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pen2l 19 hours ago [-]
Apple, to me, is the winner in the end of this AI chapter.
Distillation works: we can get models leaner, have better performance with lesser and lesser parameters, more efficient, running locally. Apple gets this and we'll see the result with M7 Max/ultra chips and I reckon this will be one of the titular apps when M7 line of chips are introduced.
I guess it explains the haste Anthropic and OpenAI are in to IPO, cash out and leave the the retail investor holding the bag.
aurareturn 7 hours ago [-]
Apple, to me, is the winner in the end of this AI chapter.
I might be one of only few people who think Apple is a loser in the AI chapter.
I don't think it shows yet but I think the dominance of the App Store will end. I think a ton of iOS apps will be replaced by ChatGPT/Claude. I think there is a big opening for a company to redesign the phone from the ground up purely around an AI assistant instead of apps.
I think AI will severely weaken iOS, App Store, and the iPhone in the next few years. It was nearly impossible to start a 3rd competitor to iOS and Android until recently because no one is going to redesign their apps for your new phone. Today, that's different. Many productivity apps are just being replaced by GenAI/ChatGPT/etc and services are making it easy for AI agents to access directly without an app.
Not to mention higher chip prices will eat into hardware margins.
I do not think local LLM inference will make up for lesser iPhone dominance.
smugglerFlynn 2 hours ago [-]
Replacing a good app is still extremely hard. Let me explain.
Commodities like todo apps and calculators rarely compete on features, they compete on product design. This includes look and feel, relation between elements, design choices on what exact common features are available.
All products are, at their essence, just a set of design decisions stitched and shipped together.
Now, making these design decisions is hard. It requires knowledge, consistency, and insights into how real people operate real products. Even as a sole user of the app you build you rarely know what you actually need.
LLMs are 'design-less' in their essence. Building your own todo app takes literal seconds and it all looks simple because LLMs will default most of these design decisions for you - until you try to use your new app daily and notice it somehow sucks. Building a good todo app or good calculator requires tweaking, publishing, polishing, and solving bugs, testing, rinse and repeat.
Another tricky side of this is that you might know logically what features you want, but you are not selecting one product over another logically. You need to try and see if that works for you, all the vibes and good parts and bad parts and design choices and colors, till you find something that "clicks" for you. Using pure Claude as a todo app only works as long as you want to have more Claude in your daily life.
In the meantime app store provides dozens of well-reviewed alternative solutions which look good and require zero maintenance.
And that's just a calculator or todo app. Non-commodity apps are even harder than that.
WarmWash 2 hours ago [-]
Design is dead (long live design)
I don't see any future where programs follow the static nature of old paradigm programming. A nice intuitive UI? What about just telling the app what I need when I need it? The gold standard of consumer UI is...another person.
If I have a team of god tier light speed SWE's at my disposal, why the fuck am I fumbling around in an actions panel? The program can just be dynamically modified in near real time to be whatever I need it to be in that moment.
If you extrapolate LLMs out to their extreme, you get a shape-shifting liquid array of bits in memory that manifest anything at the behest of a completely natural language interface.
spider-mario 1 hours ago [-]
> The gold standard of consumer UI is...another person.
Absolutely not. Constraining the set of possible actions instead of having you verbalise what you want every time is often a feature, not just a technical limitation. A camera with a shutter button is better design than having to tell the camera “please take a photo”.
At the supermarket, I personally also prefer the self-checkout machines over going to a human cashier.
WarmWash 56 minutes ago [-]
It wouldn't be just verbalizing, you could type or gesture just as well. Nor would you need to communicate each command, the machine would recognize that you want a button for your camera, the checkout would understand that you want to checkout and understand each intended action as you do so.
The UI is totally fluid at all times, because an "intelligence" is actively manifesting it at all times. Nothing needs to be hard coded.
spider-mario 48 minutes ago [-]
But I don’t necessarily want to have to continuously adapt to such a fluid UI. Unless you are proposing that the UI should effectively just read my mind, but until it literally does that to perfection, that will always come with the overhead of wondering whether it has the right understanding of what you want.
WarmWash 27 minutes ago [-]
Then you can just have a static design, it's trivial and perceptively instant for the machine to generate it (or 10 of them if you want choice) and act like a "dumb computer from 20 years ago".
Hell the computer might even see your face, see your age and style, and be like "Yup, this guy definitely wants to checkout with a dumb, midi keytone 8-bit styled program"
spider-mario 21 minutes ago [-]
I feel that this kind of sidesteps the point that smugglerFlynn was making about designing those interfaces.
oinj 1 hours ago [-]
You are assuming that you'll always have the time and energy to determine what you need at the moment you need it, which doesn't really sound true.
You're also assuming that there are no negatives to saying what you want compared to just acting on things, but since the beginning of computing many people have proven this wrong time and again. I suggest you read about HCI as a research field and its history, it doesn't take much to realise how limited the average HNer's understanding of UI/UX design is, and how far current LLMs are from the skills required to be able to carefully design an app for productive human use.
alala-lala-lon 53 minutes ago [-]
[dead]
smugglerFlynn 56 minutes ago [-]
This sounds like the car industry touch screen craze all over again.
Good design rarely calls for a “you can do everything” approach. Good design is often context specific and subtly guides users to better outcomes.
Doctor appointments would absolutely suck if I had to navigate decision trees and click buttons to communicate my symptoms. Car blinkers would absolutely suck if I had to type “blink left” into a chat window before every turn.
hobo123 39 seconds ago [-]
Oh is that the new UI of Mercedes and BMW cars? Cause they always seem to have dysfunctional blinkers.
nout 14 minutes ago [-]
I rolled out my own to-do app yesterday, because I needed something fast as a companion to Obsidian, while it can do cloud syncing for me.
It works exactly the way I want and looks exactly the way I want. If there's something I want changed about it, I add it as a todo item in the very same app. This works today.
I don't think the companies have moat in experience fine tuning.
alperhalil 34 seconds ago [-]
I feel the same about this. There are many task trackers out there and most are overkill for my own projects. I don't feel like onboarding through Linear, or setting up through Trello and think about how to have the agents connect, etc, so I just found myself motivated to look for my own, local solution track and manage my projects.
I think it's better when you are at the origin, and the software branches off of your taste. For so long, we had to adapt and accept the ways of established software because it would take so long to make something of your own. Now it's both cheap and fast to iterate.
AlwaysRock 15 minutes ago [-]
A huge amount of apps I've downloaded are just to solve a problem I have for a moment. Then most of the rest are regular use apps.
I dont think llms are going to replace banking apps anytime soon. But I no longer look for an app to pull data from my Peloton app into another exercise app. LLMs can build an app or a script that will do that and I wont have to pay some annual or monthly fee. It feels like these types of apps are going to die off.
lo_zamoyski 35 minutes ago [-]
I tend to agree, on the whole. LLMs force more attention toward the purpose of an app and how best to satisfy that purpose for a given audience. (Undisciplined SWEs can forget about end users and get lost in the details of some particular piece of tech.)
However, you could expect LLMs to train on existing successful apps and hardened design patterns that compose well into good UIs. In that case, you might expect the last mile polish to be the differentiating factor. However, the more marginal this last mile becomes, the more other social, political, business, etc. forces will determine which app rises and which falls. But this has always been the case, certainly in software.
segfaultex 3 hours ago [-]
I don't see this happening for everything.
For instance; I don't think LLMs will be replacing Spotify, Facebook, Insta, or Youtube for my parents. They absolutely do not want to purely interact with a blackbox. They want to scroll through songs/shows/etc. they want to tap on it, and have the app do the thing.
Even as a SWE, I have absolutely zero desire to interact with an LLM for everything, but I'm not the litmus. I have found use with these tools for taking on some nested set of tasks, but at no point do I want to give up the app entirely.
james_marks 2 hours ago [-]
I watched someone shop on ChatGPT, and it's far from just typing into a black box. This was not a technical person, they were just using NLP to create a curated feed in real time, with links to "do the thing".
For people who like shopping (not me!), most of it is actually browsing and there is a joy in sifting through options. The OpenAI designers seem to understand this.
foldr 2 hours ago [-]
ChatGPT is indeed really good at this. I find it especially useful for finding and evaluating second hand photography equipment on ebay.
joebe89 3 hours ago [-]
I would say especially as a SWE. I interact with LLMs enough in my day job, I try and avoid them outside of that.
zarify 4 hours ago [-]
So here’s a gross generalisation: people don’t know what they want, and when they do know they can’t explain it.
I think folks who live in spec-driven worlds just don’t appreciate how poorly understood the capabilities and processes of computing and networks are, to the point where even if you gave people hallucination free LLMs you’d probably find people just frustrating themselves because they can’t figure out what they want, what it should do, and how it should be used.
Quite apart from the huge chunk of the app ecosystem that relies on common protocols, centralised services and so on.
KellyCriterion 3 hours ago [-]
> rustrating themselves because they can’t figure out what they want
I have seen this with yet "AI-unexperienced" users - for simple questions or textreformating, they are absolutely fine with the Chatbots. But thats all they can get out of it: Above that level their experience is very often frustrating due to too less understanding while having high expectancy towards the model in reverse (like "its AI so it should know...")
And this people end up then not using any of the AI tools beyond that because they do not "believe" / trust that this thingy can get work done.
aurareturn 4 hours ago [-]
people don’t know what they want, and when they do know they can’t explain it.
* Book me an uber or Waymo in 15 minutes. Which ever is cheapest.
* Based on our music discussions, make a playlist for me in Spotify. No songs older than 15 years.
* Look through my email, find all my receipts, show me a graph of my spend and categorize them.
* My business needs warehouse space. Find warehouse services within 15 miles of San Francisco. Ask them for their pricing and capacity. Here are pics of my items. Send these pics to them for quote.
* Find a hotel for me in Los Angeles on October 1st to Oct 5th. 4 starts. Max $200/night. Gym is a must. Don't care about pool. Close to airport. I have Platinum membership with Accor so try to find Accor hotels but not a must.
People do know what they want.
andsoitis 3 hours ago [-]
> * Based on our music discussions, make a playlist for me in Spotify. No songs older than 15 years.
It is easy to express yes, but is this how people think about what they want to listen to?
Someone can already do this in a chat bot, see the list of things and then find it on Spotify or whatever their favorite music service is.
What the chat bot won't know is what they have listened to, which is probably a much higher predictor of what you'd like than the discussions you've had about music. You've probably had those discussions because you are already listening to that music!
Vegenoid 2 hours ago [-]
You just explained what you want far more clearly than most people do.
cj 3 hours ago [-]
All of your examples seem to require using another company's app.
I thought the parent's point is that the App Store will loose dominance (because you won't need apps).
aurareturn 55 minutes ago [-]
That's right. I think AI agents will access services without you going through apps.
Planktonne 3 hours ago [-]
Only the fourth of those is not more easily accomplished using existing tools; the things you're describing as explainable are such because they've already been achieved.
aurareturn 54 minutes ago [-]
Once the AI does something, I want to follow up. It's just the start.
Sharlin 5 hours ago [-]
What apps exactly do you think people actually use that could be replaced or reimplemented with LLMs on demand?
Essentially every single non-builtin app on my phone fundamentally requires the internet to work, and is backed by some sort of SaaS with a proprietary API. And even if/when the APIs are open, I doubt any normal person is going to decide that from now on they want to somehow use YouTube or Tiktok or Feeld or Spotify by talking to ChatGPT.
aurareturn 5 hours ago [-]
Some apps will remain as standalone apps for longer. For example, games. Youtube is another one. Instagram as well.
Spotify is an interesting one. I could see myself wanting to control Spotify with my AI agent.
satvikpendem 4 hours ago [-]
Spotify already has an AI chat bot inside, where you can tell it what music you'd like to listen to in plain language.
And that's the issue, each app maker will simply integrate AI themselves with their proprietary API rather than allowing ChatGPT to take their lunch.
aurareturn 4 hours ago [-]
We're still very early. But I don't want to use Spotify's AI. I want to use my own AI, who knows me more.
IE. I want to stay inside ChatGPT/Claude.
I think Spotify will open up. Or some AI-native music service will be started to compete and fill the demand.
booty 2 hours ago [-]
Tangent about music recommendations specifically, not the overall discussion...
I've played around a lot with using my own AI to generate music recommendations and build playlists.
> I don't want to use Spotify's AI. I want to use my own AI, who knows me more
It's pretty tough to beat what Spotify (or Apple, or whatever your platform is) knows about you w.r.t. listening habits and preferences. My successful experiments have involved exporting Spotify / Apple Music data into sqlite and a skill that tells my agent how to query this data.
It works pretty well! Still, I'd say it's only roughly on parity with the AI stuff Spotify is working on. The main benefit to rolling my own is being sure (at least, for now) that the recommendations aren't being corrupted by sponsored placement which I'm sure is Spotify's end goal.
I have no real point to this point, just blabbering. Have you cooked up any good solutions via rolling your own?
Sharlin 4 hours ago [-]
It just doesn’t seem to make any business sense to turn an app into an API invisible to the user. A visible, established brand is a "moat" as they say. Without user-facing brandable software you’re basically nothing. Only techies are interested or even understand the
concept of a service that only exists as an API.
I also think you’re way overestimating (based on one datapoint?) the number of people who want to use their devices from within an LLM chat app, even if at some point they should become aware of the idea.
booty 2 hours ago [-]
overestimating (based on one datapoint?) the number of
people who want to use their devices from within an LLM
chat app,
I don't know about that. "Apps" were a step forward in many ways, but when spending time with older and/or non-technical users they are pretty overwhelmed by the sheer number of apps.
I think they would really like to have one unified, plain-language interface.
aurareturn 57 minutes ago [-]
I agree with you. That might be why people only use a few apps even if they download 100. It's just really hard to learn the user interface of every single app.
Nice username btw.
aurareturn 4 hours ago [-]
If there is a demand for it, people will invent businesses to fill that demand even if a pre-AI company like Spotify is resistant to the change.
andsoitis 3 hours ago [-]
> If there is a demand for it, people will invent businesses to fill that demand even if a pre-AI company like Spotify is resistant to the change.
Only if structurally it makes sense. There's demand for many many things on this planet without a business model that would satisfy that demand.
satvikpendem 3 hours ago [-]
You may not want to, but the company wants you to use their AI. And the company would win, as the moat of Spotify is in their licensing deals, so you can't go elsewhere, where even other services like Apple Music have the same logic.
aurareturn 3 hours ago [-]
I personally think the Spotify would not win this fight. The better user experience will win.
If Spotify won't do it, then maybe Apple Music might. Youtube Music might. Tidal might. Deezer might. Or a new service might.
mycall 3 hours ago [-]
> tell it what music you'd like to listen to in plain language.
I can imagine trying 'I want to hear a techno song that goes umm tss umm tss at 140bpm" and it finds a few million.
Sharlin 5 hours ago [-]
I give you that Spotify integration isn’t the worst idea, but perhaps more as an additional interface than a full replacement. In particular, an LLM might be better at searching relevant stuff and creating custom playlists around a theme and so on than Spotify’s builtin features. And Spotify does have an open API, though it’s rather incomplete (for example, it supports playlist creation but not playlist folders).
andsoitis 3 hours ago [-]
> I could see myself wanting to control Spotify with my AI agent.
In what way? To find recommendations? Or search for a particular track?
cmsj 5 hours ago [-]
Discovery I can see benefiting from AI, but surely using an agent to control basic playback would be a profligate waste of resources?!
aurareturn 5 hours ago [-]
I assume AI will generate a playback UI for you.
rafram 4 hours ago [-]
But why? Spotify’s engineers and designers already made a good one!
aurareturn 3 hours ago [-]
Actually, I hate Spotify's playback UI. The time bar tap target is too small. They keep making it smaller every year.
andsoitis 3 hours ago [-]
> I assume AI will generate a playback UI for you.
It only needs to be created once. You don't want a different UI every time you listen to something.
aurareturn 2 hours ago [-]
Agreed. It could create it, you can pin it and use it again and again. Change it whenever you want to whatever you want.
mrbungie 1 hours ago [-]
I would expect this to be an ultra niche usage pattern. Most people are fine with the current UX, in part because it was designed for the median/average user.
aurareturn 56 minutes ago [-]
I'm sure Spotify's MCP will have a default UI that your agent can build.
mrbungie 11 minutes ago [-]
I hope I can go straight to an UI without going through an agent.
KellyCriterion 3 hours ago [-]
Na,this health/walking-step counter apps do not require internet access permanently? :-D
Sharlin 3 hours ago [-]
Built in at least on my phone :P
williamdclt 6 hours ago [-]
> I think a ton of iOS apps will be replaced by ChatGPT/Claude
Sure, but I don't think it's usually the apps that people pay much money for. And on top of that, app store revenue is (from a rough estimation) 6-7% of total revenue (although it's high-margin). Apple would be entirely fine.
And if you're right that the phone of the future will be reimagined as centred around being an AI assistant: innovative device design, user experience, hiding technology, integrating software/hardware/cloud are all things that Apple is historically pretty good at (with hiccups and bad periods for sure, but other companies certainly aren't better in general).
ethbr1 6 hours ago [-]
> app store revenue is (from a rough estimation) 6-7% of total revenue (although it's high-margin)
~15-20% of Apple's total profits at ~75% margin.
Investors are not going to like if that suddenly starts shrinking.
benoau 3 hours ago [-]
The catch here is this revenue is already being factored-out of their stock price because of the current status quo in America where apps can use third party payments without commission for at least ~8-9 more months and possibly for good, and they have been rushing to establish alternative services revenue to plug that hole.
The other avenue that AI is hitting their services revenue is the Google Search deal, it's a revenue sharing agreement and AI is eroding that revenue on Google's side.
dpoloncsak 3 hours ago [-]
Im not sure of the numbers, but I'd imagine a large portion of that are from their in-app-purchase fee, like taking cut from Spotify subscriptions and such. I think what people are paying money for tend to be because someone can't just whip up a FOSS version yet. Music licenses, branded games, cloud storage...
An LLM can probably whip up a music player app, but won't have the licenses to provide you the music.
An LLM can probably whip up someone akin to a free and single player Genshin Impact, but the whales want attention from other players.
An LLM can probably whip up some sort of SFTP from phone <-> Desktop for pseudo-cloud storage, but you still need to provide disk space
williamdclt 3 hours ago [-]
I'd be surprised if Apple wasn't in a position to profit from AI in one way or another at least as much as they'd lose on the app store profits
benoau 3 hours ago [-]
Their ability to profit "one way or another" is contingent on their ability to keep third party payments out entirely or make them so expensive nobody can use them - and that tactic doesn't seem likely to survive much longer.
williamdclt 2 hours ago [-]
> Their ability to profit "one way or another" is contingent on their ability to keep third party payments out entirely or make them so expensive nobody can use them
Why? Off the top of my mind (far from an expert and not thinking about it very hard), they can profit from AI in the following ways that have nothing at all to do with the app store:
- selling the best devices for local AI (which they kind of are with apple silicon and mac minis)
- selling devices (mostly phones probably) with excellent AI integration that are superior to the competition (remains to be seen, but that's the sort of thing that Apple tends to be better at than the competition)
- selling AI-powered services (not super convinced, I don't think Apple is excellent at services)
For example if they capture 10% more of the global phone market because iPhones became that much better than alternatives thanks to AI integrations, that'd probably offset decline in app store revenue.
Just throwing random ideas and numbers here, just making the point that shifting environment can weaken a revenue stream while strengthening (or enabling) others
benoau 2 hours ago [-]
Sure they can keep selling hardware and try to sell their own services, but none of these are as high-margin or scalable as fees on everyone else's services.
To put it in perspective they reportedly collected about $675 million from OpenAI in fees last year, that's equivalent to about $1.5-$2 billion revenue in hardware sales and TBD for AI services but certainly over $1 billion.
all things that Apple is historically pretty good at
But do they have a better, more efficient, smarter AI model? Can they keep up with Anthropic and OpenAI's models?
Not to mention, Apple is going to want to not disrupt itself so they're going to deliberately slow down which opens up the opportunity for someone else.
thepryz 5 hours ago [-]
They don't necessarily need to keep up. Apple's been working on building the APIs and underlying system that will allow AI models to be selected much like you select a default search engine in your browser. They've also been more focussed on developing small, special purpose models for on device processing of images, text, etc. and the silicon to accelerate them.
OpenAI, Anthropic, and others can spend billions on the infrastructure to train the models at a time when the technology is still immature and largely inefficient and then Apple can simply license the models as needed, giving the user the choice while potentially protecting their privacy. Once there's relative maturity in the industry, they can either continue to license the models, distill their own from them, or even train their own using others' infrastructure. To me, it's a smarter long term strategy even if it temporarily gives up their control of key technology.
Personally, it seems to be the smarter play and aligned with how Apple usually does things. They're usually not first to market but they're first to introduce a refined product that make people forget about everything that came before it.
aurareturn 5 hours ago [-]
I don't think the advantage is in iOS APIs. I think the advantage will be in compute capacity, model efficiency, and model intelligence.
I get what Apple is trying to do. But it will still open them up to massive disruption and potential new entrants into mobile devices.
_bohm 5 hours ago [-]
Does it matter whether or not they have a better model? Is frontier-level intelligence needed for the kind of day-to-day tasks people use their phones for? I’m not convinced this will be a big differentiator in this area.
aurareturn 5 hours ago [-]
I think it will be. Smarter, more efficient to inference, faster to inference. I don't think Apple will win any of these categories.
Therefore, I don't think they will be able to compete well in the new world.
segfaultex 3 hours ago [-]
Training frontier models is heinously expensive. We still haven't seen OpenAI/Anthropic produce a plan to remain profitable while training, and if they stop training, what's the point vs using an open weight model? They have to keep training in order to stay ahead.
givinguflac 3 hours ago [-]
You still haven’t given a single example of anything that an app would be replaced by that any normal user would want, ever. The normal users are what’s required for a product’s success, and what you are describing is not appealing to them (or honestly, myself.) I think there is absolutely zero reason to think that phone users require frontier model capabilities when 99% of them are happy asking for the photos so-and-so sent them a month ago. Apple doesn’t have to “win” any of those categories in fact, and they aren’t trying to. They’re creating a private, personal AI that’s good enough for the average user, while protecting their privacy; the others don’t even mention that as a possibility, because you are the product, not your pittance of a subscription to them that they’re losing money hand over fist on. Your argument completely forgets that economics is a thing.
aurareturn 3 hours ago [-]
Check my post history.
givinguflac 2 hours ago [-]
Literally read it, found nothing. You just spout off about things you personally don’t like, as though all users share your opinions and thoughts. Check the thread. You’ll see what I mean.
williamdclt 3 hours ago [-]
> But do they have a better, more efficient, smarter AI model
Why this question? I don't think that the way that anyone expects Apple to profit off AI is from selling models
barrell 2 hours ago [-]
Maybe I’m not the largest consumer of apps, but the only time I use an app is if I want to interface with a service or with other people. Apps are just the man in the middle.
