yesterday at 10:18 PM
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.
today at 10:11 AM
Apple, to me, is the winner in the end of this 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.
today at 11:44 AM
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.
today at 11:49 AM
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.
today at 12:43 PM
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.
today at 12:50 PM
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.
today at 11:54 AM
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).
today at 12:17 PM
Discovery I can see benefiting from AI, but surely using an agent to control basic playback would be a profligate waste of resources?!
today at 12:25 PM
I assume AI will generate a playback UI for you.
today at 12:53 PM
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.
today at 10:42 AM
> 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).
today at 11:34 AM
> 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.
today at 11:46 AM
all things that Apple is historically pretty good at
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.
today at 12:27 PM
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.
today at 12:35 PM
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.
today at 12:24 PM
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.
today at 12:26 PM
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.
today at 12:27 PM
> 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
today at 12:49 PM
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.
today at 12:45 PM
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.
today at 12:50 PM
But they're apps that your agent built, can change, and interact with.
today at 11:16 AM
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
today at 12:03 PM
> This is how Microsoft pulled off a master stroke with OpenAI and ChatGPT
Is this master stroke in the room with us now?
today at 12:46 PM
While I agree with your overall take that OpenAI is still struggling, this sort of meme comment isn't very interesting.
today at 12:37 PM
even if what you say is true, having the best phone for local inference would strengthen Apple's position not weaken it.
today at 12:09 PM
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".
today at 11:26 AM
Are you ready for a single app ( AI agent ) to have access and permissions on everything then?
today at 11:34 AM
Yes. I've been waiting for that day since ChatGPT first came out.
today at 12:10 PM
Yikes. That puts your original opinion into context quite a bit.
today at 12:14 PM
I probably represent the general public more than the elite 0.001% that is Hacker News posters.
today at 12:32 PM
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?
[1] https://www.pewresearch.org/short-reads/2026/03/12/key-findi...
today at 12:47 PM
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.
today at 12:36 PM
Yes. I do. Won't be in 2026. Maybe 2027 or 2028.
today at 12:21 PM
It’s already been shown that higher chip prices = higher prices to maintain margins
They’ll be fine
today at 10:45 AM
> 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.
today at 11:48 AM
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.
today at 11:59 AM
When the iPhone came out, did Blackberry have time to reinvent itself to compete against it?
today at 12:47 PM
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)
today at 12:59 PM
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.
today at 1:05 PM
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.
today at 11:22 AM
> redesign the phone from the ground up purely around an AI assistant
Literally nobody in the world wants more AI slop in their lives.
today at 11:31 AM
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.
today at 12:00 PM
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.
today at 12:02 PM
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.
today at 12:35 PM
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.
today at 1:00 PM
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.
today at 11:40 AM
> 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.
today at 11:43 AM
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.
today at 12:41 PM
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.
today at 11:45 AM
Went back and edited while you were replying. Sorry! Coffee still incoming.
today at 11:55 AM
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.
today at 12:46 PM
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.
today at 1:02 PM
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.
today at 8:05 AM
>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.
today at 8:22 AM
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?
today at 12:00 PM
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.
today at 10:34 AM
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.
today at 8:34 AM
> 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.
today at 8:45 AM
Apple have done nothing yet though so you can't be the winner without a product.
today at 9:42 AM
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.
today at 10:13 AM
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.
today at 9:30 AM
You can if the competition is "who burnt the least money?".
today at 10:14 AM
That shouldn't be the end goal of us as a society. Financial profit or loss.
today at 10:27 AM
And, hey, Apple has a sweet ~$52bil cash on hand, and has never been as gung-ho about stock buybacks as other companies.
today at 8:43 AM
> 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.
today at 9:23 AM
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.
today at 9:00 AM
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.
today at 10:04 AM
Arguably the only “useful AI application” delivered by anyone is Claude Code, and the jury’s still out.
today at 10:25 AM
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.
today at 11:19 AM
A good portion of the world’s population tends to find ChatGPT pretty useful…
today at 8:29 AM
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.
today at 10:42 AM
"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.
yesterday at 10:31 PM
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
[1] https://www.tomshardware.com/tech-industry/semiconductors/ap...
today at 6:27 AM
> 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.
today at 11:34 AM
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.
today at 9:25 AM
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.
today at 9:37 AM
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.
today at 11:26 AM
> 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.)
today at 7:35 AM
> 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
today at 8:16 AM
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 ...
yesterday at 10:51 PM
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.
