Claude Code Now Runs Locally, Offering Free Offline AI Programming

Claude Code, an AI programming tool, has been open-sourced, enabling local execution without API fees or cloud dependencies. This development allows users to run an AI programmer on their personal computers, ensuring privacy and unlimited use.

Laptop screen showing code with privacy and no-cloud icons, representing local AI code execution.

The local implementation of Claude Code eliminates concerns about Anthropic API costs, rate limits, and the uploading of sensitive code to external servers. It operates directly on macOS and Windows systems, providing a private environment for code generation and modification.

Background and Technical Details

Traditional Claude Code relies on API keys, requiring payment and cloud-based processing, which can be a barrier for projects with sensitive data. However, Ollama now supports the Anthropic Messages API, facilitating a direct interface between Claude Code and local models. This creates a fully offline AI coding agent capable of reading files, modifying code, and executing commands. Even without high-end graphics cards, users can run 7B to 30B coding-specific models for daily development, debugging, and script generation.

Abstract glowing neural network with code snippets, representing AI's technical foundation.

The open-sourcing of Claude Code followed the discovery of a configuration error in Anthropic's npm, which allowed for the reconstruction of 510,000 lines of source code from a 59.8MB .map file. This discovery was made by a computer science Ph.D. dropout known for expertise in program analysis and web security.

Local Installation Guide

Setting up Claude Code for local use involves a few steps, typically taking about five minutes.

Preparation

1. Download and install Ollama from ollama.com. Ollama supports both macOS and Windows and runs automatically in the background after installation.

2. Verify the installation by opening a terminal and typing ollama --version.

Computer screen showing Ollama installation and model pull commands in a terminal.

Model Pull

Users need to pull a local model. For systems with 16-32GB RAM, qwen3-coder:7b or gemma2:9b are recommended. High-end devices, such as those with an RTX 4090 or Mac M series, can use qwen3-coder:30b or GLM-4 series models. An example command to pull a 7B model is: ollama pull qwen3-coder:7b.

Claude Code Installation

Install Claude Code by executing the official command in the terminal: curl -fsSL https://claude.ai/install.sh | sh.

Configuration for Local Ollama

To point Claude Code to the local Ollama instance, users can use the automatic configuration method: ollama launch claude --model qwen3-coder:7b. Alternatively, environment variables can be set manually: export ANTHROPIC_BASE_URL="http://localhost:11434" export ANTHROPIC_AUTH_TOKEN="ollama" Then, run Claude Code with: claude --model qwen3-coder:7b.

Developer typing 'claude' command into a terminal, showing AI code generation.

Testing the Setup

Navigate to a project folder, type claude, and issue a command such as "Help me create a Hello World website." Claude Code will then analyze the directory, create files, and execute operations locally.

Notes and Advanced Tips

Model selection is crucial for performance. Qwen3-Coder and GLM series models are optimized for coding tasks, followed by Gemma2. Ollama plans to support additional models with strong tool-calling capabilities in the future.

Hardware requirements vary by model size. While 7B models can run on standard laptops, 30B models benefit from a dedicated GPU or more than 32GB of RAM.

A key advantage of this local setup is enhanced privacy, as all data processing occurs offline without requiring an internet connection. Although the intelligence of local models may be slightly less sophisticated than cloud-based solutions like Claude Opus, they are sufficient for most development tasks and offer a free alternative.

The project's leaked code is available at https://github.com/instructkr/claw-code.