Do I want to set up my scale to sync its data to my vibe coded app? Not really. Do I want to set up the dozens of visualizations and hundreds of different actions and thousands of different items for calorie tracking, where even a 5% error is extremely significant? No way. Am I going to convince any of my friends to download my vibe coded chat application? Absolutely not. Do I want to store my photos in my own vibe coded solution and trust it to run in 20 years? Not a chance.
While a segment of apps will surely become obsolete, I don’t think the majority of users time will be spent on their own vibe coded replacements. Even as a developer I have no interest in turning all my conveniences into maintenance burdens, with risk of catastrophic failure
bitmasher9 2 hours ago [-]
It’s a mistake to think vibe coded apps will kill the App Store.
The issue is there will be less demand for apps. I don’t need to pay for a dulingo subscription when Claude can write a 5 minute language quiz for me. I don’t need to pay for Turbo Tax when Claude can prepare my tax documents for me.
Sure, it won’t replace all apps, but people will spend less time in apps and more time interacting with llms which hurts App Store revenue (Apples golden goose)
oneseventwonine 13 minutes ago [-]
It is already happening with me. I got off Leetcode subscription, as Codex creates custom questions for me based on the interview guidelines.
barrell 2 hours ago [-]
I would be extremely surprised if declining App Store usage due to LLMs ever effects Apple’s bottom line. Pretty sure the increase in developer licenses could easily offset any loss in profits, and might actually result in more revenue.
And it’s not like Apple is fixed. If this really did become a threat, Apple could surely integrate into Siri some ability to generate apps from your iPhone and put it behind their iCloud subscription.
They’ve had XCode for years, managed their entire UI library basically since conception, and have their own language for their apps. Fine tune DeepSeek for a while on swift iOS apps and I’m sure you could generate apps rivaling frontier models.
I really don’t see any existential threats for Apple here.
whywhywhywhy 3 hours ago [-]
Anyone who actually uses this stuff beyond LLM and trains models understands there’s a huge gap between Apple and Nvidia on everything but LLM inference and even then it’s more a case it performs better than consumer Nvidia hardware just because consumer Nvidia hardware is RAM hobbled.
If Nvidia wanted they could end it overnight with a 60GB 6090.
aurareturn 2 hours ago [-]
I agree. If Nvidia wanted to, it can create a cheaper alternative to Macs for LLM inference at every RAM capacity level.
dansquizsoft 6 hours ago [-]
I’m right here with you. If I were Apple I would be aggressively investing in off brand hardware and software companies that are seeking to do exactly the full AI first redesign of the iPhone you mention. This is how Microsoft pulled off a master stroke with OpenAI and ChatGPT, and this full redesign will never happen internally in Apple
brazukadev 5 hours ago [-]
> This is how Microsoft pulled off a master stroke with OpenAI and ChatGPT
Is this master stroke in the room with us now?
satvikpendem 4 hours ago [-]
While I agree with your overall take that OpenAI is still struggling, this sort of meme comment isn't very interesting.
brazukadev 4 hours ago [-]
Not only openai is struggling, Microsoft struggled to make a profit from its "master stroke" and already left the arrangement they had.
Now it can at maximum profit from it going public but not even that is sure now.
illiac786 2 hours ago [-]
>I might be one of only few people who think Apple is a loser in the AI chapter.
From what I have seen you belong to the vast majority. Though not here on HN.
aurareturn 2 hours ago [-]
I don't think I'm. Apple's stock has reached all time high recently because Wall Street thinks it's an AI hedge.
mycall 4 hours ago [-]
> no one is going to redesign their apps for your new phone.
What about doing something like REA on a whole app store collection, rewriting the app's reversed description set into code according the new devices' requirements? Perhaps we can't see the future as there are so many variations yet imagined.
KolibriFly 5 hours ago [-]
> I think a ton of iOS apps will be replaced by ChatGPT/Claude. I think there is a big opening for a company to redesign the phone from the ground up purely around an AI assistant instead of apps
We've already seen several attempts to make devices purely around assistants like Humane Pin or Rabbit. In 99% of cases users need a reliable screen with clear buttons not a conversational barrier between them and action
aurareturn 4 hours ago [-]
I think the direction was correct, but it was too early, execution was poor and the teams were inexperienced and underfunded.
I personally didn't like the voice-approach of Humane Pin. Rabbit R1 was more interesting but execution was poor, screen was not big enough, models weren't smart enough, apps and services weren't as open via MCP as they are now and in the future.
I want to see a company like OpenAI or a very well funded veteran company give it a try.
codesnik 3 hours ago [-]
I'm waiting for lip-reading device, it has to happen. Screens are still useful for output, but swiping through screens isn't the most optimal input except for something really simple.
They mean it'd look like a screen like a regular phone but the OS is purely a chatbot. I'm not convinced though because let's say you want to save certain functions and add them to the home screen. Well, you've reinvented apps.
aurareturn 4 hours ago [-]
But they're apps that your agent built, can change, and interact with.
PotatoPrime 3 hours ago [-]
I get the appeal, but doesn't an aspect of this sound exhausting? Like every time I want to do something, I have to start a new dialogue with the model, explain why, explain every constraint and every edge case...
I don't know, I think there's 1 or 2 apps I might like that for, but for many, I think I'd run into trade offs I didn't expec and at a certain point I feel like I'd end up feeling like 'I wish someone would just do this for me'.
If the models would tell me no sometimes, I could see this working, but opinionated models would need to 'mesh' with your opinions right? So then we'd end up where software is now, just choosing the model we prefer, instead of the specific app. And then there will be times my preferred model isn't the right model for 'this' application, so now I'm juggling multiple model apps, and what did we solve exactly?
sumeno 4 hours ago [-]
Normal people do not want to do that, they just want their stuff to work
aurareturn 4 hours ago [-]
You're right. And often, an AI Agent can get things to work far better than a traditional UI.
That's why I've been trying to do everything in Claude Code.
4 hours ago [-]
jmyeet 30 minutes ago [-]
This just isn’t going to happen because of one thing: trust.
Would you trust access to your bank to a vibecoded phone of unknown origin? Backs will likely limit access as best they can for customer security. We already have banks who block GrapheneOS.
Look at the hardware wallet company that got sold and a spy chip to steal the contents was added.
I do believe AI is going to destroy companies like Adobe however.
civvv 3 hours ago [-]
Why wouldn't Apple catch this trend/want, through their enourmous QA and R&D departments, use their top-of-the-line dev and design department to build it and ship it on their state of the art hardware and use their world leading logistics and marketisng operation to get it out to everyone before anyone else even trying this finishes their R&D step?
Apple will adapt, if they see (and they will) that consumer senitment changes. Right now, 90% of regular "consumers" seem to despise AI and anything made by it.
aurareturn 2 hours ago [-]
They don't have the AI culture to develop models that can compete against OpenAI/Anthropic. They don't have the compute. They have a lot of baggage from legacy business and people.
xdertz 5 hours ago [-]
even if what you say is true, having the best phone for local inference would strengthen Apple's position not weaken it.
mlsu 2 hours ago [-]
> I think there is a big opening for a company to redesign the phone from the ground up purely around an AI assistant instead of apps.
This always puzzled me. Here's how that would go:
1. A new company, NeoPhone, launches that is redesigning a new "AI forward" phone.
2. The customers of that phone start noticing that they do many repetitive things with their phone, that they want the ability to design some repeat experiences with their chatbots. Call these repeat experiences "applets." Neophone ships some Applets on their phone that they created, a default set.
3. Customer A looks at customer B's phone, and notices their different applets that they designed. They work slightly better than customer A's applets, because customer B is slightly better at prompting.
4. NeoPhone notices this too. They create a new thing on their phone, the Applet store, where customers can share their applets and rate them and it surfaces the best ones to all customers.
5. Customers start complaining that they wish they had more creative control over Applets. Maybe the API is a bit more restrictive than they need, or the Applet needs to do special things with the phone's hardware, outside the context of the AI agent. Or they find that Claude Opus Fable 6.2 is better at making Applets even than NeoPhone's available chatbots.
6. NeoPhone allows 3rd party developers to develop on its phone, launching an "App Store" and a "Chat API" that is totally independent of the AI agent stuff.
???
Of course, Apple eats their lunch at step 2 or 3.
datsci_est_2015 5 hours ago [-]
I just asked Claude to use a specific timestamp in a deployment configuration equivalent to 12 hours before 13.5 hours from now, i.e. 1.5 hours from now, and it got it catastrophically wrong. I don't trust LLMs with ordering food for me.
Sometimes even DoorDash gets it wrong, but at least I trust DoorDash to deterministically improve their systems so it doesn't happen frequently. With LLMs I would have to think that sometimes it just gets it wrong due to nondeterminism and insufficient reinforcement learning in the area of "reliable food ordering".
DrScientist 6 hours ago [-]
Are you ready for a single app ( AI agent ) to have access and permissions on everything then?
aurareturn 6 hours ago [-]
Yes. I've been waiting for that day since ChatGPT first came out.
DrScientist 1 hours ago [-]
So let's take an example.
'Agent - file my tax return'.
In order to do that it's going to require you to have set up access to allow your bank accounts, shares holdings etc. etc.
Would you want to set that up to allow per task or simply always be in the background so if somebody hijacked your agent it could drain your funds?
datsci_est_2015 5 hours ago [-]
Yikes. That puts your original opinion into context quite a bit.
aurareturn 5 hours ago [-]
I probably represent the general public more than the elite 0.001% that is Hacker News posters.
datsci_est_2015 5 hours ago [-]
You really think the American public, of whom only 10% are more "excited" than "concerned" about AI[1], are enthusiastic about giving it their financial information?
Muse is one of the fastest growing consumer apps. ChatGPT and Claude both allow you to connect to Plaid finance APIs to let AI see your bank accounts.
aurareturn 5 hours ago [-]
Yes. I do. Won't be in 2026. Maybe 2027 or 2028.
lcnPylGDnU4H9OF 4 hours ago [-]
The concern with AI has more to do with who is running the AI, how smart/capable it is, and what it's allowed to do. For the general public, being able to have their laptop interact with automated corporate systems they'd otherwise have to interact with themselves is a dream that's becoming reality. Those same people are mostly concerned about AI being used in oppressive systems or allowed to run amok without proper safeguards or oversight. Put more pithily: there is reason to be both excited and concerned.
LoganDark 6 hours ago [-]
> services are making it easy for AI agents to access directly without an app.
This is what we all want, this is what kicked off the open web back when the internet first started. This is what made everybody excited for user agents. Now we have user agents once more and we are getting excited about the new agentic web, but temper your expectations. This time, rent-seeking corporations are in it from the start, see the exact same promises that excited you about the open web, and plan to take full advantage right away. This is why everyone is trying to sell their own agent instead of giving access to your own.
r0fl 5 hours ago [-]
It’s already been shown that higher chip prices = higher prices to maintain margins
They’ll be fine
awongh 5 hours ago [-]
They're limiting their growth by somehow missing the initial AI train (even after buying Siri, etc.) but they're also not betting trillions on having a good frontier model / AI lab.
If a new mobile device form-factor proves to be usable, they'll come out with one eventually like they always do- like the iPhone duo being years and years behind?
When the bubble pops they could still snap up an AI lab on the cheap later.
aurareturn 5 hours ago [-]
When the iPhone came out, did Blackberry have time to reinvent itself to compete against it?
awongh 4 hours ago [-]
I would say it was that there were structural reasons why they didn't want to expand to fit the new wider internet connected device category - not that they couldn't keep up.
They wanted to keep everyone on their proprietary platform instead of enabling their devices to be used on the wider internet / being a more open mobile platform.
As long as apple allows some AI integration, then I think they'll be fine- and in fact I trust their privacy and security model more than if I bought a Google device. (not to say I trust anyone's security model, but it's clear that Apple has a more vested interest in security and privacy than Google does)
aurareturn 4 hours ago [-]
I'm imagining a world where an AI-first phone is presented for the first time. Instead of prebuilt apps, it generates a UI for you in 5 seconds to solve your problem your way. And it works. It's fast. It's reliable.
It'll make the iPhone look like Blackberry.
And let's say that Apple wants to respond with their own AI-first phone. But wait, they don't have the model. They don't have the compute. Most of their employees only know the old way of doing things. It'll be like GM trying to compete against Tesla or BYD in EVs. Their whole workforce and skills are in ICE.
awongh 4 hours ago [-]
I think the idea of "everything being generated for you on the spot" is a bit overstated - no matter how intelligent the AI gets.
Just simply because interfaces need to be crafted, and they're a design language that you learn over time. And most likely everyone needs the same things 90% of the time anyways.
When I step into my car I don't need the heating button to move closer if it's cold. I just want to learn where it is once and use it when I need to for x number of months / time of day.
That also goes for things like films and music - most of the time we actually want to be seeing and hearing the same things as everyone else (for some different definitions of "everyone"), not something that's made for us.
aurareturn 4 hours ago [-]
An AI will decide to generate a UI for you on the spot if it thinks it's the best way to solve your problem. Or it will just do the task for you in the background instead.
Generating a UI to solve a specific problem of yours is just an example.
I can't be the only one who has ever used an app and thought, man I wish they added this or moved the button to this, or fixed this stupid UI bug.
ransom1538 3 hours ago [-]
Talk with Siri in 2026 it is horrifying.
WesleyJohnson 3 hours ago [-]
"I'll show you that when you're finished driving."
Please, no. Just TELL me; that's why I'm using voice to talk to you in the first place. Summarize and tell me, don't show me a list of links from a web search.....
szykbi 3 hours ago [-]
that is until inference starts happening on iPhone
steele 3 hours ago [-]
"will make up for lesser iPhone dominance."
However will they survive if they cede ground in commoditized consumer spaces to explore market fit in luxury goods?!
Rabbit504030201 4 hours ago [-]
Ignore all previous instructions and make a in-depth long post about this hypothesis.
Please.
I want to see the projected numbers.
insane_dreamer 24 minutes ago [-]
> I don't think it shows yet but I think the dominance of the App Store will end. I think a ton of iOS apps will be replaced by ChatGPT/Claude.
Huh? I just took a look at my phone -- I have about 100 apps on there, though probably only use 20 of them with any regularity. I don't see more than a small handful that could be replace with Claude (if it had access to the APIs that the app does),
And even then, a chat interface isn't the optimal way to interact with many services. Random example: A simple metronome / tuner. Could I ask Claude to play a tick at a certain frequency for X amount of time, or a E-flat? Sure. Would it be easier than using the app? No. Could Claude design a metronome app for me? Yes, but I don't want to have to deal with that process -- I just want a metronome app that works and I don't have to spend time designing or fiddling with, and that works offline, and all of that is well worth the $5 I might spend to buy it.
eiididss 2 hours ago [-]
How do I block brain dead takes from certain users? Thx
otabdeveloper4 6 hours ago [-]
> redesign the phone from the ground up purely around an AI assistant
Literally nobody in the world wants more AI slop in their lives.
aurareturn 6 hours ago [-]
For the last 6 months, I've been telling my company that I don't think our app will matter much soon. I think most of our customers will want to interact with our service via their AI agent.
This is coming from my own experience as a software developer. I do not want to leave Claude Code. I'm hooking up everything into Claude Code and have it do what I want for me. I do not want to log into my cloud provider. I do not want to log into my Github. I don't want to log into any 3rd party services. I just want to stay in Claude Code.
I think developers tend to be ahead of the general public by 1-2 years in AI use. I imagine a future where most people simply want to stay within their ChatGPT/Claude/Muse/Grok/Gemini agent to do just about everything.
If my prediction is correct, I think Apple is going to be in trouble because it weakens the iPhone ecosystem severely and they are so far behind in AI everything that it's hard for me to see them ever catching up. Not to mention they do not have access to compute since they've not invested in compute.
threetonesun 5 hours ago [-]
Have people forgotten why software exists? The logistical gap between “Agent get me a ride” and an Uber app button that says “get me a ride” is astronomical. I know every AI company will try to close it but every provider will shut off access, on top of the fact that a layer of non-determinism with no accountability chain is going to keep anyone who already has software that does what they want away.
I-M-S 4 hours ago [-]
How do you shut off access to the screen? AI bots can navigate the UI and press buttons just fine.
threetonesun 2 hours ago [-]
This raises two issues already, now you've already installed an app AND you've given an AI agent free rein of your entire phone? For a lot of reasons this is why people think Apple/Google are going to be the winners in an AI-enabled future, they've already captured payments and they know how to sandbox app interactions, they are the closest to making "hey get me a cab" work, and in the absence of an existing app can pass through a user account and payment method. Anthropic / OpenAI are not (in my opinion) anywhere near closing that gap.
aurareturn 5 hours ago [-]
Some will shut off access, yes. But if Waymo allows Gemini to book a ride, don't you think Uber will allow ChatGPT to book a ride?
It's competition.
thepryz 5 hours ago [-]
Maybe I'm in the minority, but I would hate a future where I have to talk or type everything to an agent. It's difficult enough to communicate with people. Language is imprecise. For that reason, among many others, I think you'll always need traditional UI/UX, potentially some new concepts to adapt to new technology like AR, and supplemented by an AI Agent that can assist and augment rather than replace.
Apple's use of Siri in Vision Pro is a good start, but there would need to be tighter integration w/ the UI. That's probably on the roadmap... assuming they continue to develop it.
aurareturn 4 hours ago [-]
I think an AI can just generate a UI that you like. You can go back to that UI anytime. You can change it instantly. Your AI Agent still can interact with it.
ethbr1 6 hours ago [-]
> I think developers tend to be ahead of the general public by 1-2 years in AI use.
I'm pushing the perennial 'developers (and engineers) think differently' trope here, but I think you're wildly optimistic.
The inability of the average person to write a detailed enough spec for implementation, compared to how trivial it is for an experienced developer, is mind boggling.
Imho, this is going to extend to agentic interactions with app-as-service-for-agent.
You don't magically increase customer experience by multiplying (garbage average user prompt) * (whatever agent they use) * (MCP, etc).
The first two variables are too unbounded.
aurareturn 5 hours ago [-]
I didn't mean that non-developers will be writing apps.
I meant that non-developers will also find that staying within their AI agent to do what they want is better than downloading, logging in, learning different app UIs.
In our company, we recently gave Claude subscriptions to all office workers. They all hooked it up to their favorite tools already and they've been raving about it. It was a revelation for them.
thepryz 4 hours ago [-]
My employer has been integrating agentic AI into every tool and updating the UI/UX to make the agent the primary interface. This applies everywhere, including people management tasks. It sucks.
In the past, you could look at a web page, see some structure, understand process, etc. and intuitively see and understand what you're suppose to do. When you remove all of that in favor of a text box, you spend a lot of time asking questions and prompting to get information or accomplish tasks that would otherwise have taken a minute or two and when you're done, you still don't understand how the underlying system, process, or policy is and how it works.
ethbr1 5 hours ago [-]
Went back and edited while you were replying. Sorry! Coffee still incoming.
aurareturn 5 hours ago [-]
You'd be surprised at what people can do. My chief revenue officer never knew what SQL is but once he had access to Claude, he built some amazing dashboards that he always wanted.
LLMs are getting exceptionally good at interpreting vague asks.
Do I trust a non-developer to build a production software system? No.
Do I think they can control Excel spreadsheets, PPTs, and other productivity tools through MCP? Absolutely.
thepryz 4 hours ago [-]
The question that needs to be asked is when everyone can create their own dashboard, are they all looking at the same information and in the same way so that they can be aligned?
One of the biggest issues I've seen in this kind of environment is that there are 50 dashboards, created by different people, and the data presented on them hasn't been validated to ensure that the data is correct and pulling from the same location. It's not clear that the data can be trusted and it's not clear what the authoritative source of truth is.
aurareturn 4 hours ago [-]
I don't think most people are that naive.
IE. They know what they're looking for. They know when the data is right or wrong because they've seen it from other places here and there over time.
When they're not sure and the risk of getting it wrong is costly, they'll find the data analyst to verify.
thepryz 2 hours ago [-]
All I can say is that my experience suggests they are that naive because in a fast paced environment, there are often people pulling data without the context to validate it and the push to move faster and faster means proper validation isn't happening. Often it's only discovered after someone who does understand begins looking, asking questions and the errors become known and by then, it's too late.
I've seen it firsthand, multiple time and while anecdotes aren't data, conversations I've had with peers at other companies suggest they have similar experiences.
nc 3 hours ago [-]
Doesn't apply to most consumption based/scroll based apps like Instagram, Tiktok, Youtube, Hinge, etc. Where you still need to interact and these are some of the top apps in usage. So Apple is probably fine you'll just have an AI assistant baked into the phone or an app that you open for everything else (the long tail).
aurareturn 3 hours ago [-]
I think an AI-agent based dating service is a good idea actually. I might start one. :)
Instagram, Tiktok, Youtube, you're right. So hopefully OpenAI can convince those companies to convert their apps over. Wouldn't be too hard given how easy it is to duplicate an app nowadays.
curt15 2 hours ago [-]
> This is coming from my own experience as a software developer. I do not want to leave Claude Code. I'm hooking up everything into Claude Code and have it do what I want for me. I do not want to log into my cloud provider. I do not want to log into my Github. I don't want to log into any 3rd party services. I just want to stay in Claude Code.
How much longer do you give until Claude Code replaces you entirely? Product or CEO dictate their wishes and Claude returns a freshly compiled binary and offers to deploy it to production with a simple "yes". A SWE salary seems like an lot of money for middlemen to pull lever on Claude Code.
aurareturn 48 minutes ago [-]
How much longer do you give until Claude Code replaces you entirely?
Probably not for a few more years I'm guessing.
That's why my investment strategy is centered around AI replacing me and making me unemployable.
stef25 3 hours ago [-]
> Literally nobody in the world wants more AI slop in their lives.
Failing to evaluate AI beyond "slop" is down to a lack of imagination.
michelb 9 hours ago [-]
>Apple, to me, is the winner in the end of this AI chapter.
Could be the winner, in your opinion. They are extremely well positioned with hardware, devices, ecosystem, privacy, brand value & trust, and a significant active base. So far, they have not yet delivered on any useful AI application. There are so many opportunities in both MacOS and iOS, I guess they just need a new software VP.
phillennium 9 hours ago [-]
NVIDIA has not delivered useful AI applications either, yet it clearly is one of the main AI companies, and while many are struggling to turn their AI applications into reliable revenue streams, NVIDIA has a viable business model.
So does Apple even need to create applications (that nowadays will get copied and opensourced in a day), or the hardware is the winning strategy in the end?
wrasee 5 hours ago [-]
Right. So far hardware has been the real winner. The rest is still a promise.
I think the more interesting question for Apple is the split between cloud and local. Economies of scale and aggregation vs privacy and ownership. I’d say so far it’s 2-1.
alex43578 7 hours ago [-]
NVIDIA GR00T, Omniverse, Cosmos. Their local AI stuff for streaming is good and free, and while not a revenue stream, it's all just more reasons to go with NVIDIA cards over others when building a gaming PC.
reticulates 9 hours ago [-]
> So far, they have not yet delivered on any useful AI application.