today at 12:34 AM
Can you give a citation for your 2030 being 3 years away claim
today at 3:44 AM
2030.01 - 2026.92 ~~ 3.09 years
yesterday at 11:08 PM
> 2030 - that's a mere 3 years from now
holy shit
today at 6:55 AM
2038 is going to happen!
today at 1:33 AM
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.
today at 12:10 AM
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.
today at 12:54 AM
> 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.
today at 12:55 AM
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.
today at 1:06 AM
And given the pricing of the 512GB model over $20,000, I image a 1TB version would be $50,000+.
today at 2:08 AM
The last Intel Mac Pro could rock 1.5 TB.
today at 9:43 AM
[flagged]
today at 1:13 AM
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.
today at 1:54 AM
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.
today at 8:57 AM
They were in a cartel once before already...
today at 6:28 AM
> 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.
today at 1:11 AM
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.
today at 10:25 AM
> 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.
today at 6:31 AM
Why do you think the Chinese wouldn’t gladly sell Apple memory?
today at 7:53 AM
Aren't they on a sanctions list? Would the US government let them buy it?
today at 11:35 AM
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.
today at 8:07 AM
Depends on whether there will be a sane government anytime in the future.
today at 9:55 AM
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.
today at 10:22 AM
/does the hands up and then pulls apart gesture, purses lips
yesterday at 10:47 PM
Most likely Apple has been spending whatever they can to get in front of the memory market.
yesterday at 10:51 PM
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.
yesterday at 11:21 PM
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.
today at 1:19 AM
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.
today at 1:42 AM
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.
today at 12:39 AM
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
today at 12:46 AM
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?
today at 1:34 AM
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.
today at 12:53 AM
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.
today at 12:06 AM
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?
today at 12:45 AM
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.
today at 2:53 AM
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.
today at 7:11 AM
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.
today at 9:04 AM
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.
today at 9:30 AM
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
today at 10:10 AM
> 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.
today at 10:16 AM
And storage can’t be a service?
today at 11:02 AM
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.
today at 6:53 AM
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.
today at 6:50 AM
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)
today at 7:02 AM
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.
today at 8:49 AM
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.
today at 7:30 AM
> but we simply do not have the knowledge
How is this literally even possible in 2026? In a thread about LLMs, no less?
today at 8:47 AM
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
today at 11:32 AM
Yeah this is a wild take…
today at 8:33 AM
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.
today at 6:51 AM
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.
today at 7:44 AM
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.
today at 7:59 AM
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.
today at 12:33 AM
People don’t want to send all their private company data to the model providers?
today at 12:37 AM
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.
today at 12:43 AM
Distrust in allowing an unreliable vendor to control the fate of your business?
yesterday at 11:54 PM
> 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.
today at 12:19 PM
> 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.
today at 12:31 AM
Why do you need huge economies of scale though? For 90%? of queries a local model will be good enough?
today at 8:33 AM
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.
today at 6:23 AM
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.
today at 6:33 AM
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.
today at 12:17 AM
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”.
today at 9:11 AM
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.
today at 9:27 AM
> 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.
today at 11:34 AM
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
today at 12:47 AM
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.
today at 10:16 AM
> 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.
today at 12:34 AM
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?
today at 12:39 AM
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?
today at 10:16 AM
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.
today at 12:45 AM
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.
today at 9:46 AM
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.
today at 8:42 AM
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.
today at 9:51 AM
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.
today at 11:44 AM
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
yesterday at 10:31 PM
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.
yesterday at 10:52 PM
And if you're on a mobile device, any halfway powerful local model is going to cut your battery life way down.
yesterday at 11:10 PM
Related, I tried Juggernaut XL (image model) on my iPhone, and ate 2% battery per image!
today at 9:56 AM
Gemma 4 E4B on Pixel 10 Pro is a great way to keep your hands warm in the cold
today at 12:08 AM
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.
yesterday at 11:42 PM
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.
today at 10:16 AM
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.
today at 6:31 AM
They'll win if they vertically integrate chip manufacturing - particularly the memory.
