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SilverSlash 6 hours ago

The 512GB Ultra is amazing, sure. But who is it for exactly? VC funded big spender founders? In that case why would they need local AI? The ultra rich enthusiast? But there can't be too many of those. So who actually buys these?

ericd 6 hours ago | parent | next [-]

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.

zamadatix 3 hours ago | parent | next [-]

By this kind of logic we'd paying something like ~$10,000/month for our internet connections. The perceived value needs to exceed the cost but that does not make it the only factor to consider price with.

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.

ericd 2 hours ago | parent [-]

I think the difference besides the supply crunch there is that everyone connected gets the ~same internet, just faster or slower. Quantitative, not qualitative difference. On the other hand, a computer that can run Gemma 4 8B versus one that can run DeepSeek Flash are different enough experiences that I'd say they're effectively a difference in kind. It's been a bit since we had such serious stratification in outright capability in computing, rather than just how long it takes to get something done, or how many of something it can serve at once. In the early 90s, I think there were a lot more of those "this computer can do this thing, this one just can't" scenarios.

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.

Jesus_piece 2 hours ago | parent | prev | next [-]

Could you share what you did to find events to do? That sounds really cool

ericd 2 hours ago | parent [-]

Sure, it’s pretty dumb/naive implementation, would need to be a lot more efficient to scale. Basically had Claude write polite/low touch dumb crawlers for a bunch of local sites (library, local events spaces, luma, theaters, maker spaces) and whip up a little frontend to let our family and friends manage a little text description of what their family members like, constraints, that sort of thing. Once a week, the crawlers look for new events, add to a db, and then run through the list and ask our local LLM to grade each event, given the text description and constraints. Take the top 20ish for the following two weekends and email out. It’s been super helpful, lowers the activation energy to go to more local events.

saturn8601 an hour ago | parent [-]

Do you really need a powerful Mac to do this? Wouldnt this work on a base model or even an old Windows computer?

conmod278 2 hours ago | parent | prev | next [-]

Nvidia is definitely working on a AI Rack machine fully built for on-prem uses for companies.

hectdev 5 hours ago | parent | prev | next [-]

I like this train of thought. The inverse is saying that the cost of this computer is the value we give away to AI companies by doing compute on their servers with our data. And to take it another way, is the value to you, the cost of a small used car?

ericd 5 hours ago | parent [-]

> And to take it another way, is the value to you, the cost of a small used car?

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.

jeffreygoesto 6 hours ago | parent | prev | next [-]

[flagged]

brookst 4 hours ago | parent [-]

Hey, a high school jock from 1982 wandered in to the computer lab...

iammrpayments 5 hours ago | parent | prev [-]

[flagged]

evanjrowley 3 hours ago | parent | next [-]

Members of my C-suite are doing this today on a raspberry pi, so the promise is not empty. Key difference is they aren't using local AI to do it.

For the M5 Ultra, I suspect it would be valuable for someone who wants to achieve all the above and more, but with local AI due to data privacy concerns, and also not regulated data that comes with lots of other requirements solved by more traditional approaches.

Three possibilities:

1. The type of person who deals with lots of intellectual property using expensive Mac-only desktop applications that aren't meant for servers, whose mind has formed positive associations with the term "Apple Intelligence", whose values overlap with Apple's lawyer's values, who actually stands to profit from having a Mac that's more powerful than anyone else's Mac, whose long-term goals are not impacted by planned obsolecense on a piece of computer hardware costing over $25k ($50k after 1TB SSD add-on).

2. Trust fund beneficiary who wants to show off, LARP as #1, prime target for Apple's marketing.

3. 2026 kit for billionare-class iPad babies. All brain rot content is 100% local AI-generated. Never have to speak to your children again. A true "we have dead internet theory at home" machine.

ericd 3 hours ago | parent [-]

If you actually want to learn, highly recommend a visit to https://old.reddit.com/r/LocalLLaMA/. People there are running stacks of 2-4x DGX Sparks to get to similar levels of memory, at similar cost.

ericd 5 hours ago | parent | prev | next [-]

Weird swipe, I'm not trying to sell it to you, this is just where I see it going, and why these things are going to sell (and why 512 gig M3 Ultra Mac Studios have skyrocketed in demand/price). It's not been an empty promise, in that it's been providing lots of very concrete value to us already.

marknutter 4 hours ago | parent | prev [-]

What exactly is empty about any of what he wrote?