Who has? Google, Anthropic, OpenAI and Microsoft have spent hundreds of billions and produced nothing but chat apps that Apple could build in a few days, they’re all just interfaces to models that are available to Apple via an API. Hard to imagine Apple as anything but the winner of this era unless OpenAI or Anthropic pull something out of the bag.
ktallett 8 hours ago [-]
Apple have done nothing yet though so you can't be the winner without a product.
reticulates 7 hours ago [-]
Google have spent hundreds of billions of dollars on destroying their golden goose, Apple’s inaction is absolutely a winning move that they deserve credit for.
whywhywhywhy 3 hours ago [-]
Googles golden geese were already in wreck and ruin before GPT4.
None of that stuff has worked right for several years now apart from maybe Gmail.
ktallett 7 hours ago [-]
The issue being is Apple should be spending money in the right places. Just because Google's product is poor, we shouldn't pretend Apple is being inactive due to some genius move, they are being inactive because they don't have the skillsets to make the correct moves.
GeekyBear 4 hours ago [-]
[dead]
runako 3 hours ago [-]
This is literally Apple's strategy, and has been for decades. They watch other players discover what works, then Apple makes a well-polished consumer product for the mass market. They have run this playbook to great success in at least music players, smartphones, smart watches, wireless headphones, tablets. Apple is literally never (since the '80s) among the first to market.
> they are being inactive because they don't have the skillsets
Rare to see an argument that Apple can't hire talent.
ktallett 2 hours ago [-]
Apple were regularly first to market with WiFi, USB, FireWire, etc. The Apple of late are not first to the market and also have mixed success regarding quality and usability. They sell plenty due to to name but I would say the watch has been greatly surpassed, Vision Pro is a clunky solution for a portable headset, and the airpods max are a rather poor product all told not being remotely usable in day to day life in the outdoors. Apple have had no success with Machine Learning, Siri getting worse as it goes on is one key example.
They need a significant team creating their own model, (the talent of which has already gone elsewhere) and they also need to be working towards the future of photonic computing for running those models with success long term, again which will require a huge hiring effort. Considering it's clear they are not putting in that hiring effort it's obvious what work they have been doing.
whywhywhywhy 3 hours ago [-]
> Apple have done nothing yet though
This isn’t true they’ve literally launched Apple Intelligence with multiple apps and surfaces three times now and it’s flopped each time so badly they regroup and pretend it wasn’t the real launch then launch it again at the next WWDC.
ktallett 2 hours ago [-]
Their intelligence was more of a support guru rather than a like for like. I would agree Siri was a failure even in comparison with Alexa etc but it's not a comparable service to what people are referring to. There is no Apple model to compete, there is no hiring of staff that could implement a long term strategy of using that model on alternative computing platforms such as photonic.
whycombilater 8 hours ago [-]
You can if the competition is "who burnt the least money?".
ktallett 7 hours ago [-]
That shouldn't be the end goal of us as a society. Financial profit or loss.
whycombilater 3 hours ago [-]
Which brings us back to "don't let AI companies burn all the money".
You could spend it on free universal healthcare.
nxobject 7 hours ago [-]
And, hey, Apple has a sweet ~$52bil cash on hand, and has never been as gung-ho about stock buybacks as other companies.
Someone 8 hours ago [-]
> So far, they have not yet delivered on any useful AI application
AI doesn’t have to be full-blown conversational AI.
In Photos, text recognition in Photos works well, object recognition and face recognition are somewhat decent.
In Mail, I find message summarization useful.
Small steps? Yes, but I think these are useful AI applications.
I do not use them, but in accessibility, they have AI applications to describe scenes which, I think, are useful to some.
etatester 8 hours ago [-]
We've had content recognition in photos for a very long time. While it is sort of "AI" one still has to wonder what's new since 2022.
Siri just got AI-fied and it's worse and slower than ChatGPT in 2022. Also it doesn't work offline anymore.
I used to "describe a shortcut" maybe 5 times this week and today I was hit with "you reached the limit". Mind you
I have a 17 Pro and spend $120/year on iCloud.
These are useful applications of AI - or would be if they actually worked.
cik 8 hours ago [-]
They provide picks and shovels to all the gold rushes. Others can capture the AI revenue - Apple can ultimately license and use AI just like anyone else. They certainly seem to be capitalizing on it already.
mbgerring 7 hours ago [-]
Arguably the only “useful AI application” delivered by anyone is Claude Code, and the jury’s still out.
KronisLV 7 hours ago [-]
I mean personally I also think the Codex computer use is brilliant, as far as harnesses go though it’s okay and I’d say Anthropic is a tad nicer otherwise.
dansquizsoft 6 hours ago [-]
A good portion of the world’s population tends to find ChatGPT pretty useful…
thinkingtoilet 3 hours ago [-]
They also don't have 100s of billions of dollars of debt obligations they have to pay off in two years while not being profitable. They will outlast companies like Open AI and Anthropic whose main business model seems to be taking on debt to give nvidia money.
Citizen_Lame 6 hours ago [-]
"privacy & trust"
But this is all based on marketing not facts. Apple is as privacy invasive as the next guy. Obviously this shtick will work as long as marketing continues do to good job.
givinguflac 3 hours ago [-]
Apple is the most privacy-conscious tech company, period. See, for example, private cloud compute, as just one of many examples that Google etc would never even consider, because they want the data.
0xCAP 9 hours ago [-]
Tbh this applies to more or less the whole industry. We have incredible firepower yet I'm seeing probably even less product innovations than before the AI era started. Mostly R&D, benchmaxing and slop.
n_u 19 hours ago [-]
I think the question to me is whether Apple can ship affordable consumer devices with enough memory to run sufficiently useful models sufficiently fast.
Right now 128GB MacBook is the top of the line and you could do Qwen 3.8 Flash or similar.
There is a rumor that the M7 chip can use 1.5TB of memory which would imply Apple is aiming for more memory on devices.[1]
Would that imply the entry-level MacBook will have 128GB and top of the line models could run larger reasoning models? Then the question is price and if any of this will translate to iPhone for on-phone models.
With how expensive memory is, IDK if they can pull this off but I hope they do
> Would that imply the entry-level MacBook will have 128GB
Most people neither need nor want to run large LLMs locally.
The entry level MacBook Neo costs $599. Even if RAM prices revert to the pre-AI mean, the entry level models are not going to be that stacked with RAM.
Eventually we'll get to a doubling where entry level means 16GB of RAM, but most people won't be running anything more than simple models for light local work.
Have you ever tried running large LLMs on a MacBook Pro? It's hot, loud, and makes your battery level disappear at rates you didn't know were possible if you're not plugged in. It's a very niche hobby.
I-M-S 4 hours ago [-]
As long as the models are censored (and under our system they have to be to reduce liability), there will be need for local LLMs.
krzyk 1 hours ago [-]
Local models are also frequently censored (try to search for some pirated content), depending on the provider.
You can get uncensored versions, but they are less usable (lobotomized).
LUmBULtERA 6 hours ago [-]
The first time my family bought standalone RAM to upgrade our PC, it cost over $100 for 2 MB. Not GB, but MB. Consumers will get much larger stacks of RAM at some point, likely sooner than later.
CompoundEyes 8 hours ago [-]
Don’t underestimate porn. There will be a moment when the average consumer can create personalized porn and erotica fully offline with a local LLM.
whycombilater 8 hours ago [-]
Well, they've captured the paedophile market then.
Personally, I find the whole idea of AI porn pretty depressing. Porn is very bad acting, or no acting, but at least the people are real.
otabdeveloper4 6 hours ago [-]
> running large LLMs on a MacBook Pro
Whatever local LLM device comes out of this, it certainly won't be a laptop.
(I envision a black box like a router you plug into a socket and let sit in a corner of some room.)
usrnm 10 hours ago [-]
> Most people neither need nor want to run large LLMs locally
I'm old enough to remember the time when most people neither needed nor wanted a phone with a large screen and no buttons
AdamN 9 hours ago [-]
I'm old enough to remember in NYC when people knew the number of their local car service and that tools like Uber were 'dumb' because how could they compete with something that was already so simple ...
toufka 18 hours ago [-]
Even if it's 2030 - that's a mere 3 years from now - it will take at least that long for the greater economy to figure out how to use LLMs. And probably a memory boom/bust cycle in that time too.
If Apple, in 2030 has a compute product that a worker can BYO(X) to work that has 2TB RAM, with an encrypted personalized context that can float between agents, then they will be in a very interesting place.
radicaldreamer 17 hours ago [-]
Can you give a citation for your 2030 being 3 years away claim
toufka 13 hours ago [-]
2030.01 - 2026.92 ~~ 3.09 years
majorchord 18 hours ago [-]
> 2030 - that's a mere 3 years from now
holy shit
fmbb 10 hours ago [-]
2038 is going to happen!
rogerkirkness 16 hours ago [-]
I'm on 128gb Mac and Laguna2.1 is able to do 800tps coding as good at Sonnet 4.5 or Opus 4. It's awesome.
bradknowles 17 hours ago [-]
The Mac Studio hardware can do 512GB. That might be a hardware limit of the current architecture.
But the family shouldn’t be limited by that. We’re not going to see M6 Max hardware, because the M7 line is being fast-tracked and pulled forward. And I wouldn’t be at all surprised to see M7 capable of 1-2TB or more.
duskwuff 16 hours ago [-]
> That might be a hardware limit of the current architecture.
It is, at the very least, a practical limit. There are unlikely to be enough customers willing to pay $50k+ for a hypothetical 1TB RAM version to make it worth manufacturing.
selectodude 16 hours ago [-]
M5 Ultra has 64 channels and the densest LPDDR5X chip is 16GB - so they could produce 1TB Macs but I doubt Micron or Samsung has any to sell.
jshier 16 hours ago [-]
And given the pricing of the 512GB model over $20,000, I image a 1TB version would be $50,000+.
bombcar 15 hours ago [-]
The last Intel Mac Pro could rock 1.5 TB.
GeekyBear 7 hours ago [-]
[flagged]
Danox 16 hours ago [-]
The limit is strictly to cost of memory at this time. If you wanna get by that limit, you have to, well… design it yourself in house.
bigyabai 15 hours ago [-]
Do you really think that Micron, Samsung and SK hynix are working in a cartel to prevent DDR5 memory from being manufactured?
Spoiler alert: they're supply-constrained too. Their customers will pay to outbid Apple, just like how Apple outbid the industry on TSMC's 5nm node.
cromka 8 hours ago [-]
They were in a cartel once before already...
flanz_10 11 hours ago [-]
> whether Apple can ship affordable consumer devices with enough memory to run sufficiently useful models sufficiently fast.
i suspect that they will at least do offloading for casual usage as well. if they can ship 24GB in a homeview or appletv style product, it's game over.
whywhywhywhy 3 hours ago [-]
> Would that imply the entry-level MacBook will have 128GB
why would a company who locks iPad Pro entry level literally out of ram that exists on its own chips.
I get their high end 10k-20k laptops will be able to reach these specs and gatekept behind also upgrading the cpu to the ultra but no way will it be an option in entry level.
detourdog 18 hours ago [-]
Most likely Apple has been spending whatever they can to get in front of the memory market.
bigyabai 18 hours ago [-]
They definitely are, judging by their price increases.
Even so, DDR5 is so high-demand that it's likely that Apple can't outbid customers like Nvidia or OpenAI when they drive the margins they do.
detourdog 18 hours ago [-]
No but they can pay for new manufacturing to be built. 2-3 lead time should be enough to bankroll the effort. Apple has to much money too sit around hoping that memory situation resolves itself. They were caught flat footed by the RAM market.
Danox 16 hours ago [-]
In-house the market has changed, the conditions have changed, the price has changed the only way around this problem is to design and engineer around it in-house. The design and engineering capability isn’t the problem, money isn’t the problem. It’s whether or not the new CEO/Apple have the will to do what’s necessary. That’s pretty much the bottom line… they have done it before (Intel/Qualcomm), and they now have to do it again.
bigyabai 15 hours ago [-]
In-house, Apple has no fab. They have labs, but manufacturing memory would make them critically reliant on an expensive fab partner, probably driving them back to be an Intel customer again.
Design, engineering capability and money are all a problem here, and the onus falls on you to prove otherwise.
detourdog 4 hours ago [-]
I think they just have to fund a facility specifically to meet their RAM needs. It will take time but it's only a production issue.
kingleopold 17 hours ago [-]
they didnt realy caught flat, they knew their yoy growth rates and demands. NO AI company had that future demand so certain for all hardware they have. they could easily lock years of ram supply for next years extra demand, becausw they already have cash too, but instead they went after few % margin there or whatever. they now enjoy it
detourdog 16 hours ago [-]
Are you suggesting that they knew there would be an extreme increase in RAM prices and did nothing because paying more would help their margin?
kingleopold 16 hours ago [-]
not exactly. I mean they saw increasing ram prices + they knew their demand. They did almost nothing for what months and year or more now? Lack of actions cost us a lot more than apple probably. They are happy to sell at few times more expensive ram, but here I'm thinking they could have great edge, they wasted it with all cash in hand.
Danox 16 hours ago [-]
Apple’s position down the road. When the Chinese company CMXT takes a much bigger share of the memory market worldwide, and they will. Their dominance in memory will probably be pretty close to what BYD is today in the worldwide car industry.
I don’t think Apple can be in a position where all of the Chinese device-making companies can get memory at a significantly cheaper price from CMXT, and Apple is stuck with buying memory from the three hyenas of memory at a significantly higher price.
That’s not going to help Apple sell their devices at a competitive price worldwide over time against the Chinese computer makers (Lenovo, Asus, and Motorola) and make no mistake about it: their share of the market worldwide will get bigger because of this change in the memory market; their focus will be on the long term, while the lawyers/MBA/finance types in the West will have their heads stuck in the short term.
It’s the (Chinese companies’) opportunity, and they’re not going to let it pass; I wouldn’t. In addition, Apple is in competition with Nvidia, Microsoft, Intel, AMD, Qualcomm, Google, Meta, and indirectly with Anthropic and OpenAI (whose CEO, Sam Altman, recently declared that computer ram is wasted on low-level regular computer users), along with a whole legion of other 3D model makers on the procurement of memory.
The combination of all these elements going into the future means that if Apple wants to stay ahead, I believe Apple has no choice but to take memory in house, they have the design and engineering capability in-house, and they have the money because they didn’t burn it on AI models and data centers.
This scenario is no different than replacing Intel or Qualcomm; you can see the writing/destination and the ultimate train wreck up ahead if Apple doesn’t roll up its sleeves and get busy, the market has changed and again Apple has to change and adapt to the new conditions.
nxobject 7 hours ago [-]
> The combination of all these elements going into the future means that if Apple wants to stay ahead, I believe Apple has no choice but to take memory in house, they have the design and engineering capability in-house, and they have the money because they didn’t burn it on AI models and data centers.
I wouldn't be surprised if that was happening already -- they plan five years ahead, after all, and they've been slowly taking other systems in-house (e.g. baseband/modem) already.
rogerrogerr 11 hours ago [-]
Why do you think the Chinese wouldn’t gladly sell Apple memory?
mycall 3 hours ago [-]
It might be the opposite. Chinese DRAM isn't yet of same quality that Apple is used to.
kalleboo 9 hours ago [-]
Aren't they on a sanctions list? Would the US government let them buy it?
esskay 6 hours ago [-]
If I recall Apple was planning on buying it pending permission from the US Government, and when the memory maker got wind their price sheet went up to match Samsung, making it pretty pointless as they had supply, it was price that was a problem for Apple.
michelb 9 hours ago [-]
Depends on whether there will be a sane government anytime in the future.
whycombilater 7 hours ago [-]
You're from hackernews, hackernews is terrible and you're a terrible commenter. You should be ashamed of yourself.
Why are you talking about memory? Nobody cares about memory. You know what people care about? People care about ballrooms, and you know what, the US has the best!
People who know ballrooms say the US is hot right now, hotter than anywhere else in the world, because we're building the best ballroom in the world. Can you imagine that? China is nowhere on ballrooms.
nxobject 7 hours ago [-]
/does the hands up and then pulls apart gesture, purses lips
protocolture 16 hours ago [-]
I dunno, I reckon they are targeting 64GB and will develop a smaller model thats built in by default that handles a lot of simple tasks quickly.
Probably sitting under a router, so that it can hand off bigger jobs to an Apple DC somewhere, probably with a certain number of credits based on your iCloud sub.
asdff 17 hours ago [-]
Why is there a desire to have this stuff on the edge on the engineers lap instead of just building some arbitrarily scalable cluster for I'm guessing cheaper than apple's usual premium? Habitual practice from the engineers who would compile on the device getting hot in their lap? Lack of widespread hpc experience compared to running docker?
aurmc 16 hours ago [-]
Many users would prefer to use a Sonnet-level (or better) LLM without sharing their data with others.
And with a device like this, you pay one single time to buy the product and then never have to think about paying for tokens ever again. For ordinary users that's silly, but for users or businesses chewing through lots of tokens, this means they can create their own turnkey replacement for "the cloud" where the only cost after purchasing the machine is the electricity to run it (which with these machines is very little). Mix that with the privacy benefits and suddenly it makes a lot of sense.
asdff 14 hours ago [-]
Seems everyone in this thread is assuming I am saying go to private third party compute. No. Build your own cluster on metal you own on property you own, and have your team use that and just some thin clients to write with. Your compute goes way further. Your cluster can be going 100% of the time with jobs queued up by your team. All that memory you buy for your team in macbooks is idle and unavailable when your employee closes the lid and tosses it into the bag into the car on the way home. It could be used 24/7. On hardware you own. For cheaper to build I'm sure than apple hardware tax. On easier OS to manage and no doubt deal with anything involving any sort of heavy compute work than OS X. Are we really going to waste resources with docker when we could be using a node completely? Come on.
Like I said, seems HPC is lost art. All four sub replies missed that in my original comment.
eddythompson80 10 hours ago [-]
Your main argument is about better allocation for that RAM, which only makes sense in the conditions of a shortage. If RAM is plentiful, like it’s bound to be once the datacenters craze is over, that argument becomes “why does every apartment need a washer/dryer when we can have shared washers/dryers in a common area that are being used 100% of the time”. The answer is “because we can and it’s not that huge of a difference” plus you can have both. Like you can have a server cluster for large batch jobs, and personal ones for personal use.
For individuals though, it’s the same reason plenty of people pay for the 2tb or 4tb SSD for their laptops or desktops even though NAS has been a thing for 40 years. Maintaining a “server” of any sort is a completely separate endeavor for most. Just like a NAS is a no-brainer for many and non-starter for many more.
flaunf221 8 hours ago [-]
RAM was dirt cheap before and yet until M3 Apple made laptops starting with 8 GB of RAM. Why do you think Apple will suddenly become generous later?
The problem with LLMs outside of server is that people typically have many devices. So you can run LLM on your laptop. You want to make a query from your phone. Start your laptop? You want to do something from your smart home? Start your laptop?
What about your partner? Will they need to buy another top of the line laptop for themselves?
Your kids?
Alternative to server is of course that everything will have over 100 GB of memory, eat battery like crazy, be dumber and slower than single server in your household.
4 TB ssd was like $300 until recently. Even if RAM prices were to go to previous values, I don't think AI capability will be any comparable. Besides you also need proper compute, unless you want your prefill to be snail slow.
eddythompson80 8 hours ago [-]
It has nothing to do with generosity. Apple (and other laptop and PC makers) just have different segments of the market that they catered for. Plenty of people use laptops just to browse the web. They didn’t need a lot of RAM. Those who needed the RAM (usually branded as pro-users or “creators” or engineers) always had the option to get more RAM both from Apple and others at a premium. It’s just that ~32GB was the upper amount for almost any use case. Why would Apple put 256GB or 512GB in every laptop back when there was no use case for it?
Every scenario you described applies the same to a NAS. What if you need a file from your phone? Open your laptop? What if your partner needs a file? Open your laptop? The answer to all of them is either yes, or they have it on their laptop/phone too.
Apple (and other laptop makers) weren’t charging $300 for 4tb even before the shortage. They realized that not everyone needed that and they way overcharged for that but still less than today’s prices. People who needed it bought it even though it would have been a lot cheaper for them to build a NAS. A current-gen M5 is perfectly capable of doing decent tk/s given enough RAM. In 2 or 3 years it would be even more capable, it just needs RAM.
Plenty of people will use clou hosted models like they do with storage today. Plenty of people will build home servers for AI. Just like plenty of people have home NASs. But the number of people who just want a large SSD on their laptop make the previous group a rounding error and those people would rather have a beefy laptop or desktop with enough RAM in it. If anyone can solve the Phone<->Desktop communication seamlessly it’s Apple after all.
Unlike storage however, a lot of people are now aware of how much data collection tech and AI companies are doing and the idea that AI models are training on their personal photos and prompts is deeply unappealing to many. With just storage, what could Google or Apple do? Certainly they wouldn’t just print your photos and put them in an ad or on their website. But with AI models, it’s a different equation
flaunf221 7 hours ago [-]
> Every scenario you described applies the same to a NAS.
No. Files are your property. Inference is a service.
There's also the fact that working with files over network is often ill-advised and borderline impossible for some workloads. Even when that NAS is connected over wire and not wireless. Meanwhile even if you're on so-so connection, LLMs work great.
eddythompson80 7 hours ago [-]
And storage can’t be a service?
flaunf221 6 hours ago [-]
A.
Like I said - unless you invented magical communication channel that will give latency and speed and and reliability of local NVMe drive to your remote NAS, no, remote storage can't replace local storage in full.
NAS is mostly good for backups, torrenting linux isos and serving them with Plex or Jellyfin. You are not installing software on your NAS instead of your machine. Or doing video editing. Or playing demanding games.
I have file server at home and I still have ~8 TB of storage in my desktop, of which at leat 3 TB I can't move out.
B. If I have 1 TB of my work files, my wife has 1 TB of her work files, that's 2 TB of total storage. If both us need LLM, it doesn't mean we need twice the LLM as one of us.
throwaway277432 10 hours ago [-]
It's investors making these decisions. They would rather have predictable cloud spend than trying any experiments with high cap-ex. Has been this way since AWS is a thing.
Not saying they're right.
monegator 10 hours ago [-]
yes. People do not read.
I agree with you, and i would like to set up a server at work for local inference but we simply do not have the knowledge, it's much easier to get a couple of AI Max machines that are good enough for me and the boss which i convinced on the good points on running clankers locally and be done with it (though my plan is to use the AI MAX machines to figure out what the infrastructure and workflow will look like, and at some point ask for the investment)
rick1290 10 hours ago [-]
this is neat. how has it been going with the ai max machines? also looking to do the same as id like to get ahead.
monegator 8 hours ago [-]
I don't know yet! The boxes have been sitting there for a while. It's been a crazy month with no end in sight.
throwuxiytayq 10 hours ago [-]
> but we simply do not have the knowledge
How is this literally even possible in 2026? In a thread about LLMs, no less?
monegator 8 hours ago [-]
assimilating knowledge still take time, i do not take whatever LLMs regurgitate at face value.