It's not as if they are short of money.
today at 6:35 AM
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?
today at 7:37 AM
The argument is that suppliers will serve somebody else in a price battle. If you own the supplier then they can’t do that.
today at 6:43 AM
Apple does not manufacture its products.
today at 11:23 AM
Why doesn't Apple have their own fabs yet?
today at 11:42 AM
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?
today at 11:50 AM
What M7 Max/Ultra chips?
yesterday at 11:16 PM
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.
today at 5:42 AM
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
today at 10:05 AM
100% this.
today at 9:07 AM
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.
today at 12:00 PM
Just as long as they can secure some reliable RAM supply.
yesterday at 11:49 PM
This is a nerd fever dream. Yeah I’m sure people can’t wait to run local models on their iPhones.
today at 10:27 AM
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.
yesterday at 11:53 PM
For those of using AI day to day, not being beholden to the whims of Anthropic and OpenAI is definitely a dream scenario.
today at 6:44 AM
You are just confirming his point.
today at 12:09 AM
iOS isn't exactly a distro you control either
today at 12:34 AM
Is Apple Intelligence not local models currently running on iPhones?
today at 8:44 AM
It's only running if people are using it
today at 6:53 AM
Some of it is local and some is hosted.
today at 12:39 AM
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.
today at 10:11 AM
> 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.
today at 9:09 AM
> 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."
today at 11:29 AM
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.
today at 7:31 AM
Even with the haste the 7 Anthropic founders have to wait a whole year after IPO before dumping all their shares.
today at 8:50 AM
Hint. Thats been apples public strategy for about a decade.
today at 12:28 PM
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
today at 6:57 AM
> 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.
yesterday at 10:20 PM
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.
today at 1:30 AM
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.
today at 1:46 AM
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.
today at 11:25 AM
Indeed, why doesn't Apple have their own fabs yet?
yesterday at 10:22 PM
The contrast I'm drawing is running these models locally vs on the cloud and how that would be a selling point well received.
yesterday at 10:23 PM
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.
yesterday at 11:55 PM
And that we don't want to carry a giant, hot, eGPU enclosure around with us.
today at 12:10 AM
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.
today at 1:32 AM
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.
today at 11:46 AM
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.
yesterday at 11:16 PM
Sure, all you have to do is use only what can climb the walled garden
today at 9:05 AM
> 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.
[1] https://www.theguardian.com/world/2023/oct/30/us-evangelical...
today at 3:09 AM
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
yesterday at 10:56 PM
[flagged]
yesterday at 10:57 PM
"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.
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-...
today at 12:39 PM
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).
yesterday at 11:05 PM
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.
today at 9:16 AM
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.
today at 11:50 AM
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
today at 12:44 PM
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.
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.
today at 12:48 PM
Llama.cpp is MIT licensed open source software - it’s intended for third parties to take advantage of it.
today at 12:58 PM
This is just ragebait no one should interact with beside flagging.
today at 10:14 AM
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.
today at 10:30 AM
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.
today at 1:04 PM
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.
today at 11:07 AM
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.
today at 11:30 AM
> - 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.
today at 10:40 AM
> 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.
today at 11:15 AM
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)
today at 10:37 AM
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.
today at 10:41 AM
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.
today at 11:53 AM
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.
today at 12:24 PM
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
today at 12:29 PM
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.
today at 12:32 PM
> 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.
today at 12:29 PM
Two new Mac Studios come with privacy.
today at 10:57 AM
That will be really cool. It is already possible though through Apple Intelligence. There is an open source app that already leverages that.
https://github.com/pdparchitect/noodle
today at 8:51 AM
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).
today at 12:51 PM
[flagged]
today at 7:10 AM
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.
today at 8:10 AM
$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.
today at 8:48 AM
> 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.
today at 7:22 AM
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
today at 8:55 AM
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.
today at 7:20 AM
> 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 $10k a week of usage, you should know that.
yesterday at 11:16 PM
> Cluster for scale: “Connect two or more Thunderbolt 5-capable Mac computers and Harbor pools their unified memory into a single inference resource. Run models that exceed any single computer’s capacity, or serve more concurrent requests across your cluster.”
This seems like the main way it would differentiate itself over existing solutions like LMStudio etc.
today at 12:48 AM
This is what I've wanted for the last few years. I have played around with local models and had some success, but I don't want to deal with the hassle of setting up, updating, etc.
If all of this were easy, I would happily invest in new dedicated hardware to run it. This could be a full-blown Mac or it could be a souped up HomePod-type device, loaded with RAM. Better yet, make it a revitalized Matter-enabled Airport!
today at 6:41 AM
MacMini with M7 Pro and 96G of RAM.
