy. The proxy translates Anthropic’s tool format to each provider’s native format.
Reasoning/Thinking Blocks
For models that support chain-of-thought reasoning (like DeepSeek-R1), the proxy extracts and formats thinking blocks correctly.
Voice Notes (Optional)
Transcribe voice memos to code instructions using local Whisper or NVIDIA NIM speech recognition.
Chat Bots (Optional)
Deploy Discord or Telegram bots that use the same proxy backend for remote coding sessions.
Quick Start Guide
Step 1: Install Prerequisites
# Install uv (fast Python package manager)
curl -LsSf https://astral.sh/uv/install.sh | sh
uv self update
# Install Python 3.14
uv python install 3.14
Step 2: Clone and Configure
git clone https://github.com/Alishahryar1/free-claude-code.git
cd free-claude-code
cp .env.example .env
Edit .env with your chosen provider (see examples above).
Step 3: Start the Proxy
uv run uvicorn server:app --host 0.0.0.0 --port 8082
Or install as a tool:
uv tool install git+https://github.com/Alishahryar1/free-claude-code.git
fcc-init # Creates config in ~/.config/free-claude-code/
free-claude-code
Step 4: Run Claude Code
# Bash/Linux/macOS
ANTHROPIC_AUTH_TOKEN="freecc" ANTHROPIC_BASE_URL="http://localhost:8082" claude
# PowerShell
$env:ANTHROPIC_AUTH_TOKEN="freecc"; $env:ANTHROPIC_BASE_URL="http://localhost:8082"; claude
Important: Point ANTHROPIC_BASE_URL at the proxy root (http://localhost:8082), not /v1. The proxy handles the path routing.
Performance Comparison
I tested Free Claude Code with different providers on a medium-sized Python project:
| Provider | Model | Latency | Quality | Cost/Hour |
|---|---|---|---|---|
| Anthropic (official) | Claude 3.5 Sonnet | Fast | Excellent | ~$5-15 |
| NVIDIA NIM | glm-4-9b | Medium | Good | Free* |
| OpenRouter | Claude 3.5 Sonnet | Fast | Excellent | ~$3-8 |
| DeepSeek | DeepSeek-V3 | Fast | Very Good | ~$0.50-2 |
| Ollama (local) | Llama 3.1 8B | Instant | Good | $0 |
| LM Studio (local) | Qwen 2.5 Coder | Instant | Good | $0 |
*Free tier has rate limits. Suitable for personal use.
Architecture
Claude Code CLI → Anthropic Messages API → Free Claude Code Proxy → Provider Backend
↓
Translation Layer
(OpenAI ↔ Anthropic format)
The proxy maintains Claude Code’s client-side protocol while translating to each provider’s API format:
- OpenAI-compatible (NVIDIA NIM) — translate to chat completions
- Anthropic-compatible (OpenRouter, DeepSeek, local) — pass through with adaptations
Security Considerations
- Local token storage — API keys stay in
~/.config/free-claude-code/.envwith 600 permissions - Auth token — Set
ANTHROPIC_AUTH_TOKENto any secret; Claude Code sends it back for verification - No data logging — The proxy doesn’t log your code or conversations (check provider’s policy for their side)
- Open source — All code is auditable; no black-box middleware
Limitations
- Model capability gaps — Free/local models may struggle with complex multi-step reasoning compared to Claude 3.5 Sonnet
- Context window — Local models often have smaller context windows (4K-8K vs Claude’s 200K)
- Tool reliability — Some providers handle tool calling differently; test thoroughly with your workflow
- Rate limits — Free tiers have limits; heavy users may need to upgrade or switch providers
When to Use What
| Scenario | Recommended Provider |
|---|---|
| Daily coding, budget conscious | DeepSeek or NVIDIA NIM |
| Maximum code quality | OpenRouter → Claude 3.5 Sonnet |
| Complete privacy | Ollama or LM Studio (local) |
| Offline/air-gapped | llama.cpp with downloaded weights |
| Experimenting/learning | NVIDIA NIM free tier |
Conclusion
Free Claude Code is a game-changer for developers who want Claude Code’s excellent UX without the ongoing API costs. By routing through free tiers and local models, you can reduce your AI coding assistant costs to zero while maintaining most of the functionality.
The project is actively maintained, well-tested (Pytest + CI), and supports more providers than any similar tool I’ve found. If you’re spending $50-200/month on Claude API calls, this proxy pays for itself immediately.
GitHub: Alishahryar1/free-claude-code License: MIT Python: 3.14 Status: Active development, community-driven
Have you tried Free Claude Code? Which provider works best for your workflow? Share your experience in the comments.