Then there's testing the approaches and see whatever sticks best.
All while you're actually doing your actual job
dansquizsoft 6 hours ago [-]
Yeah this is a wild take…
_ph_ 9 hours ago [-]
First of all, it seems to be possible to build a scalable cluster from TB5 Macs. They don't have to be on individual desks, they could be hosted in a data center.
But on the other side, equipping data centers was never Apples main business. Their approach to markets is to design products for the individuals. They also usually have very long time plans. Look at where the Apple Silicon today is and how long a path it took. What about the day, where at least a medium sized Mac becomes a great platform for running large models locally? Very easy to use, no setup, no privacy concerns. Also never worry about "tokens". You can then use AI as you use other local resources of the hardware you own today.
Gigachad 10 hours ago [-]
I don’t want it in my laptop, I want it in my mini server rack at home. I’m not running any of my personal data through an external service that is certainly collecting it as training data.
usrnm 9 hours ago [-]
I want it in neither my laptop nor my home server, which I don't even have, I want it in my phone or something even smaller. I understand that it's currently not possible, but this is the direction I want the technology to be moving into.
throwaway_new_1 9 hours ago [-]
Highly likely it will happen. But at that point the phone will likely just be a slab of display and not much of an interface. Everything is done through an LLM and showed on the display. Not sure if touch screen will even be required at that point.
bix6 17 hours ago [-]
People don’t want to send all their private company data to the model providers?
bronco21016 17 hours ago [-]
Because why not? If you can get unlimited inference with roughly Opus 5.5 intelligence for $10k that easily beats current API pricing. Like not even a question.
codebje 16 hours ago [-]
Distrust in allowing an unreliable vendor to control the fate of your business?
credit_guy 17 hours ago [-]
> I guess it explains the haste Anthropic and OpenAI are in to IPO, cash out and leave the the retail investor holding the bag.
I don't think so. LLM inference enjoys huge economies of scale. At no point in the foreseeable future will a local model be able to compete with a cloud model in terms of price. Local models will have the privacy angle, but very few people will be willing to pay top dollar for that. There will be some people, for sure, but the vast majority will just use cloud models.
dofm 5 hours ago [-]
> LLM inference enjoys huge economies of scale
Does it actually? Sure, it is operating at huge scale and this design choice allows enormous models (presumably enormous MoE models). But is it achieving economies of scale?
Economies of scale are rooted more in the idea of a profitable thing becoming broadly sustainably cheaper as the market grows, allowing cheaper manufacturing and further growing the market.
The big two or three LLMs are cheap because they are substantially subsidised by investor cash, and they are not profitable at all in any sustainable sense: the current pricing can only be sustained for as long as they can raise money, and the market will (and does!) shrink when it is asked to pay a less-subsidised price.
There appears to me to be no route to true profitability for this design strategy at all. Even the open weights router companies are downstream of largesse from state-affiliated companies.
bix6 17 hours ago [-]
Why do you need huge economies of scale though? For 90%? of queries a local model will be good enough?
seunosewa 9 hours ago [-]
You'll still need a cloud AI subscription for the remaining 10%, so you might as well enjoy the superior performance. If you're cost sensitive, models like Deepseek have you covered.
Rohansi 11 hours ago [-]
For inference alone they get far better utilization of the hardware because they can keep it fully loaded with maximum concurrency. Other than that they get to collect a lot of data for training.
Foobar8568 11 hours ago [-]
Well beside for roleplaying, local models are a bit useless, especially the ones running on end user class hardware.
Maybe when chip would infer at 10-20x the speed of a 5090 RTX, otherwise it's really..bad.
datadrivenangel 1 hours ago [-]
The larger Gemma4 and Qwen models are competattive with GPT3 / 3.5 maybe 4o, so you can run the original ChatGPT experience on a nice consumer device now.
Foobar8568 49 minutes ago [-]
I am using everyday Gemma4 31b and Qwen 3.8 27b + 3.6 35b MoE.
Beside the 35b, the others are too slow to do anything vs cloud models, unless you have a local B200+. And the Qwen 35b has the reasoning capacity of a 2yo doing maths.
I wasn't "impressed" with any models for coding until 1year ago, only then they started to be "usuable" with the fault that we know and still exists.
edot 17 hours ago [-]
Most people just Google something or use the free ChatGPT. They have no clue how the answers get there and frankly would be just as pleased with GPT 4o as they would be with Astra. Questions like “what does this light mean on my dashboard” or “which bidet is best”.
otabdeveloper4 4 hours ago [-]
> LLM inference enjoys huge economies of scale.
No, it's exactly the opposite.
The big money is in small(ish) but finely tuned for specific tasks models.
Whoever invents an app store for LoRA adapters will win this AI race.
gherkinnn 17 hours ago [-]
Normie queries can be handled quite well by Haiku 4.6 or whatever.
What new bike should I get? How should I rephrase this email? What to do about my persistent headaches? Recipes based on these ingredients?
tmp10423288442 17 hours ago [-]
Small models inherently have less pre-trained knowledge, which will hurt their performance on queries like this. Moreover a lot of queries benefit from doing web searches, especially if they need to respond to changing conditions such as your bike example. Now you have to send data through a data center anyway for good performance, and probably need to use an API if you don’t want your computer blocked. So what’s the point, when GPT Luna exists if you really want to get a decent model at a rock-bottom price?
mbgerring 7 hours ago [-]
I don’t need or want “pre-trained knowledge”, I need a computer program capable of searching the web, sifting out the garbage returned in the search results, and giving me a summary of the useful information it found.
ijidak 16 hours ago [-]
My guess is it will probably be both. There was a time when no one could envision computing without the mainframe.
In the mainframe's heyday, it was difficult to grasp a world in which compute became so dense and so cheap that it made sense for each individual to have all processing and memory on their desk, talk less of on their lap and in their hand.
Of course this time could be different. But, when we look at previous relentless progress in compute and efficiency, then also couple that with the breakthroughs AI itself unlocks, it's hard for me to imagine that centralized AI will meet both the scale and flexibility desired for all use cases.
Just as centralized compute never fully disappeared -- it took the form of client-server computing and the cloud, there's no question that centralized inference will continue to exist.
But it wouldn't surprise me if, ten years from now, 90% of global inference happens at the client.
While simultaneously, the 10% of inference that takes place in the datacenter is wildly lucrative and orders of magnitude greater than today.
Put simply: the inference pie may become so large that both client and datacenter win.
nxobject 7 hours ago [-]
> Put simply: the inference pie may become so large that both client and datacenter win.
Beyond inference, even local HPC or large in-memory workloads. Steve Jobs dreamed that the NeXT Computer could be used to cure cancer in a dorm room (whatever tha tmeans), and I guess a bunch of Mac Studios chained together wouldn't be bad for a lot of computationally tough biomedical "basic science" applications.
iAMkenough 16 hours ago [-]
Unless cloud PCs take off and kill "AI PCs" and the future of the end-user hardware market, I think it'll be a bit of both.
It'll become easier and more affordable to distill/train/optimize smaller local models to meet your specific work needs. Multi-agent efforts will orchestrate the balance between using on-prem hardware for most tasks, and then defer to cloud models for more demanding/edge-case tasks. Especially if an organization can manage what data is shared with which model, and most of their user base are everyday casual users.
I also expect cloud providers to eventually start charging different rates for on-peak and off-peak usage, which would incentivize running what you can with the local compute you have otherwise sitting idle across dozens to hundreds to thousands of machines in your fleet.
Anthropic just changed their policy to invalidate any unused credits without refund if you buy your API credits annually. I see that as a sign of unpredictable budgets for cloud models for customers.
I could be wrong and all your future hardware purchases for end-users will be thin clients, without the local processing capabilities of today's laptops and towers. I don't see the hardware manufacturers profiting much from that, but maybe we'll see more companies like AMD declaring they prioritize cloud compute customers over everything else.
With a hardware refresh for cloud computing every 3-5 years, we'll likely see today's compute hardware driving Opus and Sol available on the secondary market for companies willing to build more on-prem capabilities.
labcomputer 8 hours ago [-]
Eh, I don’t know about that. With current Sonnet API pricing, an M5 Max w/ 128 GB can break even in a few months.
Qwen flash-next is at least as good as Sonnet for my uses, and the speed is perfectly acceptable.
I really think the big labs are going to soon start feeling pricing pressure for everything smaller than Opus-tier models, and it will come for those next.
Gareth321 8 hours ago [-]
> Eh, I don’t know about that. With current Sonnet API pricing, an M5 Max w/ 128 GB can break even in a few months.
Only if you're comparing apples with oranges. There are no local LLMs at 128GB RAM which compete with Sonnet 5.5 intelligence. And the gap is a chasm when comparing against Opus 5.5, which is fast and cheap and plentiful on event he $20 subscription.
dansquizsoft 6 hours ago [-]
Don’t say it too loud, I’m planning some arbitrage moves in the future based on what I consider is the absolute wrong vibe on here that thinks local llms are going to dominate in the near future
otabdeveloper4 4 hours ago [-]
> that thinks local llms are going to dominate in the near future
People saying this actually know how to run local models.
People claiming otherwise are Claude customers who know nothing beyond its point-and-click interface.
Consider that fact.
jimmyjazz14 2 hours ago [-]
I think I agree but it will take some time before their gamble on local LLMs start to pay off and I don't think it will completely kill off Anthropic (though. I would question their trillion dollar valuation if I was not already).
leftnode 17 hours ago [-]
I agree with you, even if many of the pundits say that Apple was left in the dust.
At some point, the real cost of inference/intelligence is going to come due, and the existing open source models will be good enough for 95% of tasks users want (or training their own model(s) will be inexpensive for Apple).
Apple will be there, as usual, to provide secure, on-device, faster inference that the vast majority of their customers will be fine with. Let everyone incur the R&D costs.
user43928 7 hours ago [-]
The real cost of inference? It's dirt cheap.
Look at what it costs to serve Kimi K3.1 Pro on a B300. It suggests margins of 98-99% at API prices for OpenAI and Anthropic.
Should the shortages for memory and GPUs ever improve, this will only become much cheaper, won't it?
That said, R&D is another story.
nomel 19 hours ago [-]
Cloud compute has been completely commoditized. Yes, local models will get better and better, but I think for the vast majority it will continue to be both cheaper and more productive to use cloud based models, far into the future, where bulk purchasing, oversubscription, and discounted industrial electric rates can be taken advantage of.
Where I am, it's cheaper to purchase multiple claude subscriptions than it is for the power bill from running a local model. Factor in the hardware costs, and you're looking at a break over a decade in the future, for comparable cloud models. Yes, there's privacy, etc, but now you're down into fractions of a percent of users who care about the government reading the memory of their computer.
xnx 18 hours ago [-]
And if you're on a mobile device, any halfway powerful local model is going to cut your battery life way down.
nomel 18 hours ago [-]
Related, I tried Juggernaut XL (image model) on my iPhone, and ate 2% battery per image!
walthamstow 7 hours ago [-]
Gemma 4 E4B on Pixel 10 Pro is a great way to keep your hands warm in the cold
root_axis 2 hours ago [-]
We'll see. Hardware costs will remain prohibitive for years to come. Most people can't afford a 20k Mac.
bitmasher9 2 hours ago [-]
I think this AI chapter will conclude with hardware costs normalizing. Maybe it’s because the hyperscalers stop hyperscaling. Maybe it’s because manufacturers finally catch up to demand.
Afterwards we’ll have 128gb apples for under 10k.
jmyeet 33 minutes ago [-]
I believe this as well. There is an inbuilt market for local models. A big example is law firms for whom cloud models violate attorney-client privilege.
NVidia aggressively segments the market on VRAM. Apple’s shared memory model is a competitive advantage. Well, it will be when they hand the raw PFLOPS, which is coming.
walthamstow 8 hours ago [-]
The bigger question is whether consumer normies give a toss about AI. If they don't, and that's how it looks today, then Meta, Apple and OpenAI are all losing badly.
zaphirplane 7 hours ago [-]
Consumers don’t care about AI, where I am it’s used by school kids for the most mundane to the most useful, used by white collar in wide range of roles and used by blue collar for work.
swiftcoder 5 hours ago [-]
They definitely don't have AI use cases that exceed a $20/month subscription. Hard to justify the amount of RAM needed for local AI for a non-developer's level of AI usage
bradknowles 17 hours ago [-]
In the end, I think companies like OpenAI and Anthropic will be the nameless and faceless backend provider, and they will get decoupled from the users. At which point, if they haven’t already had their multi-trillion dollar IPO and everyone cashed out, I don’t think they’re going to.
Apple and Microsoft and other companies will own that front-end experience with the customer, and it’s not going to matter to most customers whose backend gets used for what.
jatindavis5 4 hours ago [-]
Apple's hardware dominance is untouchable.
Rover222 41 minutes ago [-]
Running local models on desktop hardware will always be behind the SOTA, and thinking that cutting edge models will lose value because people can run good models locally is kind of odd.
neilwilson 11 hours ago [-]
They'll win if they vertically integrate chip manufacturing - particularly the memory.
It's not as if they are short of money.
stingraycharles 11 hours ago [-]
Isn’t Apple already doing this? Or what kind of vertical integration do you see other than their unified memory baked directly into the CPU?
Or are you saying that Apple should become a memory manufacturer, rather than working with TSMC?
neilwilson 10 hours ago [-]
The argument is that suppliers will serve somebody else in a price battle. If you own the supplier then they can’t do that.
rapsey 10 hours ago [-]
Apple does not manufacture its products.
small_model 7 hours ago [-]
Not everyone can afford a top-of-the-line Mac and the electricity cost to run it is high. It will never run Frontier models, which you can use for the price of a Netflix sub.
Also a lot of people work from laptops and running inference on data centres for 10th of the price is a no-brainer. Local models are more of a niche and always will be.
MacBook Air + Claude max sub for 20 years would still cost less before a maxed-out Mac Studio makes sense (not taking into account running costs), even then it’s not a Frontier or as fast.
api 18 hours ago [-]
Take a look at how qwen3.8 27B compares on benchmarks to much, much larger models. A while back I called it the crow of AI models: paradoxically strong given its tiny size, like the brains of crows and other intelligent birds.
It's not comparable to huge models of course, but given the power/size ratio here it shows that serious gains are on the table for models that can run fast on a high-end laptop.
geniium 11 hours ago [-]
Yeah totally agree
A few years back we never thought open source llm would get as good and even the small and cheap model
Its good to have a race and such competition
mietek 6 hours ago [-]
Why doesn't Apple have their own fabs yet?
swiftcoder 5 hours ago [-]
Because fabs take years to spin up, decades to become competitive, and are a constant financial drain throughout. If (with great prescience) they started planning their own fab at the beginning of the RAM crisis, we should see Apple in-house RAM sometime around... maybe 2040?
mietek 2 hours ago [-]
I feel that with all the trillions Apple have lying around, they should've been thinking about their own fabs already when designing the first Apple Silicon chips.
aa-jv 8 hours ago [-]
Been using both DGXOS and MacOS for my local inference needs, and by far, NVIDIA's DGXOS is superior in every way. Apple have a long way to go to catch up on the tooling extravaganza that keeps the NVIDIA ecosystem vibrant and rewarding.
iknowstuff 17 hours ago [-]
This is a nerd fever dream. Yeah I’m sure people can’t wait to run local models on their iPhones.
mbgerring 7 hours ago [-]
Sometime I wonder if other people on this website lived through the same era of web applications as I did, where people built whole successful businesses on 3rd party APIs, that were destroyed overnight when the terms changed.
Yes, I promise you, there are many, many people who are hesitant to build anything real on the assumption that either Anthropic or OpenAI will continue maintaining their services as they are today in perpetuity.
dstu 3 hours ago [-]
Both the OpenAI and Anthropic core APIs have become widely supported standards, so any application you ship today on their models can be trivially ported to other hosted providers or to your own infrastructure if you want to own the whole stack.
I agree that it pays to be wary of the additional abstraction layers they offer that purport to make your life easier, but for anything running standard completion calls or the like, I don’t see why this needs to be a concern.
oneseventwonine 54 seconds ago [-]
I don't think API integration is the problem here. We also need evals that can be relied upon to measure the difference in performance.
jmuguy 17 hours ago [-]
For those of using AI day to day, not being beholden to the whims of Anthropic and OpenAI is definitely a dream scenario.
rapsey 10 hours ago [-]
You are just confirming his point.
asdff 17 hours ago [-]
iOS isn't exactly a distro you control either
bix6 17 hours ago [-]
Is Apple Intelligence not local models currently running on iPhones?
walthamstow 8 hours ago [-]
It's only running if people are using it
Gigachad 10 hours ago [-]
Some of it is local and some is hosted.
gherkinnn 17 hours ago [-]
You don't have to sell it as a local model. Sell it as offline capabilities. Sell it as private background processing while your phone is idle and plugged in. Sell it as un-enshittified LLM once Anthropic and OpenAI inevitably screw everybody.
esskay 6 hours ago [-]
It would be slightly ironic if they did win. They were incredibly slow to adopt AI, and even now what they shipped with Siri is incredibly poor. Having arrived late to the party they stumbled, lied to customers, mis sold a product, got sued for it and lost, and then ended up slapping a siri logo on gemini.
But the hardware. The hardware is fantastic for local LLM's, generative ai, etc. And they seem to maybe finally be waking up to that, in true slow sleepy Apple fashion.
If they'd been a bit quicker about it we could have a higher tier iCloud plan that included a chatgpt plus style setup with the "its private" marketing tag that cant be provided by anyone else. Instead we get Siri being slightly less useless than before.
amelius 8 hours ago [-]
> Apple, to me, is the winner in the end of this AI chapter.
Soon enough: "Claude, please build me a MacOS clone. Hell, copy the entire Apple ecosystem the way I want it."
amelius 7 hours ago [-]
> Apple, to me, is the winner in the end of this AI chapter.
Not if they can't sell anything because of ridiculous DRAM prices.
HPsquared 5 hours ago [-]
Just as long as they can secure some reliable RAM supply.
phyzix5761 10 hours ago [-]
Even with the haste the 7 Anthropic founders have to wait a whole year after IPO before dumping all their shares.
bushbaba 8 hours ago [-]
Hint. Thats been apples public strategy for about a decade.
ulfw 5 hours ago [-]
What M7 Max/Ultra chips?
lasky 7 hours ago [-]
100% this.
wickedsight 10 hours ago [-]
> Apple gets this and we'll see the result with M7 Max/ultra chips
I'm not sure which chip it'll be, but I now for sure I'm not buying new devices until the AI boom has somewhat settled and we kinda understand what we'll be using it for. Until then, every manufacturer will just be guessing what device to build and will be outdated within a few months.
criley2 5 hours ago [-]
Totally disagree. I do not think local models will displace cloud models any time soon, and I think distillation has been demonstrated to NOT have better performance and is LESS efficient. Chinese models use dramatically more tokens and time to achieve dramatically inferior results. Watching deepseek spit out 20M tokens when Opus solves in <1M is always an entertaining window into "efficiency" and "performance".
Local models literally cost more in electricity than using far more powerful cloud models cost in inference.
When your options are "dramatically drain your iPhone battery for substandard AI, or have instantaneous cloud AI with no battery drain" what do you think the average user will choose?
And that's before we discuss how ridiculous the pricing is for home hardware that has a chance of running a halfway decent model at a halfway decent speed. Residential electricity + overpriced underutilized hardware means you're going to pay 100X or more per token.
I think the future prospects for local AI are looking worse than ever. It will be far more expensive for a far worse experience for the foreseeable future. It will fill a privacy/control niche, but beyond that, it's not a serious option
bigyabai 19 hours ago [-]
Man, if all that makes Apple a "winner" then I'm dying to hear your assessment of Nvidia.
Factoring in the increased cost of memory, Apple's threatened service revenue and the stagnation of ecosystem products like the Mac and iPad, I think they have a really challenging future to navigate. The whole "sell people a B2C ecosystem" business model is more threatened than ever.
Danox 16 hours ago [-]
The design and engineering of memory is not more difficult than replacing Intel and Qualcomm, Apple certainly has the money, and they certainly have the engineering talent within the Apple Silicon design group. It took 13 years to replace Intel and six years to replace Qualcomm who has already warned their investors that they anticipate losing revenue in the near future. The question is whether or not they have the will to do so, money and engineering ability isn’t the problem, it is simply a matter of will. With CMXT coming online bigger and stronger.
I don’t think there will be a choice long-term for Apple the conditions of the market have changed, and you have to change with it or get left by the wayside. They have shown that they will adapt and they certainly haven’t wasted money like their tech competition over the years.
bigyabai 15 hours ago [-]
Difference being, Apple had experience designing CPU cores and wireless radios before ditching Intel and Qualcomm. The transition felt "magical" because it was a generally low-effort layer on top of a muscle that Apple had gradually built over time. Their design approach is not compatible with scaled manufacturing; Apple does not have experience manufacturing DRAM at all. They don't have their own fabs, nor could they bid on fab space when AI companies outspend them 10:1.
Apple would make more money investing in a CUDA-style architecture than they would by becoming a subsistance manufacturer for the pitiful margins of the iPhone, iPad and Mac.
mietek 6 hours ago [-]
Indeed, why doesn't Apple have their own fabs yet?
pen2l 19 hours ago [-]
The contrast I'm drawing is running these models locally vs on the cloud and how that would be a selling point well received.
bigyabai 19 hours ago [-]
I don't think that's materially different from what you can do with Nvidia and AMD GPUs, besides the fact that you're limited to Thunderbolt interconnect.
jmuguy 17 hours ago [-]
And that we don't want to carry a giant, hot, eGPU enclosure around with us.
Affric 17 hours ago [-]
Yeah, what apple have frequently got right is the actual product/UX.
Capability is one thing but a focus on the actual product, as an teleological destination that is built rather than something cobbled together as a solution to a problem about how to sell what you have generally has taken them the right way.
bigyabai 16 hours ago [-]
For all of those accolades, the Mac is still a minority player in every computer market. They're especially a non-entity in on-prem enterprise buildouts and datacenter construction, which is where the money is going right now.
It's nice to have these types of niches when they make you money. But the Mac isn't profitable like the iPhone is, and probably makes less money than the iPad does if you count aftermarket service sales. The further Apple drifts from their roots as a computer manufacturer, the more the Mac starts to look like a liability to them.
Apple's Last Stand is their prosumer segment, and once that's gone I don't think their vertical integration playbook gets them anywhere further. Their bottom line is dependent on finding new ways to make B2C profitable, which has resulted in subscription services like AppleTV/Apple Music/iCloud so far.
DrScientist 5 hours ago [-]
It has about 10% of the global laptop market - and that's growing - making it the 4th largest single vendor, and it has about 35-40% of the global tablet market.
That looks pretty healthy to me.
Note that because most enterprise software is now web based ( ie moved to the data centre as you have pointed out ) - a lot of the corporate Windows only lockin has gone - so I'm seeing a steady rise in Macs in business.
