EXO is a free, open-source tool that clusters Apple Silicon Macs into one giant AI brain. Because Macs use unified memory, pooling them gives you one massive memory bank — big enough to run trillion-parameter frontier models that normally live in a data center. No cloud, no API bills, no one watching your tokens. Here's the full setup.
EXO pools multiple Apple Silicon Macs over your network into a single memory bank. Unified memory means two M2 Maxes (96 GB each) become one 192 GB machine — enough for models that normally need a data center.
Pay once for the hardware, then zero per-token fees. Ever. No cloud bill, no usage meter, no API key to manage.
Nothing leaves your machine. Point it at private docs and let it run all night — no internet round-trip, nobody watching your tokens.
Not toy models. DeepSeek V3 (671B), Llama 3.3 (70B), Qwen 2.5 (72B), Mistral Large (123B) — running locally on your own silicon.
Rule of thumb: more RAM = bigger models. A single M2 Max (96 GB) runs 70B solo; pool two Macs and you're at 192 GB.
M1, M2, M3, or M4 — running macOS 13 Ventura or later. Intel Macs won't work.
The floor for useful models. More memory (or more Macs pooled) unlocks the bigger ones.
Python 3.12 or higher; Homebrew is optional but makes the install one command.
Good Wi-Fi works; wired ethernet between Macs is dramatically faster for splitting a model.
Press Cmd + Space, type Terminal, hit Enter.
Run brew install [email protected], then verify with python3 --version — it should show 3.12 or higher.
One command: pip install exo-explore. It downloads everything automatically — takes 1–3 minutes.
Run exo. It starts up, prints your local IP, and waits for peers.
Install EXO the same way on each extra Mac and run exo. They discover each other automatically on the same network — no config needed.
In a new Terminal window: exo run llama-3.2-3b (or any model from the table above). The first run downloads the weights.
Once the model loads, EXO opens a local web UI at http://localhost:52415. Open it in your browser — private AI, no internet, no API key.
# 1. install Python 3.12 if you don't have it brew install [email protected] python3 --version # should show 3.12+ # 2. install EXO (downloads everything, ~1-3 min) pip install exo-explore # 3. start EXO — run this on each Mac exo # 4. download + run a model (any from the table) exo run llama-3.2-3b # 5. open the local web UI in your browser # http://localhost:52415
A single M2 Max (96 GB) runs 70B solo. Pool two and you hit 192 GB — into trillion-parameter territory.
A wired connection between Macs dramatically speeds up the model-splitting that makes clustering work.
Nothing leaves your machine. Point it at sensitive docs and run wild — no data ever leaves the cluster.
Pay once for the hardware. Zero per-token fees, forever. The opposite of a cloud API bill.
The complete walkthrough — what EXO is, the models you can run, the requirements, all seven install steps, and the pro tips. Read inline or download.