DrScientist 5 hours ago | parent | prev | next [-]

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...

sanderjd 4 hours ago | parent | prev | next [-]

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.

Aurornis 3 hours ago | parent | prev | next [-]

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.

maherbeg 5 hours ago | parent | prev | next [-]

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!)

ericd 5 hours ago | parent | next [-]

Yeah, I'm not sure people realize how expensive ZDR/Zero Data Retention is, and how important it is to a lot of businesses, this kind of thing starts looking really cheap really fast if it's a reasonable substitute.

searealist an hour ago | parent | prev | next [-]

Don't forget about electricity costs, esp in California. Even with free hardware you may be better off using APIs.

ltbarcly3 3 hours ago | parent | prev [-]

I don't think this is accurate.

Even using multiple windows in parallel for as many as 5-10 hours per day, I find that I am not fully using my claude max (20x) and chatgpt pro (20x) accounts. I can for sure use up the claude max account, but chatgpt either gives me a free reset before I run out of tokens or I just fail to use the full quota. The quota for Sol seems like 10x that of Claude Opus at the same level, and forget Fable, you can use a 5 hour quota in 20 minutes.

But lets do the math:

Lets say a 20k workstation can run 1 inference at a time at the same speed you get with Sol hosted by openai (big assumption) and run an equally capable model (big assumption).

Each month this gives you about 100-170 inference hours on a Sol 20x Pro account, and 720 hours (if you utilize 24/7) on the workstation.

Assuming a 36 month amortization before the workstation has to be replaced due to no longer being able to run frontier models or is too inefficient due to electrical costs or what have you:

The monthly workstation cost is about $550 capex and $150 electricity -> $700/month

You would need about 6 Pro accounts to reach that capacity, which would cost you $1200 a month.

But this fails because:

- You most likely can't utilize the workstation 24/7. Your work hours will be concentrated into 6-10 hours per day.

- During work hours you are capable of utilizing more than 1 concurrent session. 6 Sol accounts would support as many as 20-30 during working hours, not all the time but if you could burst to that many (don't forget sub-agents and agent directed parallel agent workloads).

- In 1 year the cost of Sol level models is likely to cost a fraction of what it does now.

this leads to:

                       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
hellohello2 2 hours ago | parent | next [-]

"You most likely can't utilize the workstation 24/7. Your work hours will be concentrated into 6-10 hours per day."

I have agents running 24/7 doing research, in fact I would argue this how they will be used for most programming tasks in the near future. For chatting, I agree local inference makes no sense. But for tasks that run continually, I'm not so sure. Personal computers took a while, local inference will too, but I think it will happen.

slashdave 39 minutes ago | parent | prev | next [-]

Some people neglect to factor in electricity costs. Some homes have very expensive service.

timfsu 3 hours ago | parent | prev | next [-]

Subscriptions are, and will likely remain, the best deal in town. Unfortunately, larger companies aren't able to do that. When your monthly token costs are in the $5-10k range, the local inference starts to look a lot more attractive

ltbarcly3 2 hours ago | parent [-]

In the case where you pay for tokens without a subscription, the analysis is still very much not in favor of buying hardware.

The assumption previously used was that you can run a Sol level model on an M6 or whatever hardware $20k gives you. That is not true, it was an assumption made to show that even giving your own hardware every reasonable advantage it still loses.

Lets compare buying tokens of the best model you might run on your own hardware (still being unrealistic in favor of your own hardware) vs that same class of model on the market. I think one of the best models you might be able to run is GLM 5.4, but lets just look at chinese models generally:

$20k workstation, best case: $15k M5 Ultra 512GB, 36-month amortization, ~$440/mo. Runs a GLM-5.3-class model at ~30 tok/s. Saturated 24/7 it produces roughly 58M output tokens/month.