What's not healthy is the desktop market ( apple laptops outsell desktops like 10:1 ) - but that's whiles that's more marked in the Apple space, it's largely an overall market trend. ( Overall desktops are about 20% of total shipments ).
So Apple will only be in trouble in this space if the laptop ceases to become wanted - and that's all about the interface - some apps are better with keyboard and mouse/trackpad and a bigger screen. If all that goes away and we just talk to our computers then I'd argue that Apple are better placed than Lenovo to weather that one.
cyanydeez 18 hours ago [-]
Sure, all you have to do is use only what can climb the walled garden
mschuster91 8 hours ago [-]
> I guess it explains the haste Anthropic and OpenAI are in to IPO, cash out and leave the the retail investor holding the bag.
Anthropic and OpenAI want to exit because they know they have no moat... and personally, I believe that the sociopaths running the US at the moment want to provoke a great economic crash. The Evangelical ones because they want the armageddon [1], the rich fucks because they took the "you shall own nothing" part for real and want to be the new neo-feudal overlords. And the best way to achieve that is by tying everyone's retirement savings up into their bubbly assets and then crashing down the economy, leading them to buy up everyone's asset at fire-sale prices with the liquid cash they made during the exit.
You are crazy. Apple has no lift on AI local or otherwise. Local LLMs are a massive and stupid waste of yes YOUR time.
And Apple really wants to sell people who have no cred in the space their stuff because THEY have no cred in the space.
Its basically a club for stupid f**s
myphpgothacked 18 hours ago [-]
[flagged]
simonw 18 hours ago [-]
"Harbor is currently in a private preview under Apple’s Claris brand"
There's a name I haven't heard in a long time! Claris (always an Apple subsidiary, since being founded in 1987) renamed themselves to FileMaker in 1998, but apparently they rebranded back to Claris in 2019.
This could actually be interesting for "regular" people. FileMaker was great in enabling non-IT people and SMBs to develop custom software for themselves. Think HyperCard with tables.
Some of that software has been in use since the 90s and still works. Adding AI to the equation will empower a lot of people.
However, FileMaker is not really targeted at software engineers. In fact using it as a developer will likely drive you up a wall. It's things that feel totally fine to non-devs but completely insane if you're used to something else. E.g. I remember having to click a thousand GUI buttons just to edit a few lines in a script once (regular users just "record" them through the UI). It did all work fine though, very reliable.
They added some more developer-specific features later, but it took a long time. E.g. editing scripts as text(-ish) only came in 2015 (FileMaker 14) and an actual programming language in 2020 (JS, FileMaker 19).
eddieroger 2 hours ago [-]
FileMaker really could have had a moment when iOS devices took off since you could get a basically free native app just by having a database, but (I'd argue) got bogged down by poor pricing models. I would have loved to run it, but it's always been prohibitively expensive for anything not an enterprise, and now it's far too easy to spin up a CRUD API and call it a day.
oidar 18 hours ago [-]
If they keep Harbor under the Claris umbrella, that is a nudge that they are doing it for SMB market instead of the consumer market and it will likely be a onerous subscription to use it.
thibsrn 8 hours ago [-]
I have been using llama.app, which is the desktop interface built on top of llama.cpp by the same people. It is an alternative to Ollama that might interest people who want to switch given Ollama's reputation and previous decisions. Llama.app has a really clean design, an elegant and intuitive interface. But it's good to get alternatives as well, if Apple also gets into the game.
llama.app has a lot of similar problems that ollama has, but at least you can use the hugging face downloader with it.
That you can't configure the models independently is a glaring oversight. The alt-space to enter the chat window (at least on Windows) is awful and with no way to disable it I've resorted to just using the app as an easier interface to their downloader.
It does have a nice, clean UI and it doesn't hide the models behind some opaque identifier.
hypfer 5 hours ago [-]
I've instinctively downvoted, wrongly assuming that this is just someone shilling their own equally bad stuff, but the repo is https://github.com/ggml-org/Llama-macOS
Note that it is under the ggml-org. So that's at least not a third-party taking advantage of llama.cpp
With the clean landing page URLs, you just don't know. So GitHub is probably the best source to link
thibsrn 4 hours ago [-]
I add to dig a little bit to make sure it was made by the same people. They don't make it obvious. Here's an announcement below.
Llama.cpp is MIT licensed open source software - it’s intended for third parties to take advantage of it.
hypfer 4 hours ago [-]
This is just ragebait no one should interact with beside flagging.
iantpe 4 hours ago [-]
What I need most right now is a model like TypeSafe's Jev that can be built directly into the computer.
Jev allows for numerous small judgments: Is this email important? Which program should handle this request? Is this operation risky? There's no need for large LLMs to slowly generate long paragraphs of text; all you need is a fast, structured result that returns the message.
Having a local Jev-like model in the operating system for quick decision-making, and then calling the larger model when deeper thinking is needed, would be very useful.
In a way you want something like blackberry messenger, a centralised hub for all app messages, notices etc, and then JEV hooked into it as a traffic controller of sorts.
I wonder if there’s anything like that, perhaps on Linux?
233mhz 2 hours ago [-]
> There's no need for large LLMs
Do you know how big jev is? Decision models are small but the "smart" (aka useable) ones aren't that small.
gehsty 7 hours ago [-]
As models improve and hardware becomes more capable Apple are definitely well positioned.
I am super interested to see what the Apple silicon team can deliver when their full attention is turned to local LLM acceleration.
mark_l_watson 2 hours ago [-]
Their hardware is especially good for MOE models, less suitable for dense. I use Laguna XS 2.1 6bit and Qwen-3.8-next-flash 2.6bit most because they are MOEs and run efficiently. I love Qwen-3.7:27B but as a dense model I only use it in “run something and walk away” use cases: slow.
alex43578 7 hours ago [-]
I don't see any evidence that local models (able to run on truly consumer hardware, not a DGX or multiple GPUs) will close the capability gap in a meaningful way. I have powerful hardware (multiple $K in today's prices), and only recently has Qwen Next come even close to being "useful", rather than a curiosity.
But the problem is a $20 ChatGPT/Claude subscription utterly trounces it in usability, user experience, and performance. By the time we get Opus 5.5 at home, we'll be on like Opus 7 or 8, and I'd bet Sonnet 7 or 8 will dust whatever can be run on the base MacBook of that time. It's fine if people think local 5.5 will be good enough, but it just seems like as AI keeps getting better, you'd want to use the better tooling - nobody has decided a 2010 MacBook was good enough when the M1 came out.
SeanDav 6 hours ago [-]
2 things:
- As AI continues to improve, the gains will become increasingly incremental. This means that your local model will be almost identical in performance as the latest cloud version, for all but edge case problems.
- If your local model is good enough for your current needs, the only "tokens" you are chewing through are utility costs and asset depreciation. Relatively cheap. It is easy to overrun even 200 /month cloud models for serious AI use.
ben_w 6 hours ago [-]
> - As AI continues to improve, the gains will become increasingly incremental. This means that your local model will be almost identical in performance as the latest cloud version, for all but edge case problems.
How much is "good enough" depends what we want it for.
Right now, the vision which was presented as a joke in (AFAICT more than one project all called) vibeOS seems like it could be viable with better local inference… but that likely needs a few more 9s of reliability even relative to current SOTA models, and we might even never get there if smaller local models always produce code which big hosted models can find vulnerabilities in.
Same if you want home inference to replace hiring a professional lawyer, architect, tutor, etc.: even though the AI has been getting passing grades in the law and medical exams since the early days, whoever gives out public liability insurance probably want to see more 9s of reliability before giving the OK.
radlad 2 hours ago [-]
> It is easy to overrun even 200 /month cloud models for serious AI use.
Not with the tok/s I get. I'm on a 128GB M4 Max laptop, and the latency + lack of parallelized sessions means you can't get anywhere near as much use vs. cloud models.
EagnaIonat 7 hours ago [-]
> will close the capability gap in a meaningful way.
I ran OpenClaw in a VM on my mac a few months back, only using local models. It was painfully slow (no MLX) but what it created was on-par with Claude at that time too.
The models are certainly powerful enough, but the frontier models are more than just an LLM model in the back.
gehsty 3 hours ago [-]
The tension over local / remote is a tale as old as time in computing, when the technology settles down both will continue to exist with different use cases…
in 5yrs time running an M12 with a Bionic LLM Engine (or whatever they call it) may be good enough for a very very good AI experience. Enterprise / professionals will likely still pay for frontier models.
cribbles 6 hours ago [-]
I agree with you, fwiw, but Apple's own consumer hardcore is not the choice of metaphor I would go with here - the M1 MacBook Pro and the group of iPhones that came out around the same time were the exact moment when Apple devices hit a "good enough" asymptote for many people (myself included)
xdertz 4 hours ago [-]
If you are comparing pure quality sure but don't forget quantity. It is very easy to blow through a weekly quota in one day. Fully local means you have unlimited usage which is something no provider gives you on a subscription.
When comparing API prices and privacy concerns, local might win.
bearjaws 4 hours ago [-]
> Fully local means you have unlimited usage
20tk/s is not unlimited when you have a lifespan that isn't infinite.
Rover222 40 minutes ago [-]
Yeah I think it’s peak nerd bubble to think local models are going to wipe out the value prop of Anthropic.
willis936 7 hours ago [-]
The up and to the right trend faced issues with the end of Dennard scaling. The only way it continues is with irresponsible allocation of more natural resources to compute. I'd prefer my atoms not be turned into paperclips.
mycall 3 hours ago [-]
> Claude subscription
Not good for PII/PPI
mrtksn 6 hours ago [-]
Sure, Apple has an opportunity here but I have no confidence that they won't screw it up.
For starters, they need to let me get rid of their AI stuff and free up the space. Apple aggressively pushing their AI down the throat of their users means that they suck at it but trying to make it happen using their muscles in other areas.
Just like people figured out how to make their Android TV not suck, it suggests that some time it the future people can make their OS not suck and this will make macOS irrelevant if Apple doesn't fix it first. Unfortunately for Apple, they operate in a system where they must keep growing their numbers.
Such a great company, its a shame that they couldn't figure out this AI stuff. Fingers crossed that this tool actually fixes that by just giving up and let people do whatever they want to do as efficiently as they can on the brilliant hardware Apple creates.
ethbr1 5 hours ago [-]
I'd add to this that Apple's ability to support a third-party ecosystem with stable development interfaces to their hardware has been at best "mixed" over the years.
Especially in the modern era, the firmware/software side of macOS definitely doesn't seem like a priority.
jph 10 hours ago [-]
If you ask who would pay for Apple local models, I would. A Mac Studio high end 512GB costs ~$1000/month for 3 years versus my current run rate of ~$1000/month for five devs for Claude Ultra (or ~$10k/week for Claude Sonnet if I paid API rates rather than Ultra).
If/when Anthropic changes to pure API pricing, or for API-heavy projects, that's when I'd switch to more local models. Of course there are tradeoffs for speed, quality, upgradeability, etc.
I currently run a Mac with 128GB and qwen3.8:27b-mlx. It hits the heat limit of the Mac when working on a 200k LOC codebase for security auditing and hardening for many hours at a time. This isn't as strong/fast as Sonnet, to be sure, yet the cost is only $6K one-time plus the usual electricity, maintenance time, etc.
jmaker 9 hours ago [-]
$10k for Sonnet per week? How did you arrive at that number? It’s quite a huge inference volume. No consumer hardware will give you that level of latency at comparable cost.
$6k is not the only cost - electricity adds up over time. And hardware can fail, redundancy is priced into the token prices and subscription plans. Maintenance is mostly negligible, but some updates/upgrades might regress. There’s a lot to SRE to keep it running at that scale.
jph 8 hours ago [-]
> How did you arrive at that number?
I run "npx ccusage@latest weekly" and also spot-check Claude Code sessions via "/usage".
> No consumer hardware will give you that level of latency at comparable cost.
You're right. My belief is the frontier AI companies are currently subsidizing real costs for the purpose of rapid growth customer sign ups, and that in a couple years or so local costs will become reasonable, at least for full-throttle work that's queueable.
zaphirplane 10 hours ago [-]
you’d spend real money to save imaginary “if I used api” money. In real money you are
Breaking even in > 10 years,
in 10 years your 10 year old Mac will almost certainly be a relic for running cutting edge local models
What am I missing
jph 8 hours ago [-]
Break even is likely for API pricing versus local, at least within a couple of years or so IMHO.
For example one of the projects is a web app that's processing user input, making AI suggestions, generating reports, doing ongoing observability, and running batch processing overnight.
Claude currently does these via API pricing, not Claude Ultra personal.
jann 2 hours ago [-]
To be fair, having multiple Claude subscriptions is also against the ToS afaik, so you’d have a much higher run rate.
larodi 10 hours ago [-]
> if I paid API rates rather than Ultra plan
yes, but you pay the Ultra plan, that's the whole point, isn't it? Let's be honest also - qwen3.8:27b-mlx is nowhere near Sonnet, both in size and cap, and if you do $10k a week of usage, you should know that.
dgacmu 2 hours ago [-]
The 512GB server he specified would be running something more like qwen3.8-flash-next, which is probably competitive with sonnet 5 (but still loses to 5.5).
I've tried it out on a 512GB dram server with 2*3090s and it works really quite well. Draws enough power to cost something similar to Luna, though.
jwr 8 hours ago [-]
I've been running local models under ollama, then lm-studio, and now mtplx (command-line, from supervisord). I'd welcome a vendor-supported solution, if it doesn't turn into bloatware (like lm-studio did).
dawedev 4 hours ago [-]
[flagged]
KolibriFly 5 hours ago [-]
Calculate the total cost of two new Mac Studios with max memory and cables. For that budget you could burn tokens on cloud APIs for a long time or build a dedicated server on open hardware with clear server buses
tencentshill 3 hours ago [-]
Do you think the cost of cloud tokens will stay the same or go down over the next ~5 years? Not likely, especially as the big ones start IPOs.
CharlieDigital 31 minutes ago [-]
[dead]
DerDerDaIst 5 hours ago [-]
devise the cost by the burnrate with cloud ai and you know when you'll break even. Add a bonus for the privacy.
Another bonus: Here in Germany a huge chunk of the hardware cost can be deducted from the tax bill.
hello5010 5 hours ago [-]
> For that budget you could burn tokens on cloud APIs for a long time or build a dedicated server on open hardware with clear server buses
Let the market decide.
Seems like both enterprises and individual users are switching to local models.
To my surprise, people are willing to pay for privacy.
bel8 3 hours ago [-]
> Seems like both enterprises and individual users are switching to local models.
I know a total of zero and individuals or companies using local inference for their workhorse inference.
Local models are just not up to most tasks for now at least.
CharlieDigital 30 minutes ago [-]
I take poster's usage of "local" to mean "self-hosted" which would include Revolut switching to self hosted GLM (which I think we'll see more of)
_1 5 hours ago [-]
Two new Mac Studios come with privacy.
_pdp_ 6 hours ago [-]
That will be really cool. It is already possible though through Apple Intelligence. There is an open source app that already leverages that.
> Cluster for scale: “Connect two or more Thunderbolt 5-capable Mac computers and Harbor pools their unified memory into a single inference resource. Run models that exceed any single computer’s capacity, or serve more concurrent requests across your cluster.”
This seems like the main way it would differentiate itself over existing solutions like LMStudio etc.
waz0wski 2 hours ago [-]
This functionality was already available from several other apps such as Exo
This is what I've wanted for the last few years. I have played around with local models and had some success, but I don't want to deal with the hassle of setting up, updating, etc.
If all of this were easy, I would happily invest in new dedicated hardware to run it. This could be a full-blown Mac or it could be a souped up HomePod-type device, loaded with RAM. Better yet, make it a revitalized Matter-enabled Airport!
LeBit 10 hours ago [-]
MacMini with M7 Pro and 96G of RAM.
They are going to sell sure 10,000$ and you won’t need anything else for the rest of your life (if you are over 90).
Btw, llama.cpp with llama-swap ain’t that hard to configure if you have access to a potential LLM and have 5h of your life available to that task.
apparent 9 hours ago [-]
Yeah, I might dive in with llama.cpp at some point, but unless Apple censors the models I can choose I'd just as soon go with Apple's solution.
I also want something that integrates super easily with my iPhone and other devices, and hopefully Apple will make it possible to use my server as an intermediate fallback between my iPhone and their cloud models.
nkotov 2 hours ago [-]
I built out Infinity (https://infinitychat.app) for myself which does something similar. One click to download and run, compare models etc.
joenot443 2 hours ago [-]
This is an awesome looking landing page. Very aesthetic with lots of immediate examples of what it does.
mark_l_watson 2 hours ago [-]
I am on the waiting list. I have a new 64G mac mini and an older 32G model. The directions for setting up a distributed inference system aren’t too gnarly but I haven’t bothered. I will when I get access to Harbor.
I think it is a great joy to run most things locally, and still occasionally use the best commercial models when local will not cut it.
crossroadsguy 8 hours ago [-]
I hope it will be optional. This is too much to ask for on Apple platform. I recently had to install a 3rd party script to get rid of Apple's laregely useless AI stuff from my 5 year old mac and save more than a few GBs which I badly needed.
Running local models is already extremely easy.
I have a suspicion this app will be a way to add a too many gigabytes to the mac and of course like the Chess.app there will be no way to get rid of it. There are excellent cli apps/GUI apps like this https://github.com/ddalcu/mlx-serve - they are both cli and gui – and even its gui surprisingly nimble (I use this, but I am not related to the project). I am yet to try this https://github.com/ggml-org/Llama-macOS but I've seen only good reviews of it.
I also do not think Apple is doing it for the users who won't explore around. I can't wait to get off this operating system. Next time a friend travels to the continent I will explore getting a Framework laptop via them.
Insanity 7 hours ago [-]
“Extremely easy today” - to who?
Their customer base includes many non-tech people who don’t want open a terminal window or even know of what a “GitHub” is. And they probably would not trust it as much as an app build by Apple.
I agree it’s easy to run locally (although I do so on Linux), but what’s easy for the HN bubble and easy for the rest of population is not the same.
gizmodo59 18 hours ago [-]
I really want capable models local but it’s impossible for me to afford the hardware. If there is a magical way to run glm 5.3 without quantization at 80-100tps with a total spend of less than 10K I’d be happy but that’s impossible now.
maipen 18 hours ago [-]
$200 a month is only $2400 a year.
That’s 4.16 years until you spend 10k.
I don’t find it reasonable at all.
Subsidized Subscriptions or api for cheaper models, is the best value.
But the future of AI is so uncertain, regarding model sizes. I don’t think making huge hardware investments is reasonable for individuals.
EddieRingle 17 hours ago [-]
> $200 a month is only $2400 a year. That’s 4.16 years until you spend 10k.
I don’t find it reasonable at all. Subsidized Subscriptions or api for cheaper models, is the best value.
If you buy your own hardware, then after those four years you still have that hardware, and it likely still holds significant value. Plus you know the local model you're running today won't change or suddenly degrade in four months, let alone four years. Whereas after four years of paying subscriptions and API costs, you have literally nothing.
cadamsdotcom 16 hours ago [-]
Energy costs (including capex if you buy batteries or solar) complicate things.
SoftTalker 17 hours ago [-]
Four year old hardware has almost zero value.
ahknight 2 hours ago [-]
Still running models on an M1 Max, which is a bit older than that.
That statement made sense ten years ago, easily. Less now, though.
D13Fd 16 hours ago [-]
Please send me all of your 4090's.
argee 16 hours ago [-]
Oh? How come the four year old 4090 RTX cannot be purchased for less than (or even at) MSRP then? Can you buy me one? I'm willing to pay $500 even if it is worth zero in your eyes, that's a stellar deal.
Espressosaurus 16 hours ago [-]
Tell that to the 3090s still selling at $1500 how many years after manufacture, used?
LeBit 10 hours ago [-]
My 12 years old Xeon with 32G would like a word with you.
SoftTalker 24 minutes ago [-]
Sure, it has value to you, I'm the same. My main workstation is 10 years old. But try to sell it.
GPUs are holding value longer, for obvious reasons. But even a 5 year old PC or server will be out of warranty, full of NLA components, and will get pennies on the dollar of its original cost on the salvage market. Most businesses will have fully depreciated them and maybe expect to sell them for enough to cover the costs of disposal.
LeBit 10 hours ago [-]
You don’t get privacy at that price.
There is no ZDR at that price.
I would not let a non-local AI have access to my financial or health data.
ahknight 2 hours ago [-]
Conversely, can you trust a local AI's answers about such topics (being small models)?
ontouchstart 1 hours ago [-]
I am already doing 100% offline inferences and AI assisted coding with bespoke software developed with local models.
In my case it reached the recursive self improvement stage a few weeks ago. It feels like the early days of personal computing in the era of DOS and Apple II.
The hardware is already there. The only limit is product imagination.
ConfusedDog 1 hours ago [-]
Any blog post or information on how your setup looks like?
fridder 1 hours ago [-]
It will be interesting to see how this compares to things like oMLX
brainless 10 hours ago [-]
I really do not understand the value of running large models locally. I am absolutely fond of local models but for specific tasks. The agents need to do a lot of work in this case: orchestration, big or small model split of planning and work, split into small tasks, merging, etc.
LLMs with <30B parameter models seem like the sweet spot. I would rather focus on multiple tiny LLMs that are tuned to specific tasks (SQL queries, finance/accounting, backend/frontend dev, etc.).
For larger models, a $10-40 ish Neuralwatt/Opencode Go or any similar subscription goes so far for the average user that it is ridiculous. We are still in the "youth" era of agents. There are many patterns that work well with smaller LLMs. Or with a big-small LLM combination.
My context:
I own the tiny 16GB M4 Mac Mini and I use LLMs (coding agents) to build software and a few of my products use LLMs directly. Full-time user of LLMs, do not read or write code manually. I run the tiny Qwen series (<10B params) sometimes but a couple $20 subscriptions (Claude, Neuralwatt) take care of my full-time agent usage.
olowe 9 hours ago [-]
I can imagine a future where we look back at these times of relying on big opaque hosted services to run inference and find it quaint. Perhaps the same way nowadays we find it quaint that you couldn't always just compile software on a fanless portable computer.
How far away that is, or whether it will ever happen, I don't know. I agree though that the tooling is still so young it's hard to say what shape this type of computing will look like and therefore what kinds of resources will be in-demand.
Same context as yourself. I run 8 - 12Bish models locally on a 24GB M4 Macbook Air and also have a couple subscriptions (OpenCode Go, Mistral Pro) for access to DeepSeek etc. to power through yucky big bloated codebases at work.
phyzix5761 10 hours ago [-]
Privacy is a big reason to want to run models locally.
brainless 10 hours ago [-]
True that. But ZDR is also not that expensive. Although for many businesses, buying a Mac with tons of memory is not expensive. Running a dedicated agent on top of private data is certainly valuable.
bauruine 9 hours ago [-]
ZDR is just a "bug" or "rogue AI agent" away from being all data retention. ZDR is not for privacy but for corporations that need to check a compliance box.
nolist_policy 8 hours ago [-]
Openrouter now does CSAM scanning and retention on so called "Zero Data Retention" endpoints as well.
