Apple is actually interesting. They are one of the few companies with a chip / PC play with real power AND basically no play I'm the hyperscalar market.
That means they're actually incentivized at least short term, to benefit PCs becoming strong enough to do local LLMs. Which makes this play make even more sense. Though, I've been saying for a while that the local AI inflectiom point is the death knell for these frontier labs.
> Though, I've been saying for a while that the local AI inflectiom point is the death knell for these frontier labs.
"Death knell" is a touch hyperbolic. Hardware that can only run quantized models that take up GBs in VRAM falls short of even an A100 (by almost an order of magnitude[0]), which in turn falls short of what an 8xH100 cluster can do (also by another order of magnitude[0]).
I'm an avid believer in local LLMs, but I cannot deceive myself - data center accelerators will win on power dissipation numbers alone[1], even when giving generous allowances for higher efficiency on Apple chips - and assuming the Apple-efficiency advantage persists on the same TSMC process node.
0. Based on my unscientific fine-tuning training experiments across local and rented GPUs. YMMV for inference.
1. Unless Apple surprises everyone and brings back the XServe with M7, if not, then laptop and desktop for factors simply can't dump heat fast enough to compete head-to-head, and will be designed for lower input wattage.
Doesn’t need to be a winner head to head. If it can do 90% of the tasks the big boys do, at 50% speed, for virtually no extra overhead cost save for the power consumed by a prompt - that’s gonna work for a lot of people. And that’s also basically where we’re at today. Qwen3.6 35b running quantized on 10 year old hardware solves basically all of my uses cases for agents except for coding.
The frontier models are faster, and better at coding, but not so much that i’ll pay $200/month for them.
We'll likely see a transformation in how frontier models are trained as a result of a push towards local inference. While it seems unlikely now, given current pricing for RAM, in 10-15 years it's not unthinkable to assume we could see individual machines with 10-12TB (and well beyond that) of RAM which are accessible to the GPU. Min/max system RAM increased a LOT from 2010-2025 and largely because it was cheap. Once the hyperscalers aren't generating revenue for the RAM manufacturers, I wouldn't be surprised to see a massive push towards consumers in order to maintain gross profit. Not to mention new players who enter the market because the margins are measurably absurd right now.
At some point there will be diminishing returns towards the "just throw more RAM at it" approach the current frontier models are taking. Commoditization is just as inevitable as it ever was... and in doing so will enable actual leaps of what AI/ML is capable of. That's not to say there won't be a place for 99.999999% accurate vs 99.99999% but those cases will be limited and likely prime to disruption based on real innovation vs access to capital.
The established AI players have no financial interest to make LLM available locally. They aren't hardware companies and if running LLM requires paying them to host the models as well then they can naturally capture more of the value chain = more revenue.
Apple is the only player here where it would play into their natural hardware incentive to get you to pay more for better hardware. It would make sense for them to find a way to run LLM locally (eg, newer architectures that others here have pointed out).
Is it hyperbolic though? One of the best things about the compute and memory shortage is that people are going to insane lengths to optimize things to run on lower memory / lower compute devices. If we keep this up for a while and then ramp up memory and local compute production, that AI inflection point may actually come.
The big question for local LLMs is whether there is a 100 tok/s model which requires less than 16 GB of memory and is competitive on most tasks with the cloud models.
There is some signal that this is possible through both hardware innovation and training/data improvements.
Cloud models have their own constraints - I can’t have opus4.8 spend 4 hours on a deep research question I had in the shower without spending money. I can’t do real time video game upscaling and graphics work in the cloud period.
A laptop is about an order of magnitude cheaper than a cloud server thanks to economies of scale, uptime requirements, and other factors.
The thing is, with the level of hard investment AI vendors have, even a small reduction of their addressable market is significant. They aren’t profitable, and inference is getting commoditized fast, so even if they eventually become profitable (not via financial engineering) they won’t be able to have good margin. The pressure of both open models AND local models is pretty bad imho
> Hardware that can only run quantized models that take up GBs in VRAM
That's the today hardware.
