Date: 01/07/2026
Local AI Supercomputer: Run Massive Models on Your Home Network with Exo
Turn everyday devices like Macs, Linux machines, and even Raspberry Pis into a powerful, distributed AI setup—no cloud dependency, no data risks, and zero GPU costs.
In this video, dive into Exo, the open-source tool enabling huge models (up to 671B parameters) across your local network. Covers setup, benchmarks, RDMA over Thunderbolt 5 for ultra-low latency, and mixing hardware for real-world clusters.
Key Highlights:
- What is Exo? Distributed inference on consumer hardware.
- Milestones: Llama support, M4 Mac integration, Pi compatibility.
- Benchmarks: 235B–671B models running smoothly at home.
- Pros & Cons: Game-changing for privacy, but not flawless.
🔗 Links:
- Exo GitHub: https://github.com/exo-explore/exo
- Official Site: https://exolabs.net/
- Jeff Geerling’s Deep Dive: https://www.jeffgeerling.com/blog/2025/15-tb-vram-on-mac-studio-rdma-over-thunderbolt-5
About Better Stack: Building better observability tools—check their stack (https://betterstack.com/), tutorials (https://betterstack.com/community/), and GitHub (https://github.com/BetterStackHQ).
Follow Them:
- Twitter: https://twitter.com/betterstackhq
- Instagram: https://www.instagram.com/betterstackhq/
- TikTok: https://www.tiktok.com/@betterstack
- LinkedIn: https://www.linkedin.com/company/betterstack
Chapters:
- 0:00 – Exo Explained: Home AI Power
- 0:33 – Distributed AI Basics
- 1:00 – How It Works
- 1:55 – Key Milestones
- 2:05 – Setup Guide
- 2:50 – Thunderbolt 5 Magic (99% Latency Cut)
- 3:11 – Benchmarks on Big Models
- 3:31 – Mixed Hardware Setup
- 3:58 – Limitations
Perfect for no-code/low-code AI enthusiasts wanting privacy-first computing! 🚀