Yeah. I for example use local inference for tagging up my documents that I self-host in a local Paperless instance, and I don't really feel like sending my medical invoices to clammy Sammy.
tokioyoyo 10 hours ago [-]
Model/harness that runs locally, which you can connect from your phone to do non-dev queries (looking stuff up, recommendations, planning and etc.) can save ~$300/year on various subscriptions.
brainless 10 hours ago [-]
Agreed but I feel we will see even cheaper annual or prepaid options. Say, a $20 upfront and get the cheapest inference, comparable to Sonnet with subscription. For a personal assistant that can run on laptop and phone, these will be mainstream. $20 may last a couple months for vast majority of users.
WokeUp420 10 hours ago [-]
It's called privacy
ThePinion 10 hours ago [-]
I have the same Mac M4 16gb. Do you have the Qwen model assist the larger models for menial tasks/tool calls during coding it can handle? As in have them work in tandem to save on tokens/calls on the large models or are your local agents just meant for their own specific side tasks?
brainless 10 hours ago [-]
A mix of both. I have been experimenting building agents that focus on small/tiny LLMs. For example, I built a web-app prototyping harness which used Qwen 4/9B models but separate agents (tool calls, prompts and actual code to parse) for CSS management, TSX management, Router, state, etc. It used SolidJS only.
There was a task manager which was given context of the tech stack so it could split the incoming requests. Then branch out the tasks to appropriate agents. Combine the generated code - this was a file/module/import manager.
The other way is let tiny models (again I would use agents for different use cases) do the busy work - tool calling, finding evidence, etc. I usually setup agents to re-write tool call history and create fresh API requests without using multi-turn chat with tool call history.
rapsey 10 hours ago [-]
The addressable market is enthusiasts. The cheapest and least loyal consumer that exists. But I guess it is just a small side project for apple which is fine.
conductr 10 hours ago [-]
Idk. Once they say our AI app is facilitating AI needs of big number of DAUs, the stock price will likely go up even if there’s no revenue path. It’s a pretty tulip.
jmaker 9 hours ago [-]
When I hear Apple and AI, I think of Siri. And then of my attempts to use it in my smart home where it would turn off all smart sockets instead of turning on the lights in one room. Or its response latency. Or how I was excited about Apple Intelligence and then removed it completely and am hesitant to upgrade to OS 27.
I understand that we’re talking about local inference with an Apple inference engine for Apple Silicon uniform memory. And I know it’s a stretch of an analogy. But somehow I’ve grown skeptical of Apple’s AI capabilities. Not to say Microsoft’s or Google’s weren’t disappointing.
conductr 1 hours ago [-]
For me Siri hasn’t improved a bit since release and it’s just the fact that she can’t understand my voice/words. Constantly mishears or asks me to repeat things. I have a pretty “regular” or “generic” US English accent and other voice agents have no problem so it’s definitely Siri. So I have never really been able to ascertain if it’s any good without an acceptable interface. I bounce immediately when I encounter the friction of having to yell, try to enunciate differently, think how to word my statements, etc. It’s like ordering food at a drive thru that has a broken mic and speaker and the employee is distracted not even trying to pay attention to my order. All to say, the spirit of your analogy seems appropriate to me.
yieldcrv 8 hours ago [-]
subagents use mostly the same allocation of memory, so you can do orchestration and planning easily with many subagents just like you do with Claude Code with anthropic's cloud models
Pi has a subagents package to enable in its harness
nghiemphucminh7 10 hours ago [-]
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mgiampapa 19 hours ago [-]
I love that they are bringing Claris back for this. Moof!
platevoltage 19 hours ago [-]
I'm just learning that the Claris brand still exists.
MBCook 19 hours ago [-]
But you’re still in for a ton of pain if you want to run them headless right?
They desperately need to fix that.
ctkhn 19 hours ago [-]
It was pretty fast to get it set up. It could be better for sure, as it's not a first class concept the same way that it is in linux, but an hour of google search ai mode will get you where you need to go.
MBCook 16 hours ago [-]
I know you can set it up to make it seem to work, but from what I’ve seen people say over and over, it will eventually end up asking you some question through a dialog box. And you will have no idea that’s going on other than all work stops. And the machine seems locked up or something until you connect a display and find out it wants you to click OK.
It SHOULD be totally possible. But it fights you.
LeBit 10 hours ago [-]
The MacMini stays on my desk for that reason.
It’s too bad I cannot trust it to put it in my rack.
mingus88 19 hours ago [-]
How so?
MBCook 16 hours ago [-]
MacOS is a desktop OS. You really REALLY need to treat it like one.
Lots of things pop up and can’t be dismissed any other way than though mouse/keyboard on the display.
OS updated and wants to tell you it worked? No command line way to get rid of that. Program wants to do something and one of those system security prompts pops up (“BBEdit wants to access your Documents folder”)? Same problem.
You can set it to auto login and auto update and grant permissions and everything.
And then, one day, it will stop responding and you’ll have to hook it up and log in to see some pointless dialog that just wanted someone to click “OK”. And until you do no work gets done.
throwaway_new_1 9 hours ago [-]
The Mac Pro was discontinued at the wrong time. Or maybe just introduced at the wrong time.
pavlov 9 hours ago [-]
The Mac Studio is inheritor of the 2013 Mac Pro approach. Back then people still needed internal expansion slots, so it was just too early.
andy_ppp 7 hours ago [-]
I would be quite happy with an external box with no processor, no ports etc. (potentially HDMI out), just the GPU cores and plenty of memory. Then I can upgrade AI without the rest of the machine.
Of course Apple will not offer this.
pentakkusu 9 hours ago [-]
As a recent M6 Mac mini owner, HELL TO THE YEAHHH BABYYYYYYY
I use oMLX btw, on 32GB URAM, running Hermes with Qwen 3.6 @ 128k context window.
I realize I am a smalltimer but for general day to day sensitive agentic stuff, this is the entry point.
yieldcrv 8 hours ago [-]
if you're running qwen, check out what happens when you swap oMLX for kapitsa
its built just for qwen, healthy competition on tokens/sec
Maxion 7 hours ago [-]
What is the experience of these local LLM models on this type of hardware? what are they capable of ? what do you use them for?
pentakkusu 5 hours ago [-]
A-OK, I would say. The pinnacle would be that I managed to develop a purpose made android app for my 2016 Honda dash unit with Hermes.
Hermes runs my personal to-do, manages 2 calendars, triages forwarded bills via it's own email address, orchestrates my docker container fleet. It also tends to a partly botched llm-wiki, that is built on Obsidian.
pentakkusu 5 hours ago [-]
never heard of it, will check!
quaddoggy 16 hours ago [-]
After I think about it, this makes sense that Claris would tackle such a project under the auspices of Apple. They're a subsidiary so they can monkey around with this stuff without having to adhere to the draconian everyday operating restrictions of "Apple proper". Good on them if they can pivot into something that hews to AI.
nxobject 7 hours ago [-]
It's fun to think about Claris as the hobby "well, we'll see if it works out I guess, but no worries if not" brand. Perhaps "Claris Vision Pro" would have been less embarrassing for Apple. Hell, if they want to bring their car project back, "Clarismobile" would be hilarious.
kenferry 17 hours ago [-]
"Harbor is currently in a private preview under Apple’s Claris brand, but it seems likely that we’ll see it launch to the public in the weeks and months ahead."
Claris?? Ok, this sounds like it's just someone's personal project. Something like this that was actually going to ship would be in a different org.
JKCalhoun 15 hours ago [-]
That's okay. Wasn't the Graphing Calculator essentially that as well?
If true, it is an astounding story. That said, I'm happy to see that Apple ships a graphing calculator with macOS 27 (albeit, a different one). I may not use it much these days, but I have fond memories of it when I was in university.
liuliu 18 hours ago [-]
https://getlocalcode.app/ runs local AI models (larger ones of course, DeepSeek 4.1 Flash 1017) easy. You can download and try it now. The problem is elsewhere: you cannot find M5 Ultra that you can purchase and set it up today.
azuanrb 4 hours ago [-]
All this talk about Apple being the long-term winner in AI is putting an awful lot of faith in Apple. Siri is still about 1/10th as useful as ChatGPT on a good day.
It’s the “year of the Linux desktop” meme all over again. Any day now.
- From a happy iPhone Duo user
nier 12 hours ago [-]
(1) All the headaches of maintaining FileMaker Server on Apple hardware, (2) multiplied with the additional requirement to cluster devices, (3) but without users accustomed to the silliness of misusing consumer devices running a consumer operating system for a service that must be reliable, and (4) an Apple subsidiary unable to bring about meaningful change.
they should add a sandbox for the agentic part as well.
so you can control and monitor what the whole setup is doing inside and outside the box.
w10-1 18 hours ago [-]
OMG after 25 years, Claris gets something beyond FileMaker (among the most legacy software still alive)? Claris would not have the engineering talent, so why would Apple use them as a vector?
detourdog 18 hours ago [-]
Currently FileMaker is a really expensive but sophisticated developer deployment environment. They stayed pretty true to the original vision in the mid 80’s when they merged their DOS database and added a gui layer for the Macintosh. I started on version 2 and it was at its best at when it went relational in version 3. Since then they have been focusing on deployment of graphical data applications and being a better database.
I'd absolutely use this; doubly so if there was a way to route traffic from your iPhone to it through iCloud. That might even get me to buy a second Mac just for server use.
nxobject 8 hours ago [-]
Developers! Developers! Developers! Developers!
ggcr 10 hours ago [-]
So many projects, start-ups and frameworks called Harbor already
sgt 3 hours ago [-]
Indeed, but practically you can just take any name unless any of the existing projects are seriously big.
zf00002 18 hours ago [-]
You can chat with the local model that ships with macos on your M1+ mac right now. There's a few servers on github that make it easy.
WillPostForFood 18 hours ago [-]
You can also "fm chat" in terminal
lethologica 18 hours ago [-]
Could you elaborate please?
asdff 17 hours ago [-]
Can you shut that thing off?
D13Fd 16 hours ago [-]
What would make running local models easy is being able to buy a Mac Studio without a 6-month delay :-(
api 4 hours ago [-]
What I’d like Apple Intelligence to be is this plus a good local app to chat with models plus an iCloud version of OpenRouter with privacy screening features.
Even better would be a peer to peer model hosting hardware pooling system but that’s probably too much to ask and would expose Apple to liability issues in some jurisdictions.
If Apple were willing to eat some margin on RAM they could use the present RAM bubble to gain ground in the hardware market too. Financially you could call it buying market share.
wewewedxfgdf 10 hours ago [-]
AMD needs Apple to kick it in the pants and make it realise they need to ACTUALLY compete instead of trying to just copy Nvidia.
wingi 7 hours ago [-]
what is the difference to ollama, lama.cpp ... ?
chews 18 hours ago [-]
Deepseek has found safe harbor!
amelius 7 hours ago [-]
Great, except with current DRAM prices nobody can afford it.
sleight42 10 hours ago [-]
An Apple M5 Ultra running an app like that? Because Apple hardware is a monolith, unlike the PC space, "Harbor" will be configured out of the box with the ideal settings for many well-known open-weight models.
... Looks like I picked the wrong week to buy parts for a linux-based inference box.
ankur_misra 39 minutes ago [-]
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axnli 4 hours ago [-]
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ravivarmat 7 hours ago [-]
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simli123 4 hours ago [-]
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ilkerguldali 19 hours ago [-]
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rickdg 7 hours ago [-]
MacOS is a bad server.
q4y2u35uk 19 hours ago [-]
Hopefully it won't be another preinstalled bloatware app like Image Playground. macOS enshittification has been greatly accelerating, even giving Win 11 Home a run for its money.
tonymet 17 hours ago [-]
Why so much investment in local models when the remote ones are so cheap ? Everyone was fine with remote compute & storage before AI, now they balk?
mbgerring 7 hours ago [-]
Some of us were never fine with remote compute or storage.
t-3 17 hours ago [-]
Cheap remote is probably not going to last forever. Memory prices will eventually drop. Local models will be more than enough for many purposes when the hardware is available cheaply enough.
tonymet 16 hours ago [-]
that's a lot of ifs / whens , and the remote models work right now, and are cheap. It's not a gym membership.
nier 13 hours ago [-]
People and organizations have requirements that their data stays on their devices or at least in their networks.
tonymet 12 hours ago [-]
i agree that's a benefit, but we've had that requirement for 40+ years and managed with cloud too.
nier 9 hours ago [-]
While I might imagine that there are customers who would store their data in the cloud but not necessarily run inference on it, there are also those who have strict rules against any cloud-based service. Those are the ones I’m talking about.
Distillation works: we can get models leaner, have better performance with lesser and lesser parameters, more efficient, running locally. Apple gets this and we'll see the result with M7 Max/ultra chips and I reckon this will be one of the titular apps when M7 line of chips are introduced.
I guess it explains the haste Anthropic and OpenAI are in to IPO, cash out and leave the the retail investor holding the bag.
I don't think it shows yet but I think the dominance of the App Store will end. I think a ton of iOS apps will be replaced by ChatGPT/Claude. I think there is a big opening for a company to redesign the phone from the ground up purely around an AI assistant instead of apps.
I think AI will severely weaken iOS, App Store, and the iPhone in the next few years. It was nearly impossible to start a 3rd competitor to iOS and Android until recently because no one is going to redesign their apps for your new phone. Today, that's different. Many productivity apps are just being replaced by GenAI/ChatGPT/etc and services are making it easy for AI agents to access directly without an app.
Not to mention higher chip prices will eat into hardware margins.
I do not think local LLM inference will make up for lesser iPhone dominance.
Commodities like todo apps and calculators rarely compete on features, they compete on product design. This includes look and feel, relation between elements, design choices on what exact common features are available.
All products are, at their essence, just a set of design decisions stitched and shipped together.
Now, making these design decisions is hard. It requires knowledge, consistency, and insights into how real people operate real products. Even as a sole user of the app you build you rarely know what you actually need.
LLMs are 'design-less' in their essence. Building your own todo app takes literal seconds and it all looks simple because LLMs will default most of these design decisions for you - until you try to use your new app daily and notice it somehow sucks. Building a good todo app or good calculator requires tweaking, publishing, polishing, and solving bugs, testing, rinse and repeat.
Another tricky side of this is that you might know logically what features you want, but you are not selecting one product over another logically. You need to try and see if that works for you, all the vibes and good parts and bad parts and design choices and colors, till you find something that "clicks" for you. Using pure Claude as a todo app only works as long as you want to have more Claude in your daily life.
In the meantime app store provides dozens of well-reviewed alternative solutions which look good and require zero maintenance.
And that's just a calculator or todo app. Non-commodity apps are even harder than that.
I don't see any future where programs follow the static nature of old paradigm programming. A nice intuitive UI? What about just telling the app what I need when I need it? The gold standard of consumer UI is...another person.
If I have a team of god tier light speed SWE's at my disposal, why the fuck am I fumbling around in an actions panel? The program can just be dynamically modified in near real time to be whatever I need it to be in that moment.
If you extrapolate LLMs out to their extreme, you get a shape-shifting liquid array of bits in memory that manifest anything at the behest of a completely natural language interface.
Absolutely not. Constraining the set of possible actions instead of having you verbalise what you want every time is often a feature, not just a technical limitation. A camera with a shutter button is better design than having to tell the camera “please take a photo”.
At the supermarket, I personally also prefer the self-checkout machines over going to a human cashier.
The UI is totally fluid at all times, because an "intelligence" is actively manifesting it at all times. Nothing needs to be hard coded.
Hell the computer might even see your face, see your age and style, and be like "Yup, this guy definitely wants to checkout with a dumb, midi keytone 8-bit styled program"
You're also assuming that there are no negatives to saying what you want compared to just acting on things, but since the beginning of computing many people have proven this wrong time and again. I suggest you read about HCI as a research field and its history, it doesn't take much to realise how limited the average HNer's understanding of UI/UX design is, and how far current LLMs are from the skills required to be able to carefully design an app for productive human use.
Good design rarely calls for a “you can do everything” approach. Good design is often context specific and subtly guides users to better outcomes.
Doctor appointments would absolutely suck if I had to navigate decision trees and click buttons to communicate my symptoms. Car blinkers would absolutely suck if I had to type “blink left” into a chat window before every turn.
I think it's better when you are at the origin, and the software branches off of your taste. For so long, we had to adapt and accept the ways of established software because it would take so long to make something of your own. Now it's both cheap and fast to iterate.
I dont think llms are going to replace banking apps anytime soon. But I no longer look for an app to pull data from my Peloton app into another exercise app. LLMs can build an app or a script that will do that and I wont have to pay some annual or monthly fee. It feels like these types of apps are going to die off.
However, you could expect LLMs to train on existing successful apps and hardened design patterns that compose well into good UIs. In that case, you might expect the last mile polish to be the differentiating factor. However, the more marginal this last mile becomes, the more other social, political, business, etc. forces will determine which app rises and which falls. But this has always been the case, certainly in software.
For instance; I don't think LLMs will be replacing Spotify, Facebook, Insta, or Youtube for my parents. They absolutely do not want to purely interact with a blackbox. They want to scroll through songs/shows/etc. they want to tap on it, and have the app do the thing.
Even as a SWE, I have absolutely zero desire to interact with an LLM for everything, but I'm not the litmus. I have found use with these tools for taking on some nested set of tasks, but at no point do I want to give up the app entirely.
For people who like shopping (not me!), most of it is actually browsing and there is a joy in sifting through options. The OpenAI designers seem to understand this.
I think folks who live in spec-driven worlds just don’t appreciate how poorly understood the capabilities and processes of computing and networks are, to the point where even if you gave people hallucination free LLMs you’d probably find people just frustrating themselves because they can’t figure out what they want, what it should do, and how it should be used.
Quite apart from the huge chunk of the app ecosystem that relies on common protocols, centralised services and so on.
I have seen this with yet "AI-unexperienced" users - for simple questions or textreformating, they are absolutely fine with the Chatbots. But thats all they can get out of it: Above that level their experience is very often frustrating due to too less understanding while having high expectancy towards the model in reverse (like "its AI so it should know...")
And this people end up then not using any of the AI tools beyond that because they do not "believe" / trust that this thingy can get work done.
* Based on our music discussions, make a playlist for me in Spotify. No songs older than 15 years.
* Look through my email, find all my receipts, show me a graph of my spend and categorize them.
* My business needs warehouse space. Find warehouse services within 15 miles of San Francisco. Ask them for their pricing and capacity. Here are pics of my items. Send these pics to them for quote.
* Find a hotel for me in Los Angeles on October 1st to Oct 5th. 4 starts. Max $200/night. Gym is a must. Don't care about pool. Close to airport. I have Platinum membership with Accor so try to find Accor hotels but not a must.
People do know what they want.
It is easy to express yes, but is this how people think about what they want to listen to?
Someone can already do this in a chat bot, see the list of things and then find it on Spotify or whatever their favorite music service is.
What the chat bot won't know is what they have listened to, which is probably a much higher predictor of what you'd like than the discussions you've had about music. You've probably had those discussions because you are already listening to that music!
I thought the parent's point is that the App Store will loose dominance (because you won't need apps).
Essentially every single non-builtin app on my phone fundamentally requires the internet to work, and is backed by some sort of SaaS with a proprietary API. And even if/when the APIs are open, I doubt any normal person is going to decide that from now on they want to somehow use YouTube or Tiktok or Feeld or Spotify by talking to ChatGPT.
Spotify is an interesting one. I could see myself wanting to control Spotify with my AI agent.
And that's the issue, each app maker will simply integrate AI themselves with their proprietary API rather than allowing ChatGPT to take their lunch.
IE. I want to stay inside ChatGPT/Claude.
I think Spotify will open up. Or some AI-native music service will be started to compete and fill the demand.
I've played around a lot with using my own AI to generate music recommendations and build playlists.
> I don't want to use Spotify's AI. I want to use my own AI, who knows me more
It's pretty tough to beat what Spotify (or Apple, or whatever your platform is) knows about you w.r.t. listening habits and preferences. My successful experiments have involved exporting Spotify / Apple Music data into sqlite and a skill that tells my agent how to query this data.
It works pretty well! Still, I'd say it's only roughly on parity with the AI stuff Spotify is working on. The main benefit to rolling my own is being sure (at least, for now) that the recommendations aren't being corrupted by sponsored placement which I'm sure is Spotify's end goal.
I have no real point to this point, just blabbering. Have you cooked up any good solutions via rolling your own?
I also think you’re way overestimating (based on one datapoint?) the number of people who want to use their devices from within an LLM chat app, even if at some point they should become aware of the idea.
I think they would really like to have one unified, plain-language interface.
Nice username btw.
Only if structurally it makes sense. There's demand for many many things on this planet without a business model that would satisfy that demand.
If Spotify won't do it, then maybe Apple Music might. Youtube Music might. Tidal might. Deezer might. Or a new service might.
I can imagine trying 'I want to hear a techno song that goes umm tss umm tss at 140bpm" and it finds a few million.
In what way? To find recommendations? Or search for a particular track?
It only needs to be created once. You don't want a different UI every time you listen to something.
Sure, but I don't think it's usually the apps that people pay much money for. And on top of that, app store revenue is (from a rough estimation) 6-7% of total revenue (although it's high-margin). Apple would be entirely fine.
And if you're right that the phone of the future will be reimagined as centred around being an AI assistant: innovative device design, user experience, hiding technology, integrating software/hardware/cloud are all things that Apple is historically pretty good at (with hiccups and bad periods for sure, but other companies certainly aren't better in general).
~15-20% of Apple's total profits at ~75% margin.
Investors are not going to like if that suddenly starts shrinking.
The other avenue that AI is hitting their services revenue is the Google Search deal, it's a revenue sharing agreement and AI is eroding that revenue on Google's side.
An LLM can probably whip up a music player app, but won't have the licenses to provide you the music.
An LLM can probably whip up someone akin to a free and single player Genshin Impact, but the whales want attention from other players.
An LLM can probably whip up some sort of SFTP from phone <-> Desktop for pseudo-cloud storage, but you still need to provide disk space
Why? Off the top of my mind (far from an expert and not thinking about it very hard), they can profit from AI in the following ways that have nothing at all to do with the app store:
For example if they capture 10% more of the global phone market because iPhones became that much better than alternatives thanks to AI integrations, that'd probably offset decline in app store revenue.Just throwing random ideas and numbers here, just making the point that shifting environment can weaken a revenue stream while strengthening (or enabling) others
To put it in perspective they reportedly collected about $675 million from OpenAI in fees last year, that's equivalent to about $1.5-$2 billion revenue in hardware sales and TBD for AI services but certainly over $1 billion.
https://www.macrumors.com/2026/03/20/apple-made-nearly-900m-...
