From homelab and edge AI to local LLMs, Turing Pi handles it all. Datacenter-level compute in a desktop design. Join the community https://xitter.cf/t.co/Siv6YvvCYO

United States
Joined June 2019
One board. Four slots. Pick a chip for each job. >RK1 for k3s and databases >Jetson Orin NX for vision and local LLMs >CM4 for the small stuff that just has to stay up Mix them in any combination on a Turing Pi 2.5. What goes in your four slots?
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Private by default. No settings page required.
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NVIDIA's new Nemotron model is the brain of this robot, running on a Jetson Orin Nano 8GB. The model needs only 4.2 GB of memory and does 15.5 tokens a second. On a Turing Pi 2.5, that's just one slot.
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Things your homelab will never do: >raise the price >deprecate your plan >sunset the feature you rely on >update the terms of service >show you ads Buy it once. It's yours.
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If you self-host Nextcloud, WordPress or anything else on PHP, update tonight. Two flaws let attackers run code on your server without logging in. Attacks have already started. Fixed in PHP 8.5.12, 8.4.27, 8.3.36 and 8.2.35. There's no workaround.
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Things that shouldn't live in someone else's cloud: >your camera footage >your voice commands >your family photos >your passwords 4 nodes. One board. Your house.
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Your security camera shouldn't come with a subscription to your own footage. Run AI-powered object detection locally on a Jetson module inside Turing Pi 2.5. No cloud required for detection. No monthly AI inference fees. Just your cameras, your hardware, and your data. And that's only one of four compute slots.
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Anthropic ran a 26B model on 15 cheap TV boxes >paper: "AI models may be capable of self-replicating without access to a datacenter" >15 off-brand Android TV boxes, about $55 each >4GB of RAM per box >Gemma4-26B split by layers across all 15 >it worked >0.39 tokens per second >why so slow? only one box works at a time >the other 14 wait Homelab lesson: splitting a model across weak nodes doesn't add up their speed. Fit it in one node's memory and use the rest of the cluster for everything else. anthropic.com/research/self-…
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Paying $15/month to host an app? Another $15 for your database? Another $15 for a side project? Those subscriptions add up. With Turing Pi 2.5, you can run up to 4 compute nodes on one board. Host your apps, databases, containers, and local AI workloads on hardware you control. No per-app cloud hosting bills for what you self-host. Just your hardware, power, and internet. Stop renting compute. Start owning it. Build your own cluster → turingpi.com
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The quietest data center you'll ever own fits next to your coffee.
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Why pay for four virtual servers when you can own four real ones?
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