NVIDIA's numbers for Nemotron 3.5 Bolt E4B (Q4_K_M, llama.cpp, 3K prompt): research.nvidia.com/labs/nem…
For anyone asking what's in the photo: turingpi.com/product/turing-…
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.
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-…
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