Now suppose Apple goes to any of Samsung/Micron/Hynix and says "we'll pay you the entire cost of building another DRAM fab and in exchange we want its entire output" and then releases M7 devices with enough memory and compute to run bigger models.
> Unless Apple surprises everyone and brings back the XServe with M7, if not, then laptop and desktop for factors simply can't dump heat fast enough to compete head-to-head, and will be designed for lower input wattage.
Laptops maybe. Desktops can dissipate more heat than the amount of electricity you can draw from a typical household wall outlet.
Indeed. Local models becoming available and halfway decent don't obviate the laws of scale. And because there's no ceiling to what scaling more will buy you in terms of capability, there's no reason not to scale more, there's no incentive for billionaires not to grab all the fab capacity they can.
Enjoy paying $1000 or more for a little 4 GiB cloud terminal that connects you to all your online accounts where all your actual work gets done. This is the future.
It's plausible but is the Apple Tax for a 1TB memory machine on top of current memory prices really worth it? I paid around $4000 for 4090m laptop with 16GB VRAM back in 2023, it's great but DoA for even quantized LLMs. I can run SLMs and fine tune it but that's it.
We need one of those specialized inference chip startups to succeed and a PC manufacturer willing to bet on them against Nvidia for the local AI to find mass market appeal.
Tangential: About 8 years ago ex-Apple chip engineers left to design server-grade chips, this was Nuvia, and they got sued by Apple to the point that they had to get acquired by Qualcomm.
I worked at a hyperscaler when the M1 came out. A MacBook Air M1, running a Linux VM was faster and more energy efficient than anything we had in the data center.
They do stand in front of a great opportunity that would also benefit consumers, which seems rare in the llm era.
If people can get opus4.6/gpt5.5-like models locally, labs could raise their prices and sell token speed, better reasoning, mobile-focused improvements, you name it.
Not all consumers are power users and many will be happy to pay for flexibility.
>AND basically no play I'm the hyperscalar market.
I do wish they have Xserve back, or a Mac Pro that is Rack Based and support multiple node with M6 Ultra. The Hyperscaler market is so large along with AI their old business case of Xserve didn't make sense no long hold true.
768GB RAM pipe dreams make no sense to Apple. By discontinuing 256GB / 512GB M3 Ultra and raising prices $5000 -> $7000 on Macbook pro with 128GB they basically confirmed how badly RAM shortage affecting them.
768GB is 64-times of 12GB which is rumored to be amount of RAM in new iPhones. Imagine what profit margin 768GB Mac Studio gonna need in order to justify making one instead of 64 iPhones.
Apple is the company that is okay about selling microfiber cloth for $100 and wheels for $700. Imagine how bad price hike for M3 Ultra 256GB / 512GB had to be in order for them to just discontinue them instead of getting free money out of desperate local AI folks.
They could treat the extreme spec machines separately from the prosumer ones, like they did with the Xserve. Let business customers spec up to 768GB (say) who are prepared for a $20-25k price tag, while keeping them away from the stores and usual consumer supply chains (Amazon et al). It may not be a big enough market segment for them to care about anymore, though.
They can do it, but that gonna need to be different SKU not Mac Studio. Otherwise news will be full of discussions about Apple price hike from $8000 to $24,000 or who the hell knows $48,000.
So yeah the only way I see them selling it is usual "call us" enterprise price tag.
But since its not what Apple usually do its easier to sell 4x Mac Studio 256GB RAM boxes with interconnect for lets say $12,000 - $15,000 each.
> Let business customers spec up to 768GB who are prepared for a $20-25k price tag
There is a clear difference between $25k and $100k.
64 iPhones at retail price is already around $64k. For something at 768GB to be profitable at Apple's terms, this has to retail at $100k for it to be profitable. That was the OP's point.
Honestly you're still looking at (from my understanding) ~3 minutes prefill (TTFT) even with architectural improvements and so on with a 32k context window (against a large model). How is this going to be competitive with Nvidia and all of the tricks massive scale get's you to parallelise context across many machines?
The message I’m getting is that Apple will never compromise on its healthy margins. If something becomes basically unaffordable for their target market, they’d cut the production and even discontinue the product, than take a hit on margins. Their business model is refreshingly simple.
