I think there's some mental inertia around what a computer is and what it's worth. This thing can build custom software for you, mostly autonomously. It can monitor things happening on the internet that are relevant to you, in a holistic and flexible way. We have one crawling the web for local events we'll like, and it judges them based on what it knows about us, and it tells us about the best matches every weekend, which has yielded some awesome outings we wouldn't have known about. It reads the literature on a subject in seconds and uses it as context to help in decision support. It's not the same value proposition as a computer 3 years ago, where most people are mentally anchored on what a computer should cost. Having it at home means that you can use it as a personal agent that always puts your interests first, regardless of what ad model the commercial providers decide to put in, and you can stash in it your medical data, what you buy, what you make, your worries, hopes, and dreams, without worrying about that being used as training data, or worse, something to exploit you commercially. I think it'll become considered totally reasonable to consider spending the cost of a small car on a computer, for many families.

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.

Remember core customers of Apple studio type products is content creation/video editing, etc.

AI based tools are very useful here - thinks like object removable or cleanup etc, not just AI generation.

For example Apple mentioned performance increases for https://learn.foundry.com/nuke/content/reference_guide/air_n...

If I can get Sol level capabilities on a $20k machine, then it is well worth it for my employer to buy me that machine for work as a workstation. When you start paying in tokens vs subscription costs due to enterprise agreements, you really start to see how much cash utilizing frontier models at the frontier costs (and I'm efficiently using luna and other models where possible!)

                       Workstation   1 Sol Pro   2 Sol Pro

  Monthly cost            $700          $200        $400

  Raw capacity (hrs)      720           120         240

  Usable capacity (hrs)   100-130       120         240

  Concurrent sessions     1             3-5         6-10

  $ per usable hour       ~$6.00        $1.67       $1.67

  Usable hours per $700   ~115          ~420        ~420

  DeepSeek V4 Pro  @ $0.87/M   $50
  Kimi K2.6        @ $4.00/M   $232
  GLM-5.3          @ $4.40/M   $255
  Kimi K3          @ $15.00/M  $870  (does not fit on the box)

I think "ultra rich enthusiast" is in the right ballpark. There are people betting on being able to create their own revenue generating products and services with their own local hardware and very little operating costs. That may or may not make sense as a business idea. But people with wealth and risk appetite trying a new kind of business model and cost structure has a strong tradition.

Put another way: If $25k is the full extent of the start up capital costs, and operating costs are very low, that is a much cheaper business to start than most! The question is whether this is actually a useful model for a revenue generating business. I think that remains to be seen.

My guess is that there will be a few hits (which we'll hear a lot about - especially when someone actually pulls off "the first single-person unicorn", which I do suspect will happen someday) and a huuuge number of misses, which we won't hear much about.

Enthusiasts buying these for fun are not the target market. These aren’t big sellers to begin with but a lot of the sales are going to companies where people have budgets for gear like this and can make a business case for it.

This is, sadly, probably a foreign concept to a lot of people who have only worked at companies where hardware purchases are viewed as something to minimize and everyone is stuck with the same low spec laptops that the finance department picked out. At companies where someone might have a legitimate use for a $20K machine, their fully loaded costs (not their salary) are $300K or more, and other teams like sales are spending thousands of dollars per week on things like travel and hotels for their job, spending $20K on a computer that’s going to last several years is not a hard choice.

Other than the local AI crowd which is much recent it is professionals using Final Cut Pro for video editing, Logic Pro as a DAW and music production, Video transcoding, Photoshop and other tasks for high performance computing that don't need Laptops but want above 128GB of ram and prefer a Mac. Then there is the obvious group of developers that are making Apps for all of their products. Also, these are great for the workplace. AI is much more recent thing that Apple products were used for.

If Apple didn't sold these things they wouldn't make them but, also the level of marketing that Apple is talking about for AI is basically the new group they need to capture because the ones I just listed are already buying Macs and or easily to motivate with the other obvious CPU / GPU performance upgrades for code compilation, faster memory and video transcoding.

For some , the idea that some proprietary information could potentially leak is enough to justify any price.

Anyone dealing with sensitive or regulated data can get started instantly with local models where they may need time consuming process or complexities to send sensitive data outside.

You can connect up to 4 of them via RDMA so 2TB total RAM.

Its cheaper than Nvidia AI hardware.

If you want to run reasonably big, local AI models, what are your alternatives?

That may not be many people, but there certainly will be some people who want to do that, and are willing to pay big bucks to do so.

The competition is a custom multi-GPU NVIDIA RTX pro desktop, which go for much much more. $20k is cheap for 512GB addressable memory. The old mac pro could easily be configured to cost that much.

I know people who would get it for local LLMs for use in their company.

this comment has always existed behind every apple release, most especially anything vaguely pro-ish.

to answer your question : looking at the aftermarket availability of Apple's prior best and brightest : practically no one buys them.

"people here buy them" , well, 'here' is one of the most affluent groups of people in the world.

They're available as movie and television set pieces (undoubtedly disappearing into the home of someone close to the staff post-production), and for administrative/boss types that can slip the cost into a ledger somewhere that few will ever see.

It has been a hobby of mine every few years to check out the apple site and see how big I can option a machine. My record was when I was in high school years ago and was able to option some pro studio-ish apple desktop thing to like 61,000 usd out the door.

I realize it's not a 512, but for context on why I ordered a 96GB. $95/month after a trade in. I'll use it for a long term project where I'm building a national sized dataset/processing video transcripts with a rubric (of churches/sermon health). I'm willing to trade SOTA models for local ones for cost of regenerating/model consistency/ethical reasons.

I'll find other ways to use the power though, opencode or maybe start working on more video projects.

My friend plans to get the 512GiB M5 Ultra ASAP. He makes money by selling synthetic data and training models for companies in San Francisco and it's the cheapest way to be able to do that on your own local hardware. It's also a bit irrational as he could save money by just renting, but I get the appeal of owning something outright.

A number of people in these comments, it would seem.

I always just assume that super expensive computers are like hot rods and an expensive hobby.

Local AI is the future, and a lot of people want the first mover advantage or to toy around with it. I know a guy with a small rack of Nvidia Spark machines that he uses for that purpose; it's as much as a decent used car.

you can run open source models in the privacy of your own home :)

Twitter users.

John Siracusa, for sure. He's not getting an EV. He's getting this.

it's for me

Companies used to have local server rooms in their office, like mini centers, and buy all the equipment end to end.

It’s when self hosting and local hosting was the norm, and why it’s also starting to come back.

There will be workloads that can never touch a public cloud, and for it solutions like this are an option.