Run Claude Code on a Fully Local Model — in 5 Minutes

Point Anthropic's Claude Code at a model running on your own Mac. No cloud, no per-token bill, and your code never leaves the machine. It's two environment variables — here's the whole thing.

Claude Code is a great agent. But every keystroke, every file it reads, every tool call goes to the cloud — and gets billed per token. For a lot of work — refactors, codebase Q&A, editing files you'd rather not upload — you don't need a frontier model in a datacenter. You need a capable model on your desk.

Here's why the swap is worth it:

• Your code stays on the Mac. Nothing is uploaded — works on a plane, behind an air-gap, or on a repo you're not allowed to send anywhere.
• No meter running. Once the model is on disk, an all-day agent session costs exactly nothing.
• It actually works — not a hack. rapid-mlx speaks Claude Code's native wire (/v1/messages) and ships guaranteed-parseable tool calling, so the agent's edits and tool calls land instead of flailing. More on that below.

The whole setup is about five minutes, most of which is a model download. You'll need an Apple Silicon Mac (M1 or newer).

Before you start

You need Claude Code itself. If you don't have the CLI yet:

npm install -g @anthropic-ai/claude-code

1 · Install rapid-mlx

rapid-mlx is a local, OpenAI- and Anthropic-compatible inference server for Apple Silicon. It's in Homebrew core:

brew install rapid-mlx

Prefer not to use Homebrew? curl -fsSL https://rapidmlx.com/install.sh | bash does the same — no sudo, self-contained.

2 · Serve a model that fits your Mac

Pick a model sized to your RAM and start the server. A solid default for coding is Qwen 3.6:

rapid-mlx serve qwen3.6-35b-4bit

First run downloads the weights (cached after that). The server comes up at http://localhost:8000 with both OpenAI and Anthropic routes.

3 · Point Claude Code at it

Claude Code honors the ANTHROPIC_BASE_URL environment variable. Set it to your local server and launch — that's the whole integration:

export ANTHROPIC_BASE_URL=http://localhost:8000
export ANTHROPIC_API_KEY=not-needed
claude

4 · Do something real

You're now running a fully local agent. Point it at a repo and give it a task:

# inside any project
claude
> add a --dry-run flag to scripts/deploy.py and update the README

It reads your files, plans, and edits — all on your machine. Pull the network cable; it keeps working.

Why it just works (and where it doesn't)

Two things make this a real integration rather than a duct-tape proxy:

• Native Anthropic wire. Claude Code speaks /v1/messages, not OpenAI's format. rapid-mlx serves that as a first-class route, so it's an env-var flip — no shim, no translation layer to break.
• Guaranteed-parseable tool calls. Tool-call output is constrained by a grammar at generation time, so the model can't emit a malformed call. That's the difference between an agent that edits your files and one that stalls on a broken tool block. (Verified on rapid-mlx 0.10.15: a bare serve plus an Anthropic /v1/messages request with a tool returns a proper tool_use block.)

Honest expectations. A 35B model on your Mac is not Claude Opus, and pretending otherwise helps no one. Where local shines: private and offline work, codebase Q&A, straightforward edits and refactors, and never watching a bill. Where the cloud still wins: the hardest multi-step reasoning and the largest context.

The good news — you don't have to choose. Flip the two environment variables off and Claude Code is back on the cloud model. Local for the 80%, cloud for the hard 20%.

Where to go next

• Full Claude Code guide — SDK snippet, tool schemas, and every gotcha.
• Integration matrix — 11 agents across the four Tier-1 families, tested.
• Install rapid-mlx — Homebrew or one curl. Apache 2.0.
• Browse models — pick one that fits your RAM.

Using Cursor, Codex CLI, or Aider instead? Same idea — each has a one-page guide in the docs.