Apple is not gonna risk their iphones, as they are their flagship (aside even from giving them higher margins). My opinion is that, as we are talking about ram SHORTAGE (not just for ram price hike) they have to cut the more ram hungry models to be able to keep up with their projected production/demand (at reasonable ram prices). Getting iphones "sold out" is not a great thing for apple.
Once/if the ram shortage ends, they will continue increasing the ram caps as they were already doing, because then selling ram-heavy macs will not interfere with the rest of their products.
It's just a planned economy failing the way planned economies often do: the central planner failed to predict the demand correctly. Instead of trying to secure additional stock from the market at spot prices, they are simply waiting for the next batches they had planned for.
If they cared about local AI market they would price hike M3 Ultra instead of discontinuing them. After all they conviniently introduced RDMA just few months before that.
Initially when it happened everyone expected they did it because they planned to announce M5 Ultra shortly, but its not looks like this is happening.
Now IMHO its indicates they simply run out of RAM supply.
If you’re truly serious about local AI you’re not using a Mac. A Mac is for people who want the best of both worlds, GPUs are much faster if memory is equal.
It's even worse than that. Demand is so high so every next GB will be sligly more expensive. There is a lot of smaller hardware manufacturers that unable to secure DRAM chips at any price, there just no free capacity on market.
Of course Apple is massive, but if they announce inference boxes that everyone wants they need to make 10,000s or even 100,000s of them.
And it's very much likely they'd rather sell 600,000 - 10,000,000 more iPhones or Macbooks Neo. End users bring Apple money with every OpenAI / Claude subscriprion sold through their platform.
And inference boxes is just one-off sale of hardware that will bring no further income.
They are assuming that they are able to get ram in the future, once the AI bubble either dissipates or pops. Its far easier to build something you planned for 3 years ago, than crash build it in 3 months.
Of course if RAM prices crash Apple might of bring high RAM options back. We just cant bet on it as consumers.
Right now RAM shortages are bad to the point where likely even Apple have to decide what products they make and what they discontinue.
There been short time where M3 Ultra with 256GB / 512GB been best offet on market because Apple lagged with price increase. Now HN crowd expect Apple of all companies jump into price war with Nvidia and to subsidize their inference hardware.
The article says base M7 memory bandwidth is targeted at 240GB/s.
M1 had 70 GB/s, M1 Pro: 200, M1 Max 400, M1 Ultra 800.
Modern RTX 6000: ~1,600 or so.
If we get a 1,200-1,500 GB/s bandwidth M7 variant in late 2027 with 512GB of RAM, that will be a very interesting chip. Tracking LLM size and performance improvements, I can imagine that being a sort of inflection point for local inference. I wonder what the power budget would be in desktop format.
A hypothetical M7 Ultra with LPDDR6 14.4Gbps memory would be 1.85 Tb/s.
You're look at about 100 tokens/s for a 1T MoE 37B active 4bit model.
It'd probably cost $30k or more I'm guessing if memory prices do not come down. Even at $30k, it could still be a relative bargain since an RTX Pro 6000 Blackwell 96GB card costs $12k today. The M3 Ultra with 512GB was around $8k before Apple discontinued it. I expect an M7 Ultra to have 768GB or 1024GB.
Apple Silicon Macs were on their way to becoming cheap local LLM machines relative to professional GPUs before this memory crisis. It may still emerge as such in a few years.
Here's some interesting math: At 512GB, an Ultra chip could make 42 pro iPhones. Assume a 55% profit margins, and $1200 ASP, you're looking at $28,160 in profit from making iPhones instead. No wonder Apple discontinued the M3 Ultra 512GB. If they only have a limited supply of RAM for all their products, it makes no sense to produce an $8000 M3 Ultra 512GB when you can produce 42 pro iPhones. You can only configure an M3 Ultra up to 96GB today as of June 2026.
Apple would have to raise the price of a 512GB Ultra Mac to around $50k to match iPhone profits.
> Assume a 55% profit margins, and $1200 ASP, you're looking at $28,160 in profit from making iPhones instead. No wonder Apple discontinued the M3 Ultra 512GB.