They are going to sell sure 10,000$ 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.
today at 7:56 AM
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.
today at 12:19 PM
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.
today at 6:48 AM
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.
today at 8:25 AM
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.
today at 7:27 AM
Privacy is a big reason to want to run models locally.
today at 7:31 AM
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.
today at 8:14 AM
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.
today at 8:44 AM
Openrouter now does CSAM scanning and retention on so called "Zero Data Retention" endpoints as well.
https://openrouter.ai/blog/announcements/csam-screening/
today at 7:43 AM
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.
today at 6:55 AM
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.
today at 7:05 AM
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.
today at 7:02 AM
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?
today at 7:10 AM
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.
today at 7:39 AM
It's called privacy
today at 6:57 AM
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.
today at 7:28 AM
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.
today at 8:03 AM
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.
today at 9:13 AM
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
today at 7:24 AM
[flagged]
today at 9:40 AM
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.
today at 9:58 AM
“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.
yesterday at 10:24 PM
I love that they are bringing Claris back for this. Moof!
yesterday at 10:36 PM
I'm just learning that the Claris brand still exists.
today at 8:37 AM
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.
today at 9:11 AM
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
today at 10:36 AM
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?
today at 11:53 AM
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.
today at 11:49 AM
never heard of it, will check!
yesterday at 11:22 PM
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.
yesterday at 11:31 PM
$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.
today at 12:22 AM
> $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.
today at 1:00 AM
Energy costs (including capex if you buy batteries or solar) complicate things.
today at 12:40 AM
Four year old hardware has almost zero value.
today at 1:01 AM
Please send me all of your 4090's.
today at 12:56 AM
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.
today at 1:17 AM
Tell that to the 3090s still selling at $1500 how many years after manufacture, used?
today at 6:44 AM
My 12 years old Xeon with 32G would like a word with you.
today at 6:43 AM
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.
today at 1:24 AM
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.
today at 10:09 AM
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.
today at 6:55 AM
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.
today at 7:56 AM
The Mac Pro was discontinued at the wrong time. Or maybe just introduced at the wrong time.
today at 10:26 AM
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.
today at 8:02 AM
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.
today at 12:22 AM
"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.
today at 2:36 AM
That's okay. Wasn't the Graphing Calculator essentially that as well?
today at 7:34 AM
This is the story I read many years back:
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.
yesterday at 11:05 PM
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.
today at 12:43 PM
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
today at 5:29 AM
(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.
today at 8:31 AM
Sherlocking Exo, then--although that will work in a regular LAN as well. I should have finished https://rcarmo.github.io/projects/go-exotic...
today at 9:06 AM
Developers! Developers! Developers! Developers!
yesterday at 10:35 PM
But you’re still in for a ton of pain if you want to run them headless right?
They desperately need to fix that.
yesterday at 10:40 PM
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.
today at 1:32 AM
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.
today at 6:46 AM
The MacMini stays on my desk for that reason.
It’s too bad I cannot trust it to put it in my rack.
yesterday at 10:38 PM
How so?
today at 1:31 AM
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.
today at 7:02 AM
So many projects, start-ups and frameworks called Harbor already
today at 10:18 AM
what is the difference to ollama, lama.cpp ... ?
yesterday at 10:43 PM
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?
yesterday at 11:04 PM
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.
https://en.wikipedia.org/wiki/FileMaker
yesterday at 11:03 PM
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.
yesterday at 11:19 PM
You can also "fm chat" in terminal
yesterday at 11:24 PM
Could you elaborate please?
today at 12:10 AM
Can you shut that thing off?
today at 12:58 AM
What would make running local models easy is being able to buy a Mac Studio without a 6-month delay :-(
today at 10:11 AM
Great, except with current DRAM prices nobody can afford it.
yesterday at 11:17 PM
Deepseek has found safe harbor!
today at 6:50 AM
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.
today at 12:55 PM
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today at 10:11 AM
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yesterday at 10:20 PM
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today at 10:11 AM
MacOS is a bad server.
today at 12:13 AM
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?
today at 10:37 AM
Some of us were never fine with remote compute or storage.
today at 12:35 AM
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.
today at 12:42 AM
that's a lot of ifs / whens , and the remote models work right now, and are cheap. It's not a gym membership.
today at 4:01 AM
People and organizations have requirements that their data stays on their devices or at least in their networks.
today at 5:30 AM
i agree that's a benefit, but we've had that requirement for 40+ years and managed with cloud too.
today at 8:22 AM
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.
yesterday at 10:39 PM
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.
yesterday at 10:58 PM
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