Also, a lot of companies are looking at how to run capable models locally to cut some of their (massive) cloud AI bills. An easy answer is worth a lot to them.
Also, a lot of companies are looking at how to run capable models locally to cut some of their (massive) cloud AI bills. An easy answer is worth a lot to them.
What makes this expensive & sell well is it's not very fungible at the moment. Where else are you going to get 512 GB of high speed memory with a well supported accelerator attached that you can throw in the corner of anyone's home and not really have them notice? There are plenty of lesser options, plenty of noiser/power hungry options, plenty of harder to support options, but not really something in direct competition at the moment. Even the next rounds of the integrated AMD/Nvidia solutions are only targeting 196 GB of much slower memory and compute.
Closest competition I see right now are stacks of 2-4 connected DGX Sparks, similar lowish speed high mem, and about the same cost/gig.
For me personally, not quite that valuable yet, but I think it's getting there quickly. Deepseek V4 Flash massively increased the value of local AI to me, to the point where it's displaced most of my Claude Code usage, its upcoming vision enabled version should bump it further, and it's only going to get better from there.
It's a lot faster, but a lot of it is also feeling free to discuss things I wouldn't be comfortable sending to Claude, with the idea that that info is now theirs in perpetuity. I got my genome fully sequenced recently (it's cheap now!), and I get a battery of blood tests every year. Wouldn't do processing on any of that with Claude, but local AI? Totally great.
And if I was running a company with a large cloud AI bill, I'd probably buy a wheelbarrow full of these macs. Cheaper, but also a more solid/predictable base to build on.