Run Claude Code Locally
Kill the $300 AI Bill with Free, Private Coding Agents on Ollama and Open Models
Stop renting your coding agent. Wire the real Claude Code, Codex, and OpenCode to a model on your own machine: no $300 bill, no rate limits, nothing leaving your laptop, with an honest map of where local still loses to cloud.
You hit the rate limit mid-refactor, then the monthly bill lands. Again. Meanwhile other developers run the same coding agents locally for the price of electricity, with nothing leaving the laptop. This book wires the real Claude Code, Codex, and OpenCode to a model running on your own machine: a local agent editing real code in 15 minutes, Claude Code running fully local through a LiteLLM proxy you control, a model-picker tuned to your hardware, a break-even calculator with your name on it, and a troubleshooting runbook for the failure modes that make people quit on day one. It’s an honest map of where local wins and where you still reach for cloud, not another “local AI is magic” pamphlet. 182 pages of real wiring, real model picks, and the truth about both sides.
What You'll Build
Why local coding works now, the three reasons to switch, and the honest catch nobody mentions.
The agent / model / API-shape mental model that makes every later config step obvious.
A green/amber decision matrix so you know, before you start, whether local will nail a task or choke.
Install, pull a model, and watch an agent edit real code offline, no proxy required.
Stand up the LiteLLM proxy and config.yaml that make Claude Code run 100% local, verified.
Choose your model by tool-call reliability and a benchmark you run yourself, not a leaderboard.
Pick your agent and runtime (Ollama, llama.cpp, vLLM, MLX) on purpose, with the tradeoffs on the table.
Three knobs (model size, quantization, context) that turn a 52-second tool call into a 4-second one.
Fill in a calculator with your real usage and walk out with your personal break-even month.
Prove your code never leaves the machine, and run fully offline on a plane or in an air-gapped facility.
A five-symptom runbook for every way local breaks, with the fix for each.
Lock every choice into one safe, sandboxed stack and run a real day on it.
Free Articles from this Book
Local vs Cloud AI Coding: When Local Loses
Are local coding models good enough? For most of your day, yes. The honest map of where local wins, where it loses, and how to decide before you fire a task.
from: Run Claude Code Locally
How to Pick a Local Model for Coding
The best local LLM for coding isn't the leaderboard winner. Pick by tool-call reliability and speed, with a model table and a benchmark you run yourself.
from: Run Claude Code Locally
Run a Local AI Coding Agent Free in 15 Minutes
Build a local AI coding agent on Ollama that edits real code offline. Install, pull qwen2.5-coder, run Codex, ship your first edit with the Wi-Fi off.
from: Run Claude Code Locally
Run Claude Code Locally with Ollama
Point the real Claude Code CLI at a local Ollama model through a LiteLLM proxy. The exact env vars, the config.yaml, and the version you must never install.
from: Run Claude Code Locally
Why Your Local AI Coding Agent Is Slow
Why is Ollama slow for coding? Almost never your hardware. Fix the 52-second tool call with three knobs: model size, quantization, and context length.
from: Run Claude Code Locally