So they have basically reused the same hardware as in the DGX Spark (GB10)...
That chip isn't great for LLM inference actually.
https://www.techpowerup.com/gpu-specs/gb10.c4342 https://www.nvidia.com/en-us/products/rtx-spark/
https://www.techpowerup.com/gpu-specs/gb10.c4342 https://www.nvidia.com/en-us/products/rtx-spark/
Basically the same tradeoff as macmini with unified memory.
I think its gonna be another failure as we are used to see with the PC market these days.
Why do I have the feeling it's been intentionally made to be bad in order to get you on to their most pensive datacenter gear.
At this point, your cost-efficient options include used 3090s, "frankenrigs" using recycled data center cards, and a handful of "workstation" class cards, where the originally high margins and the long enterprise purchasing cycles have kept prices from going up too fast.
In contrast, a lot of these "personal" AI systems are basically a GPU-like core wired to larger amounts of slow RAM. Which is still semi-affordable. Generally speaking, they make for OK chatbots but extremely slow coding agents. Whereas you can run a modestly useful coding agent at reasonable speed on a 3090.
So yeah, a lot of these systems are bit scammy. But not because it's a secret conspiracy to protect data center cards. Rather, there simply isn't enough fast RAM in the entire world. So they'll flog you disappointly slow RAM instead.
TL;dr: Might be useful for some use cases, but benchmark very carefully.