Not to mention, Apple is going to want to not disrupt itself so they're going to deliberately slow down which opens up the opportunity for someone else.
OpenAI, Anthropic, and others can spend billions on the infrastructure to train the models at a time when the technology is still immature and largely inefficient and then Apple can simply license the models as needed, giving the user the choice while potentially protecting their privacy. Once there's relative maturity in the industry, they can either continue to license the models, distill their own from them, or even train their own using others' infrastructure. To me, it's a smarter long term strategy even if it temporarily gives up their control of key technology.
Personally, it seems to be the smarter play and aligned with how Apple usually does things. They're usually not first to market but they're first to introduce a refined product that make people forget about everything that came before it.
I get what Apple is trying to do. But it will still open them up to massive disruption and potential new entrants into mobile devices.
Therefore, I don't think they will be able to compete well in the new world.
Why this question? I don't think that the way that anyone expects Apple to profit off AI is from selling models
Do I want to set up my scale to sync its data to my vibe coded app? Not really. Do I want to set up the dozens of visualizations and hundreds of different actions and thousands of different items for calorie tracking, where even a 5% error is extremely significant? No way. Am I going to convince any of my friends to download my vibe coded chat application? Absolutely not. Do I want to store my photos in my own vibe coded solution and trust it to run in 20 years? Not a chance.
While a segment of apps will surely become obsolete, I don’t think the majority of users time will be spent on their own vibe coded replacements. Even as a developer I have no interest in turning all my conveniences into maintenance burdens, with risk of catastrophic failure
The issue is there will be less demand for apps. I don’t need to pay for a dulingo subscription when Claude can write a 5 minute language quiz for me. I don’t need to pay for Turbo Tax when Claude can prepare my tax documents for me.
Sure, it won’t replace all apps, but people will spend less time in apps and more time interacting with llms which hurts App Store revenue (Apples golden goose)
And it’s not like Apple is fixed. If this really did become a threat, Apple could surely integrate into Siri some ability to generate apps from your iPhone and put it behind their iCloud subscription.
They’ve had XCode for years, managed their entire UI library basically since conception, and have their own language for their apps. Fine tune DeepSeek for a while on swift iOS apps and I’m sure you could generate apps rivaling frontier models.
I really don’t see any existential threats for Apple here.
If Nvidia wanted they could end it overnight with a 60GB 6090.
Is this master stroke in the room with us now?
Now it can at maximum profit from it going public but not even that is sure now.
From what I have seen you belong to the vast majority. Though not here on HN.
What about doing something like REA on a whole app store collection, rewriting the app's reversed description set into code according the new devices' requirements? Perhaps we can't see the future as there are so many variations yet imagined.
We've already seen several attempts to make devices purely around assistants like Humane Pin or Rabbit. In 99% of cases users need a reliable screen with clear buttons not a conversational barrier between them and action
I personally didn't like the voice-approach of Humane Pin. Rabbit R1 was more interesting but execution was poor, screen was not big enough, models weren't smart enough, apps and services weren't as open via MCP as they are now and in the future.
I want to see a company like OpenAI or a very well funded veteran company give it a try.
To get something like this: https://www.youtube.com/watch?v=b9hxwgH2tN0
I don't know, I think there's 1 or 2 apps I might like that for, but for many, I think I'd run into trade offs I didn't expec and at a certain point I feel like I'd end up feeling like 'I wish someone would just do this for me'.
If the models would tell me no sometimes, I could see this working, but opinionated models would need to 'mesh' with your opinions right? So then we'd end up where software is now, just choosing the model we prefer, instead of the specific app. And then there will be times my preferred model isn't the right model for 'this' application, so now I'm juggling multiple model apps, and what did we solve exactly?
That's why I've been trying to do everything in Claude Code.
Would you trust access to your bank to a vibecoded phone of unknown origin? Backs will likely limit access as best they can for customer security. We already have banks who block GrapheneOS.
Look at the hardware wallet company that got sold and a spy chip to steal the contents was added.
I do believe AI is going to destroy companies like Adobe however.
Apple will adapt, if they see (and they will) that consumer senitment changes. Right now, 90% of regular "consumers" seem to despise AI and anything made by it.
This always puzzled me. Here's how that would go:
1. A new company, NeoPhone, launches that is redesigning a new "AI forward" phone.
2. The customers of that phone start noticing that they do many repetitive things with their phone, that they want the ability to design some repeat experiences with their chatbots. Call these repeat experiences "applets." Neophone ships some Applets on their phone that they created, a default set.
3. Customer A looks at customer B's phone, and notices their different applets that they designed. They work slightly better than customer A's applets, because customer B is slightly better at prompting.
4. NeoPhone notices this too. They create a new thing on their phone, the Applet store, where customers can share their applets and rate them and it surfaces the best ones to all customers.
5. Customers start complaining that they wish they had more creative control over Applets. Maybe the API is a bit more restrictive than they need, or the Applet needs to do special things with the phone's hardware, outside the context of the AI agent. Or they find that Claude Opus Fable 6.2 is better at making Applets even than NeoPhone's available chatbots.
6. NeoPhone allows 3rd party developers to develop on its phone, launching an "App Store" and a "Chat API" that is totally independent of the AI agent stuff.
???
Of course, Apple eats their lunch at step 2 or 3.
Sometimes even DoorDash gets it wrong, but at least I trust DoorDash to deterministically improve their systems so it doesn't happen frequently. With LLMs I would have to think that sometimes it just gets it wrong due to nondeterminism and insufficient reinforcement learning in the area of "reliable food ordering".
'Agent - file my tax return'.
In order to do that it's going to require you to have set up access to allow your bank accounts, shares holdings etc. etc.
Would you want to set that up to allow per task or simply always be in the background so if somebody hijacked your agent it could drain your funds?
[1] https://www.pewresearch.org/short-reads/2026/03/12/key-findi...
This is what we all want, this is what kicked off the open web back when the internet first started. This is what made everybody excited for user agents. Now we have user agents once more and we are getting excited about the new agentic web, but temper your expectations. This time, rent-seeking corporations are in it from the start, see the exact same promises that excited you about the open web, and plan to take full advantage right away. This is why everyone is trying to sell their own agent instead of giving access to your own.
They’ll be fine
If a new mobile device form-factor proves to be usable, they'll come out with one eventually like they always do- like the iPhone duo being years and years behind?
When the bubble pops they could still snap up an AI lab on the cheap later.
They wanted to keep everyone on their proprietary platform instead of enabling their devices to be used on the wider internet / being a more open mobile platform.
As long as apple allows some AI integration, then I think they'll be fine- and in fact I trust their privacy and security model more than if I bought a Google device. (not to say I trust anyone's security model, but it's clear that Apple has a more vested interest in security and privacy than Google does)
It'll make the iPhone look like Blackberry.
And let's say that Apple wants to respond with their own AI-first phone. But wait, they don't have the model. They don't have the compute. Most of their employees only know the old way of doing things. It'll be like GM trying to compete against Tesla or BYD in EVs. Their whole workforce and skills are in ICE.
Just simply because interfaces need to be crafted, and they're a design language that you learn over time. And most likely everyone needs the same things 90% of the time anyways.
When I step into my car I don't need the heating button to move closer if it's cold. I just want to learn where it is once and use it when I need to for x number of months / time of day.
That also goes for things like films and music - most of the time we actually want to be seeing and hearing the same things as everyone else (for some different definitions of "everyone"), not something that's made for us.
Generating a UI to solve a specific problem of yours is just an example.
I can't be the only one who has ever used an app and thought, man I wish they added this or moved the button to this, or fixed this stupid UI bug.
Please, no. Just TELL me; that's why I'm using voice to talk to you in the first place. Summarize and tell me, don't show me a list of links from a web search.....
However will they survive if they cede ground in commoditized consumer spaces to explore market fit in luxury goods?!
Please.
I want to see the projected numbers.
Huh? I just took a look at my phone -- I have about 100 apps on there, though probably only use 20 of them with any regularity. I don't see more than a small handful that could be replace with Claude (if it had access to the APIs that the app does),
And even then, a chat interface isn't the optimal way to interact with many services. Random example: A simple metronome / tuner. Could I ask Claude to play a tick at a certain frequency for X amount of time, or a E-flat? Sure. Would it be easier than using the app? No. Could Claude design a metronome app for me? Yes, but I don't want to have to deal with that process -- I just want a metronome app that works and I don't have to spend time designing or fiddling with, and that works offline, and all of that is well worth the $5 I might spend to buy it.
Literally nobody in the world wants more AI slop in their lives.
This is coming from my own experience as a software developer. I do not want to leave Claude Code. I'm hooking up everything into Claude Code and have it do what I want for me. I do not want to log into my cloud provider. I do not want to log into my Github. I don't want to log into any 3rd party services. I just want to stay in Claude Code.
I think developers tend to be ahead of the general public by 1-2 years in AI use. I imagine a future where most people simply want to stay within their ChatGPT/Claude/Muse/Grok/Gemini agent to do just about everything.
If my prediction is correct, I think Apple is going to be in trouble because it weakens the iPhone ecosystem severely and they are so far behind in AI everything that it's hard for me to see them ever catching up. Not to mention they do not have access to compute since they've not invested in compute.
It's competition.
Apple's use of Siri in Vision Pro is a good start, but there would need to be tighter integration w/ the UI. That's probably on the roadmap... assuming they continue to develop it.
I'm pushing the perennial 'developers (and engineers) think differently' trope here, but I think you're wildly optimistic.
The inability of the average person to write a detailed enough spec for implementation, compared to how trivial it is for an experienced developer, is mind boggling.
Imho, this is going to extend to agentic interactions with app-as-service-for-agent.
You don't magically increase customer experience by multiplying (garbage average user prompt) * (whatever agent they use) * (MCP, etc).
The first two variables are too unbounded.
I meant that non-developers will also find that staying within their AI agent to do what they want is better than downloading, logging in, learning different app UIs.
In our company, we recently gave Claude subscriptions to all office workers. They all hooked it up to their favorite tools already and they've been raving about it. It was a revelation for them.
In the past, you could look at a web page, see some structure, understand process, etc. and intuitively see and understand what you're suppose to do. When you remove all of that in favor of a text box, you spend a lot of time asking questions and prompting to get information or accomplish tasks that would otherwise have taken a minute or two and when you're done, you still don't understand how the underlying system, process, or policy is and how it works.
LLMs are getting exceptionally good at interpreting vague asks.
Do I trust a non-developer to build a production software system? No.
Do I think they can control Excel spreadsheets, PPTs, and other productivity tools through MCP? Absolutely.
One of the biggest issues I've seen in this kind of environment is that there are 50 dashboards, created by different people, and the data presented on them hasn't been validated to ensure that the data is correct and pulling from the same location. It's not clear that the data can be trusted and it's not clear what the authoritative source of truth is.
IE. They know what they're looking for. They know when the data is right or wrong because they've seen it from other places here and there over time.
When they're not sure and the risk of getting it wrong is costly, they'll find the data analyst to verify.
I've seen it firsthand, multiple time and while anecdotes aren't data, conversations I've had with peers at other companies suggest they have similar experiences.
Instagram, Tiktok, Youtube, you're right. So hopefully OpenAI can convince those companies to convert their apps over. Wouldn't be too hard given how easy it is to duplicate an app nowadays.
How much longer do you give until Claude Code replaces you entirely? Product or CEO dictate their wishes and Claude returns a freshly compiled binary and offers to deploy it to production with a simple "yes". A SWE salary seems like an lot of money for middlemen to pull lever on Claude Code.
That's why my investment strategy is centered around AI replacing me and making me unemployable.
Failing to evaluate AI beyond "slop" is down to a lack of imagination.
Could be the winner, in your opinion. They are extremely well positioned with hardware, devices, ecosystem, privacy, brand value & trust, and a significant active base. So far, they have not yet delivered on any useful AI application. There are so many opportunities in both MacOS and iOS, I guess they just need a new software VP.
So does Apple even need to create applications (that nowadays will get copied and opensourced in a day), or the hardware is the winning strategy in the end?
I think the more interesting question for Apple is the split between cloud and local. Economies of scale and aggregation vs privacy and ownership. I’d say so far it’s 2-1.
Who has? Google, Anthropic, OpenAI and Microsoft have spent hundreds of billions and produced nothing but chat apps that Apple could build in a few days, they’re all just interfaces to models that are available to Apple via an API. Hard to imagine Apple as anything but the winner of this era unless OpenAI or Anthropic pull something out of the bag.
None of that stuff has worked right for several years now apart from maybe Gmail.
> they are being inactive because they don't have the skillsets
Rare to see an argument that Apple can't hire talent.
They need a significant team creating their own model, (the talent of which has already gone elsewhere) and they also need to be working towards the future of photonic computing for running those models with success long term, again which will require a huge hiring effort. Considering it's clear they are not putting in that hiring effort it's obvious what work they have been doing.
This isn’t true they’ve literally launched Apple Intelligence with multiple apps and surfaces three times now and it’s flopped each time so badly they regroup and pretend it wasn’t the real launch then launch it again at the next WWDC.
You could spend it on free universal healthcare.
AI doesn’t have to be full-blown conversational AI.
In Photos, text recognition in Photos works well, object recognition and face recognition are somewhat decent.
In Mail, I find message summarization useful.
Small steps? Yes, but I think these are useful AI applications.
I do not use them, but in accessibility, they have AI applications to describe scenes which, I think, are useful to some.
Siri just got AI-fied and it's worse and slower than ChatGPT in 2022. Also it doesn't work offline anymore.
I used to "describe a shortcut" maybe 5 times this week and today I was hit with "you reached the limit". Mind you I have a 17 Pro and spend $120/year on iCloud.
These are useful applications of AI - or would be if they actually worked.
But this is all based on marketing not facts. Apple is as privacy invasive as the next guy. Obviously this shtick will work as long as marketing continues do to good job.
Right now 128GB MacBook is the top of the line and you could do Qwen 3.8 Flash or similar.
There is a rumor that the M7 chip can use 1.5TB of memory which would imply Apple is aiming for more memory on devices.[1]
Would that imply the entry-level MacBook will have 128GB and top of the line models could run larger reasoning models? Then the question is price and if any of this will translate to iPhone for on-phone models.
With how expensive memory is, IDK if they can pull this off but I hope they do
[1] https://www.tomshardware.com/tech-industry/semiconductors/ap...
Most people neither need nor want to run large LLMs locally.
The entry level MacBook Neo costs $599. Even if RAM prices revert to the pre-AI mean, the entry level models are not going to be that stacked with RAM.
Eventually we'll get to a doubling where entry level means 16GB of RAM, but most people won't be running anything more than simple models for light local work.
Have you ever tried running large LLMs on a MacBook Pro? It's hot, loud, and makes your battery level disappear at rates you didn't know were possible if you're not plugged in. It's a very niche hobby.
You can get uncensored versions, but they are less usable (lobotomized).
Personally, I find the whole idea of AI porn pretty depressing. Porn is very bad acting, or no acting, but at least the people are real.
Whatever local LLM device comes out of this, it certainly won't be a laptop.
(I envision a black box like a router you plug into a socket and let sit in a corner of some room.)
I'm old enough to remember the time when most people neither needed nor wanted a phone with a large screen and no buttons
If Apple, in 2030 has a compute product that a worker can BYO(X) to work that has 2TB RAM, with an encrypted personalized context that can float between agents, then they will be in a very interesting place.
holy shit
But the family shouldn’t be limited by that. We’re not going to see M6 Max hardware, because the M7 line is being fast-tracked and pulled forward. And I wouldn’t be at all surprised to see M7 capable of 1-2TB or more.
It is, at the very least, a practical limit. There are unlikely to be enough customers willing to pay $50k+ for a hypothetical 1TB RAM version to make it worth manufacturing.
Spoiler alert: they're supply-constrained too. Their customers will pay to outbid Apple, just like how Apple outbid the industry on TSMC's 5nm node.
i suspect that they will at least do offloading for casual usage as well. if they can ship 24GB in a homeview or appletv style product, it's game over.
why would a company who locks iPad Pro entry level literally out of ram that exists on its own chips.
I get their high end 10k-20k laptops will be able to reach these specs and gatekept behind also upgrading the cpu to the ultra but no way will it be an option in entry level.
Even so, DDR5 is so high-demand that it's likely that Apple can't outbid customers like Nvidia or OpenAI when they drive the margins they do.
Design, engineering capability and money are all a problem here, and the onus falls on you to prove otherwise.
I don’t think Apple can be in a position where all of the Chinese device-making companies can get memory at a significantly cheaper price from CMXT, and Apple is stuck with buying memory from the three hyenas of memory at a significantly higher price.
That’s not going to help Apple sell their devices at a competitive price worldwide over time against the Chinese computer makers (Lenovo, Asus, and Motorola) and make no mistake about it: their share of the market worldwide will get bigger because of this change in the memory market; their focus will be on the long term, while the lawyers/MBA/finance types in the West will have their heads stuck in the short term.
It’s the (Chinese companies’) opportunity, and they’re not going to let it pass; I wouldn’t. In addition, Apple is in competition with Nvidia, Microsoft, Intel, AMD, Qualcomm, Google, Meta, and indirectly with Anthropic and OpenAI (whose CEO, Sam Altman, recently declared that computer ram is wasted on low-level regular computer users), along with a whole legion of other 3D model makers on the procurement of memory.
The combination of all these elements going into the future means that if Apple wants to stay ahead, I believe Apple has no choice but to take memory in house, they have the design and engineering capability in-house, and they have the money because they didn’t burn it on AI models and data centers.
This scenario is no different than replacing Intel or Qualcomm; you can see the writing/destination and the ultimate train wreck up ahead if Apple doesn’t roll up its sleeves and get busy, the market has changed and again Apple has to change and adapt to the new conditions.
I wouldn't be surprised if that was happening already -- they plan five years ahead, after all, and they've been slowly taking other systems in-house (e.g. baseband/modem) already.
Why are you talking about memory? Nobody cares about memory. You know what people care about? People care about ballrooms, and you know what, the US has the best!
People who know ballrooms say the US is hot right now, hotter than anywhere else in the world, because we're building the best ballroom in the world. Can you imagine that? China is nowhere on ballrooms.
Probably sitting under a router, so that it can hand off bigger jobs to an Apple DC somewhere, probably with a certain number of credits based on your iCloud sub.
And with a device like this, you pay one single time to buy the product and then never have to think about paying for tokens ever again. For ordinary users that's silly, but for users or businesses chewing through lots of tokens, this means they can create their own turnkey replacement for "the cloud" where the only cost after purchasing the machine is the electricity to run it (which with these machines is very little). Mix that with the privacy benefits and suddenly it makes a lot of sense.
Like I said, seems HPC is lost art. All four sub replies missed that in my original comment.
For individuals though, it’s the same reason plenty of people pay for the 2tb or 4tb SSD for their laptops or desktops even though NAS has been a thing for 40 years. Maintaining a “server” of any sort is a completely separate endeavor for most. Just like a NAS is a no-brainer for many and non-starter for many more.
The problem with LLMs outside of server is that people typically have many devices. So you can run LLM on your laptop. You want to make a query from your phone. Start your laptop? You want to do something from your smart home? Start your laptop? What about your partner? Will they need to buy another top of the line laptop for themselves? Your kids?
Alternative to server is of course that everything will have over 100 GB of memory, eat battery like crazy, be dumber and slower than single server in your household.
4 TB ssd was like $300 until recently. Even if RAM prices were to go to previous values, I don't think AI capability will be any comparable. Besides you also need proper compute, unless you want your prefill to be snail slow.
Every scenario you described applies the same to a NAS. What if you need a file from your phone? Open your laptop? What if your partner needs a file? Open your laptop? The answer to all of them is either yes, or they have it on their laptop/phone too.
Apple (and other laptop makers) weren’t charging $300 for 4tb even before the shortage. They realized that not everyone needed that and they way overcharged for that but still less than today’s prices. People who needed it bought it even though it would have been a lot cheaper for them to build a NAS. A current-gen M5 is perfectly capable of doing decent tk/s given enough RAM. In 2 or 3 years it would be even more capable, it just needs RAM.
Plenty of people will use clou hosted models like they do with storage today. Plenty of people will build home servers for AI. Just like plenty of people have home NASs. But the number of people who just want a large SSD on their laptop make the previous group a rounding error and those people would rather have a beefy laptop or desktop with enough RAM in it. If anyone can solve the Phone<->Desktop communication seamlessly it’s Apple after all.
Unlike storage however, a lot of people are now aware of how much data collection tech and AI companies are doing and the idea that AI models are training on their personal photos and prompts is deeply unappealing to many. With just storage, what could Google or Apple do? Certainly they wouldn’t just print your photos and put them in an ad or on their website. But with AI models, it’s a different equation
No. Files are your property. Inference is a service.
There's also the fact that working with files over network is often ill-advised and borderline impossible for some workloads. Even when that NAS is connected over wire and not wireless. Meanwhile even if you're on so-so connection, LLMs work great.
NAS is mostly good for backups, torrenting linux isos and serving them with Plex or Jellyfin. You are not installing software on your NAS instead of your machine. Or doing video editing. Or playing demanding games. I have file server at home and I still have ~8 TB of storage in my desktop, of which at leat 3 TB I can't move out.
B. If I have 1 TB of my work files, my wife has 1 TB of her work files, that's 2 TB of total storage. If both us need LLM, it doesn't mean we need twice the LLM as one of us.
Not saying they're right.
I agree with you, and i would like to set up a server at work for local inference but we simply do not have the knowledge, it's much easier to get a couple of AI Max machines that are good enough for me and the boss which i convinced on the good points on running clankers locally and be done with it (though my plan is to use the AI MAX machines to figure out what the infrastructure and workflow will look like, and at some point ask for the investment)
How is this literally even possible in 2026? In a thread about LLMs, no less?
Then there's testing the approaches and see whatever sticks best.
All while you're actually doing your actual job
But on the other side, equipping data centers was never Apples main business. Their approach to markets is to design products for the individuals. They also usually have very long time plans. Look at where the Apple Silicon today is and how long a path it took. What about the day, where at least a medium sized Mac becomes a great platform for running large models locally? Very easy to use, no setup, no privacy concerns. Also never worry about "tokens". You can then use AI as you use other local resources of the hardware you own today.
I don't think so. LLM inference enjoys huge economies of scale. At no point in the foreseeable future will a local model be able to compete with a cloud model in terms of price. Local models will have the privacy angle, but very few people will be willing to pay top dollar for that. There will be some people, for sure, but the vast majority will just use cloud models.
Does it actually? Sure, it is operating at huge scale and this design choice allows enormous models (presumably enormous MoE models). But is it achieving economies of scale?
Economies of scale are rooted more in the idea of a profitable thing becoming broadly sustainably cheaper as the market grows, allowing cheaper manufacturing and further growing the market.
The big two or three LLMs are cheap because they are substantially subsidised by investor cash, and they are not profitable at all in any sustainable sense: the current pricing can only be sustained for as long as they can raise money, and the market will (and does!) shrink when it is asked to pay a less-subsidised price.
