Hi there, welcome back.

One of the most talked-about developer setups right now is also completely free. Here's what it is, how it works and how you can get it running today.

If you have been watching your API bill grow every time you use Claude Code, this one is worth your time.

A recent update from Ollama (version 0.14.0, released January 16, 2026) added full compatibility with the Anthropic Messages API. That single change opened a door most developers did not expect: you can now point Claude Code at a local model running on your own machine, skip the API entirely, and pay nothing.​

Ollama is a tool that lets you run open-source language models locally. It handles the heavy lifting: model downloads, memory management, GPU acceleration. The Anthropic API compatibility layer is the new piece that makes the Claude Code connection possible.

What Ollama supports through this bridge includes streaming responses, tool calling, system prompts, image input and extended thinking. That covers most of what Claude Code actually needs to function properly.​

Step 1: Install Ollama

Download and install Ollama from ollama.com. It runs on Mac, Windows, and Linux.​

Step 2: Pull a Local Coding Model

Open your terminal and run one of these based on your machine's RAM:

Qwen 2.5 Coder 32B scores the highest on coding benchmarks among local models at 49% HumanEval, making it the top pick if your hardware can handle it. DeepSeek Coder V2 16B is a great middle ground, delivering around 95% of that performance at half the RAM requirement.​

Step 3: Install Claude Code

Step 4: Connect Claude Code to Ollama

This is the key step. Set two environment variables to redirect Claude Code away from Anthropic's servers and toward your local Ollama instance:​

Step 5: Launch It

Navigate to your project folder in the terminal and run:

claude --model qwen2.5-coder:7b --dangerously-skip-permissions

Note: The --dangerously-skip-permissions flag just turns off the "are you sure?" pop-ups inside Claude Code so it can work without interrupting you. It does not affect your system security in any way.

That's it. You now have a fully local coding agent with file access, terminal commands and multi-step task handling.​

This setup is genuinely useful, but it is worth being honest about what you are trading off.​

The local models are strong for day-to-day tasks: writing functions, refactoring code, explaining errors, generating boilerplate. Where they fall short is in reasoning through genuinely complex architecture decisions or handling very long context windows.​

Think of this as your free, always-available coding companion for everyday work, with cloud Claude as the option you reach for on harder problems.

If you have 16GB of RAM and want the most reliable experience right now, pull deepseek-coder-v2:16b. It runs on most modern laptops, handles the majority of coding tasks cleanly, and gives you a real sense of what this setup can do before you commit to pulling a larger model.​

For anyone working on a codebase where privacy matters, like a client project, an internal tool, or anything you would rather keep off third-party servers, this setup makes a lot of sense even beyond the cost angle.

Local tooling has been improving steadily, and this particular combination is genuinely worth trying. The setup takes ten minutes, costs nothing, and gives you a working coding agent that runs entirely on your own hardware.

What you do with it from there is up to you.

In other words, treat this setup the same way you treat your editor and terminal: keep your system secure and it will quietly do its job in the background.

Until next time, keep building.

Stay sharp,
Better Every Day