Buying those tokens:

  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)

The economics can never work in your favor for buying your own hardware here, unless you can utilize it or sell excess capacity and you have access to nearly free electricity. The reason is someone else can buy the same hardware at scale (or realistically more efficient hardware), park it somewhere with very cheap electricity, and sell tokens. They can get very high utilization that you are not likely to get.

And keep in mind I am giving 'your own hardware' no overhead or maintenance cost, despite your condition that it's in a large corporate environment. In reality corporate IT would make it almost impossible to set up and your would need huge lead times to buy the hardware and get it installed.

maherbeg 2 hours ago | parent [-]

Thank you for being explicit with the math!

So yes, at that speed for sure. But if the speed goes up? or the ability to batch at the same speed goes up? The economics start to shift. The gap is much closer, and you'd end up with a box you can still use or sell later.

Subscription pricing is still the best though!

mathisfun123 2 hours ago | parent | prev [-]

> - You most likely can't utilize the workstation 24/7. Your work hours will be concentrated into 6-10 hours per day.

isn't the whole point of all this ..... agents? isn't that what literally everyone is always clammering about in these threads? in which case the workstation is useful 720 hours out of 720 hours.

zitterbewegung 5 hours ago | parent | prev | next [-]

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.

tencentshill 6 hours ago | parent | prev | next [-]

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.

2 hours ago | parent | prev | next [-]
[deleted]
LeBit 6 hours ago | parent | prev | next [-]

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

SXX 6 hours ago | parent | prev | next [-]

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

Its cheaper than Nvidia AI hardware.

serf 6 hours ago | parent [-]

also way slower if we're just going against 'nvidia hardware'.

SXX 3 hours ago | parent [-]

Even at high announced pricing 4 of them still much more accessible than any Nvidia solution with same amount of VRAM,

skinfaxi 6 hours ago | parent | prev | next [-]

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

usrnm 6 hours ago | parent [-]

So, rich enthusiasts it is, then

fearmerchant 5 hours ago | parent [-]

I'm going to buy one to watch youtube videos and surf social media.

eigenspace 5 hours ago | parent | prev | next [-]

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.

mschuetz 5 hours ago | parent | prev | next [-]

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

c0rruptbytes 30 minutes ago | parent | prev | next [-]

it's for me

serf 6 hours ago | parent | prev | next [-]

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.

avalys 6 hours ago | parent [-]

Movie set pieces, as a motivation for Apple making these high-end configs available? That makes no sense.

For one thing, you can’t tell from a movie what the specs are. A $999 Mac Studio looks exactly the same as a $20,000 one.

For another, Apple updates the industrial design on their products so rarely, a 6-year-old Mac, iMac or MacBook also looks nearly indistinguishable from a brand-new one.

michaelbuckbee 2 hours ago | parent [-]

Movie production (editors, sound design, and a portion of fx work).

Mistletoe 2 hours ago | parent | prev | next [-]

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

mikert89 5 hours ago | parent | prev | next [-]

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

lenerdenator 6 hours ago | parent | prev | next [-]

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.

brianwawok 5 hours ago | parent | next [-]

But is it? If it’s cheap enough latency doesn’t matter. Unlike say cloud gaming, where latency does matter. I’ll take my games local and my text bots cloud

lenerdenator an hour ago | parent [-]

Of course. People are valuing privacy now, and it's almost inevitable that humans will seek to have more agency over a social contact, even if it's an artificial one.

brianwawok 15 minutes ago | parent [-]

History has shown me people value convenience and cheapness and maybe safety. Privacy is far down the list for 99% of the world

intrasight 5 hours ago | parent | prev [-]

It's as much as a new car

try-working 6 hours ago | parent | prev | next [-]

Twitter users.

j45 6 hours ago | parent | prev [-]

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.