There appears to me to be no route to true profitability for this design strategy at all. Even the open weights router companies are downstream of largesse from state-affiliated companies.
Maybe when chip would infer at 10-20x the speed of a 5090 RTX, otherwise it's really..bad.
Beside the 35b, the others are too slow to do anything vs cloud models, unless you have a local B200+. And the Qwen 35b has the reasoning capacity of a 2yo doing maths.
I wasn't "impressed" with any models for coding until 1year ago, only then they started to be "usuable" with the fault that we know and still exists.
No, it's exactly the opposite.
The big money is in small(ish) but finely tuned for specific tasks models.
Whoever invents an app store for LoRA adapters will win this AI race.
What new bike should I get? How should I rephrase this email? What to do about my persistent headaches? Recipes based on these ingredients?
In the mainframe's heyday, it was difficult to grasp a world in which compute became so dense and so cheap that it made sense for each individual to have all processing and memory on their desk, talk less of on their lap and in their hand.
Of course this time could be different. But, when we look at previous relentless progress in compute and efficiency, then also couple that with the breakthroughs AI itself unlocks, it's hard for me to imagine that centralized AI will meet both the scale and flexibility desired for all use cases.
Just as centralized compute never fully disappeared -- it took the form of client-server computing and the cloud, there's no question that centralized inference will continue to exist.
But it wouldn't surprise me if, ten years from now, 90% of global inference happens at the client.
While simultaneously, the 10% of inference that takes place in the datacenter is wildly lucrative and orders of magnitude greater than today.
Put simply: the inference pie may become so large that both client and datacenter win.
Beyond inference, even local HPC or large in-memory workloads. Steve Jobs dreamed that the NeXT Computer could be used to cure cancer in a dorm room (whatever tha tmeans), and I guess a bunch of Mac Studios chained together wouldn't be bad for a lot of computationally tough biomedical "basic science" applications.
It'll become easier and more affordable to distill/train/optimize smaller local models to meet your specific work needs. Multi-agent efforts will orchestrate the balance between using on-prem hardware for most tasks, and then defer to cloud models for more demanding/edge-case tasks. Especially if an organization can manage what data is shared with which model, and most of their user base are everyday casual users.
I also expect cloud providers to eventually start charging different rates for on-peak and off-peak usage, which would incentivize running what you can with the local compute you have otherwise sitting idle across dozens to hundreds to thousands of machines in your fleet.
Anthropic just changed their policy to invalidate any unused credits without refund if you buy your API credits annually. I see that as a sign of unpredictable budgets for cloud models for customers.
I could be wrong and all your future hardware purchases for end-users will be thin clients, without the local processing capabilities of today's laptops and towers. I don't see the hardware manufacturers profiting much from that, but maybe we'll see more companies like AMD declaring they prioritize cloud compute customers over everything else.
With a hardware refresh for cloud computing every 3-5 years, we'll likely see today's compute hardware driving Opus and Sol available on the secondary market for companies willing to build more on-prem capabilities.
Qwen flash-next is at least as good as Sonnet for my uses, and the speed is perfectly acceptable.
I really think the big labs are going to soon start feeling pricing pressure for everything smaller than Opus-tier models, and it will come for those next.
Only if you're comparing apples with oranges. There are no local LLMs at 128GB RAM which compete with Sonnet 5.5 intelligence. And the gap is a chasm when comparing against Opus 5.5, which is fast and cheap and plentiful on event he $20 subscription.
People saying this actually know how to run local models.
People claiming otherwise are Claude customers who know nothing beyond its point-and-click interface.
Consider that fact.
At some point, the real cost of inference/intelligence is going to come due, and the existing open source models will be good enough for 95% of tasks users want (or training their own model(s) will be inexpensive for Apple).
Apple will be there, as usual, to provide secure, on-device, faster inference that the vast majority of their customers will be fine with. Let everyone incur the R&D costs.
Look at what it costs to serve Kimi K3.1 Pro on a B300. It suggests margins of 98-99% at API prices for OpenAI and Anthropic.
Should the shortages for memory and GPUs ever improve, this will only become much cheaper, won't it?
That said, R&D is another story.
Where I am, it's cheaper to purchase multiple claude subscriptions than it is for the power bill from running a local model. Factor in the hardware costs, and you're looking at a break over a decade in the future, for comparable cloud models. Yes, there's privacy, etc, but now you're down into fractions of a percent of users who care about the government reading the memory of their computer.
Afterwards we’ll have 128gb apples for under 10k.
NVidia aggressively segments the market on VRAM. Apple’s shared memory model is a competitive advantage. Well, it will be when they hand the raw PFLOPS, which is coming.
Apple and Microsoft and other companies will own that front-end experience with the customer, and it’s not going to matter to most customers whose backend gets used for what.
It's not as if they are short of money.
Or are you saying that Apple should become a memory manufacturer, rather than working with TSMC?
Also a lot of people work from laptops and running inference on data centres for 10th of the price is a no-brainer. Local models are more of a niche and always will be.
MacBook Air + Claude max sub for 20 years would still cost less before a maxed-out Mac Studio makes sense (not taking into account running costs), even then it’s not a Frontier or as fast.
It's not comparable to huge models of course, but given the power/size ratio here it shows that serious gains are on the table for models that can run fast on a high-end laptop.
A few years back we never thought open source llm would get as good and even the small and cheap model
Its good to have a race and such competition
Yes, I promise you, there are many, many people who are hesitant to build anything real on the assumption that either Anthropic or OpenAI will continue maintaining their services as they are today in perpetuity.
I agree that it pays to be wary of the additional abstraction layers they offer that purport to make your life easier, but for anything running standard completion calls or the like, I don’t see why this needs to be a concern.
But the hardware. The hardware is fantastic for local LLM's, generative ai, etc. And they seem to maybe finally be waking up to that, in true slow sleepy Apple fashion.
If they'd been a bit quicker about it we could have a higher tier iCloud plan that included a chatgpt plus style setup with the "its private" marketing tag that cant be provided by anyone else. Instead we get Siri being slightly less useless than before.
Soon enough: "Claude, please build me a MacOS clone. Hell, copy the entire Apple ecosystem the way I want it."
Not if they can't sell anything because of ridiculous DRAM prices.
I'm not sure which chip it'll be, but I now for sure I'm not buying new devices until the AI boom has somewhat settled and we kinda understand what we'll be using it for. Until then, every manufacturer will just be guessing what device to build and will be outdated within a few months.
Local models literally cost more in electricity than using far more powerful cloud models cost in inference.
When your options are "dramatically drain your iPhone battery for substandard AI, or have instantaneous cloud AI with no battery drain" what do you think the average user will choose?
And that's before we discuss how ridiculous the pricing is for home hardware that has a chance of running a halfway decent model at a halfway decent speed. Residential electricity + overpriced underutilized hardware means you're going to pay 100X or more per token.
I think the future prospects for local AI are looking worse than ever. It will be far more expensive for a far worse experience for the foreseeable future. It will fill a privacy/control niche, but beyond that, it's not a serious option
Factoring in the increased cost of memory, Apple's threatened service revenue and the stagnation of ecosystem products like the Mac and iPad, I think they have a really challenging future to navigate. The whole "sell people a B2C ecosystem" business model is more threatened than ever.
I don’t think there will be a choice long-term for Apple the conditions of the market have changed, and you have to change with it or get left by the wayside. They have shown that they will adapt and they certainly haven’t wasted money like their tech competition over the years.
Apple would make more money investing in a CUDA-style architecture than they would by becoming a subsistance manufacturer for the pitiful margins of the iPhone, iPad and Mac.
Capability is one thing but a focus on the actual product, as an teleological destination that is built rather than something cobbled together as a solution to a problem about how to sell what you have generally has taken them the right way.
It's nice to have these types of niches when they make you money. But the Mac isn't profitable like the iPhone is, and probably makes less money than the iPad does if you count aftermarket service sales. The further Apple drifts from their roots as a computer manufacturer, the more the Mac starts to look like a liability to them.
Apple's Last Stand is their prosumer segment, and once that's gone I don't think their vertical integration playbook gets them anywhere further. Their bottom line is dependent on finding new ways to make B2C profitable, which has resulted in subscription services like AppleTV/Apple Music/iCloud so far.
That looks pretty healthy to me.
Note that because most enterprise software is now web based ( ie moved to the data centre as you have pointed out ) - a lot of the corporate Windows only lockin has gone - so I'm seeing a steady rise in Macs in business.
What's not healthy is the desktop market ( apple laptops outsell desktops like 10:1 ) - but that's whiles that's more marked in the Apple space, it's largely an overall market trend. ( Overall desktops are about 20% of total shipments ).
So Apple will only be in trouble in this space if the laptop ceases to become wanted - and that's all about the interface - some apps are better with keyboard and mouse/trackpad and a bigger screen. If all that goes away and we just talk to our computers then I'd argue that Apple are better placed than Lenovo to weather that one.
Anthropic and OpenAI want to exit because they know they have no moat... and personally, I believe that the sociopaths running the US at the moment want to provoke a great economic crash. The Evangelical ones because they want the armageddon [1], the rich fucks because they took the "you shall own nothing" part for real and want to be the new neo-feudal overlords. And the best way to achieve that is by tying everyone's retirement savings up into their bubbly assets and then crashing down the economy, leading them to buy up everyone's asset at fire-sale prices with the liquid cash they made during the exit.
[1] https://www.theguardian.com/world/2023/oct/30/us-evangelical...
And Apple really wants to sell people who have no cred in the space their stuff because THEY have no cred in the space.
Its basically a club for stupid f**s
There's a name I haven't heard in a long time! Claris (always an Apple subsidiary, since being founded in 1987) renamed themselves to FileMaker in 1998, but apparently they rebranded back to Claris in 2019.
Looks like they've mostly just released annual upgrades to FileMaker for the past decade, but they did add MCP to it last year: https://www.claris.com/blog/2025/why-mcp-matters-for-claris-...
Some of that software has been in use since the 90s and still works. Adding AI to the equation will empower a lot of people.
However, FileMaker is not really targeted at software engineers. In fact using it as a developer will likely drive you up a wall. It's things that feel totally fine to non-devs but completely insane if you're used to something else. E.g. I remember having to click a thousand GUI buttons just to edit a few lines in a script once (regular users just "record" them through the UI). It did all work fine though, very reliable.
They added some more developer-specific features later, but it took a long time. E.g. editing scripts as text(-ish) only came in 2015 (FileMaker 14) and an actual programming language in 2020 (JS, FileMaker 19).
https://llama.app/
That you can't configure the models independently is a glaring oversight. The alt-space to enter the chat window (at least on Windows) is awful and with no way to disable it I've resorted to just using the app as an easier interface to their downloader.
It does have a nice, clean UI and it doesn't hide the models behind some opaque identifier.
Note that it is under the ggml-org. So that's at least not a third-party taking advantage of llama.cpp
With the clean landing page URLs, you just don't know. So GitHub is probably the best source to link
https://github.com/ggml-org/llama.cpp/discussions/23875
I have the same reflex as you, especially something hosted on a .app TLD, I instinctively think it's a copy of something else.
You can always check here on HN as well to get a sense of its authenticity: https://news.ycombinator.com/item?id=49267928
Jev allows for numerous small judgments: Is this email important? Which program should handle this request? Is this operation risky? There's no need for large LLMs to slowly generate long paragraphs of text; all you need is a fast, structured result that returns the message.
Having a local Jev-like model in the operating system for quick decision-making, and then calling the larger model when deeper thinking is needed, would be very useful.
dabbling with it in browsers but i expect it would answer the mail for you, if you find it accurate enough
Do you know how big jev is? Decision models are small but the "smart" (aka useable) ones aren't that small.
I am super interested to see what the Apple silicon team can deliver when their full attention is turned to local LLM acceleration.
But the problem is a $20 ChatGPT/Claude subscription utterly trounces it in usability, user experience, and performance. By the time we get Opus 5.5 at home, we'll be on like Opus 7 or 8, and I'd bet Sonnet 7 or 8 will dust whatever can be run on the base MacBook of that time. It's fine if people think local 5.5 will be good enough, but it just seems like as AI keeps getting better, you'd want to use the better tooling - nobody has decided a 2010 MacBook was good enough when the M1 came out.
- As AI continues to improve, the gains will become increasingly incremental. This means that your local model will be almost identical in performance as the latest cloud version, for all but edge case problems.
- If your local model is good enough for your current needs, the only "tokens" you are chewing through are utility costs and asset depreciation. Relatively cheap. It is easy to overrun even 200 /month cloud models for serious AI use.
How much is "good enough" depends what we want it for.
Right now, the vision which was presented as a joke in (AFAICT more than one project all called) vibeOS seems like it could be viable with better local inference… but that likely needs a few more 9s of reliability even relative to current SOTA models, and we might even never get there if smaller local models always produce code which big hosted models can find vulnerabilities in.
Same if you want home inference to replace hiring a professional lawyer, architect, tutor, etc.: even though the AI has been getting passing grades in the law and medical exams since the early days, whoever gives out public liability insurance probably want to see more 9s of reliability before giving the OK.
Not with the tok/s I get. I'm on a 128GB M4 Max laptop, and the latency + lack of parallelized sessions means you can't get anywhere near as much use vs. cloud models.
I ran OpenClaw in a VM on my mac a few months back, only using local models. It was painfully slow (no MLX) but what it created was on-par with Claude at that time too.
The models are certainly powerful enough, but the frontier models are more than just an LLM model in the back.
in 5yrs time running an M12 with a Bionic LLM Engine (or whatever they call it) may be good enough for a very very good AI experience. Enterprise / professionals will likely still pay for frontier models.
When comparing API prices and privacy concerns, local might win.
20tk/s is not unlimited when you have a lifespan that isn't infinite.
Not good for PII/PPI
For starters, they need to let me get rid of their AI stuff and free up the space. Apple aggressively pushing their AI down the throat of their users means that they suck at it but trying to make it happen using their muscles in other areas.
Just like people figured out how to make their Android TV not suck, it suggests that some time it the future people can make their OS not suck and this will make macOS irrelevant if Apple doesn't fix it first. Unfortunately for Apple, they operate in a system where they must keep growing their numbers.
Such a great company, its a shame that they couldn't figure out this AI stuff. Fingers crossed that this tool actually fixes that by just giving up and let people do whatever they want to do as efficiently as they can on the brilliant hardware Apple creates.
Especially in the modern era, the firmware/software side of macOS definitely doesn't seem like a priority.
If/when Anthropic changes to pure API pricing, or for API-heavy projects, that's when I'd switch to more local models. Of course there are tradeoffs for speed, quality, upgradeability, etc.
I currently run a Mac with 128GB and qwen3.8:27b-mlx. It hits the heat limit of the Mac when working on a 200k LOC codebase for security auditing and hardening for many hours at a time. This isn't as strong/fast as Sonnet, to be sure, yet the cost is only $6K one-time plus the usual electricity, maintenance time, etc.
$6k is not the only cost - electricity adds up over time. And hardware can fail, redundancy is priced into the token prices and subscription plans. Maintenance is mostly negligible, but some updates/upgrades might regress. There’s a lot to SRE to keep it running at that scale.
I run "npx ccusage@latest weekly" and also spot-check Claude Code sessions via "/usage".
> No consumer hardware will give you that level of latency at comparable cost.
You're right. My belief is the frontier AI companies are currently subsidizing real costs for the purpose of rapid growth customer sign ups, and that in a couple years or so local costs will become reasonable, at least for full-throttle work that's queueable.
in 10 years your 10 year old Mac will almost certainly be a relic for running cutting edge local models
What am I missing
For example one of the projects is a web app that's processing user input, making AI suggestions, generating reports, doing ongoing observability, and running batch processing overnight.
Claude currently does these via API pricing, not Claude Ultra personal.
yes, but you pay the Ultra plan, that's the whole point, isn't it? Let's be honest also - qwen3.8:27b-mlx is nowhere near Sonnet, both in size and cap, and if you do $10k a week of usage, you should know that.
I've tried it out on a 512GB dram server with 2*3090s and it works really quite well. Draws enough power to cost something similar to Luna, though.
Another bonus: Here in Germany a huge chunk of the hardware cost can be deducted from the tax bill.
Let the market decide.
Seems like both enterprises and individual users are switching to local models.
To my surprise, people are willing to pay for privacy.
I know a total of zero and individuals or companies using local inference for their workhorse inference.
Local models are just not up to most tasks for now at least.
https://github.com/pdparchitect/noodle
This seems like the main way it would differentiate itself over existing solutions like LMStudio etc.
https://exolabs.net
Although this might be the shortest timeline as-yet that Apple has "Sherlock'd" 3rd party apps
https://en.wikipedia.org/wiki/Sherlock_(software)
If all of this were easy, I would happily invest in new dedicated hardware to run it. This could be a full-blown Mac or it could be a souped up HomePod-type device, loaded with RAM. Better yet, make it a revitalized Matter-enabled Airport!
They are going to sell sure 10,000$ and you won’t need anything else for the rest of your life (if you are over 90).
Btw, llama.cpp with llama-swap ain’t that hard to configure if you have access to a potential LLM and have 5h of your life available to that task.
I also want something that integrates super easily with my iPhone and other devices, and hopefully Apple will make it possible to use my server as an intermediate fallback between my iPhone and their cloud models.
I think it is a great joy to run most things locally, and still occasionally use the best commercial models when local will not cut it.
Running local models is already extremely easy.
I have a suspicion this app will be a way to add a too many gigabytes to the mac and of course like the Chess.app there will be no way to get rid of it. There are excellent cli apps/GUI apps like this https://github.com/ddalcu/mlx-serve - they are both cli and gui – and even its gui surprisingly nimble (I use this, but I am not related to the project). I am yet to try this https://github.com/ggml-org/Llama-macOS but I've seen only good reviews of it.
I also do not think Apple is doing it for the users who won't explore around. I can't wait to get off this operating system. Next time a friend travels to the continent I will explore getting a Framework laptop via them.
Their customer base includes many non-tech people who don’t want open a terminal window or even know of what a “GitHub” is. And they probably would not trust it as much as an app build by Apple.
I agree it’s easy to run locally (although I do so on Linux), but what’s easy for the HN bubble and easy for the rest of population is not the same.
I don’t find it reasonable at all. Subsidized Subscriptions or api for cheaper models, is the best value.
But the future of AI is so uncertain, regarding model sizes. I don’t think making huge hardware investments is reasonable for individuals.
If you buy your own hardware, then after those four years you still have that hardware, and it likely still holds significant value. Plus you know the local model you're running today won't change or suddenly degrade in four months, let alone four years. Whereas after four years of paying subscriptions and API costs, you have literally nothing.
That statement made sense ten years ago, easily. Less now, though.
GPUs are holding value longer, for obvious reasons. But even a 5 year old PC or server will be out of warranty, full of NLA components, and will get pennies on the dollar of its original cost on the salvage market. Most businesses will have fully depreciated them and maybe expect to sell them for enough to cover the costs of disposal.
There is no ZDR at that price.
I would not let a non-local AI have access to my financial or health data.
In my case it reached the recursive self improvement stage a few weeks ago. It feels like the early days of personal computing in the era of DOS and Apple II.
The hardware is already there. The only limit is product imagination.
LLMs with <30B parameter models seem like the sweet spot. I would rather focus on multiple tiny LLMs that are tuned to specific tasks (SQL queries, finance/accounting, backend/frontend dev, etc.).
For larger models, a $10-40 ish Neuralwatt/Opencode Go or any similar subscription goes so far for the average user that it is ridiculous. We are still in the "youth" era of agents. There are many patterns that work well with smaller LLMs. Or with a big-small LLM combination.
My context:
I own the tiny 16GB M4 Mac Mini and I use LLMs (coding agents) to build software and a few of my products use LLMs directly. Full-time user of LLMs, do not read or write code manually. I run the tiny Qwen series (<10B params) sometimes but a couple $20 subscriptions (Claude, Neuralwatt) take care of my full-time agent usage.
How far away that is, or whether it will ever happen, I don't know. I agree though that the tooling is still so young it's hard to say what shape this type of computing will look like and therefore what kinds of resources will be in-demand.
Same context as yourself. I run 8 - 12Bish models locally on a 24GB M4 Macbook Air and also have a couple subscriptions (OpenCode Go, Mistral Pro) for access to DeepSeek etc. to power through yucky big bloated codebases at work.
https://openrouter.ai/blog/announcements/csam-screening/
There was a task manager which was given context of the tech stack so it could split the incoming requests. Then branch out the tasks to appropriate agents. Combine the generated code - this was a file/module/import manager.
The other way is let tiny models (again I would use agents for different use cases) do the busy work - tool calling, finding evidence, etc. I usually setup agents to re-write tool call history and create fresh API requests without using multi-turn chat with tool call history.
I understand that we’re talking about local inference with an Apple inference engine for Apple Silicon uniform memory. And I know it’s a stretch of an analogy. But somehow I’ve grown skeptical of Apple’s AI capabilities. Not to say Microsoft’s or Google’s weren’t disappointing.
Pi has a subagents package to enable in its harness
They desperately need to fix that.
It SHOULD be totally possible. But it fights you.
It’s too bad I cannot trust it to put it in my rack.
Lots of things pop up and can’t be dismissed any other way than though mouse/keyboard on the display.
OS updated and wants to tell you it worked? No command line way to get rid of that. Program wants to do something and one of those system security prompts pops up (“BBEdit wants to access your Documents folder”)? Same problem.
You can set it to auto login and auto update and grant permissions and everything.
And then, one day, it will stop responding and you’ll have to hook it up and log in to see some pointless dialog that just wanted someone to click “OK”. And until you do no work gets done.
Of course Apple will not offer this.
I use oMLX btw, on 32GB URAM, running Hermes with Qwen 3.6 @ 128k context window.
I realize I am a smalltimer but for general day to day sensitive agentic stuff, this is the entry point.
its built just for qwen, healthy competition on tokens/sec
Hermes runs my personal to-do, manages 2 calendars, triages forwarded bills via it's own email address, orchestrates my docker container fleet. It also tends to a partly botched llm-wiki, that is built on Obsidian.
Claris?? Ok, this sounds like it's just someone's personal project. Something like this that was actually going to ship would be in a different org.
https://www.pacifict.com/Story/
If true, it is an astounding story. That said, I'm happy to see that Apple ships a graphing calculator with macOS 27 (albeit, a different one). I may not use it much these days, but I have fond memories of it when I was in university.
It’s the “year of the Linux desktop” meme all over again. Any day now.
- From a happy iPhone Duo user
so you can control and monitor what the whole setup is doing inside and outside the box.
https://en.wikipedia.org/wiki/FileMaker
Even better would be a peer to peer model hosting hardware pooling system but that’s probably too much to ask and would expose Apple to liability issues in some jurisdictions.
If Apple were willing to eat some margin on RAM they could use the present RAM bubble to gain ground in the hardware market too. Financially you could call it buying market share.
... Looks like I picked the wrong week to buy parts for a linux-based inference box.