How would that work? They purchase 512GB from Samsung and then it doesn't matter if that's like 128x 4GB or 4x 128GB?
I’d assume by next year the open weights models will be outlawed the way things are going nowadays :/
Edit: for those of you downvoting I don’t celebrate this prospect. I’m merely realistic about where things are going given the rapid vibe shift from the administration on AI since the start of June.
Apple is finally going to realize Jobs vision where sand comes into the factory, is turned into RAM and CPU chips, then installed in a Mac or iPhone then shipped to a customer.
Well yes. But similar to the Apple TSMC relationship, could Apple step in with large orders to established RAM makers such that the RAM makers can invest with stability?
192gb or 256gb of RAM would be enough ! We could run real time large MoE models, REAPed for our usage (e.g. english agentic coding), dynamic quant 2-4bits
Well yeah but NVidia just released a contender to their silicon and the M6 is probably already set in stone. Best to reshift resources to a great M7 than having a mediocre M6 and M7.
(This is assuming Apple will deliver, but this area is one of the biggest ones they have in AI, and they need the developer ecosystem to exist and survive)
I think that people are still underestimating the technical merits of Intel's 18A fabrication process.
I haven't seen any competitor even try to address the backside power delivery of 18A. I suspect that Samsung,TSMC have something similar and doesn't talk about it.
The design rules for the standard cell (sort of corresponding to the die area required by a transistor) for the Intel 18A seem to target dense, high performance designs. That's not a particularly meaningful insight - of course Intel wants to have the highest performance of all the fabs.
Intel's packaging expertise used to be a generation ahead, and indeed their server chips currently use a mad mix of chiplets and through-silicon visas for direct stacking, all heaped onto a reticule-limited monster interposer die. All of this expensive complexity might be sustainable as long as Intel can keep its enterprise customers happy. That hasn't turned out too well for them.
AMD has found a mass-market winner with mainstream gaming CPU with extra level 3 cache die stacked on top. Compared to Intel servers, it's brutally simple. But extremely effective in its consumer market.
But the Intel chiplets and packaging could be a great toolbox for M7 generation of Apple Silicon. Now that the M5 Pro and Max are multi chip packages, they more resemble the Intel and AMD designs, with chiplets dedicated to I/O or GPU.
(Speculation and dreams. That's all I got, and I'm writing it in the face of an absolutely psychotic autocorrect on a tablet.)
> I suspect that Samsung,TSMC have something similar and doesn't talk about it.
They do, just not as hyped up as Intel. TSMC will have it after 20A. Either 18A or 14A. GAA was supposed to be in 3nm but didn't happen due to multiple reasons. So it is now delayed to 20A. Backside delivery was supposed to be 20A and also got pushed back as well.
As we all know, Intel used to be famous for their engineering and their ability to scale up a newer, smaller process with way earlier commercial viability. This all ended with the Sisyphean 10nm move that was years late and honestly Intel just don't seem to have recovered from it.
So Intel seemingly has underutilized fab capacity whereas the likes of TSMC and Samsung can probably produce every chip they make with demand to spare. Given the CHIPS Act that was passed under Biden, the Trump admin taking a stake in Intel and the environment of tariffs and a push for American manufacturing, everything seems to be lining up for someone to take advantage of Inte's physical fabs and American production and that could be Apple.
What's their backup plan if the AI world doesn't pan out? What if it turns out people want base compute capability and lots of RAM for filestore cache and programs?
Maybe this strategy works, even in that world.
Remember when we all thought (were told we thought) the world was heading to 3D views of our 2D lived experience like a solid Cube of GUI we could rotate around and live inside? Well Apple took the simple 2D square pane of virtual desktops and .. made it a SONY strip. One variable: sideways.
So here we are being told AI is the future. Apple seems to be saying "yes but it will run local" which might be a safe bet if AI comes true but I wonder how many of us want the AI outcome, which is morally speaking the 3D immersive GUI cube here: what if we don't want that?
I can't imagine any world where we put this AI stuff back in the box. It is simply too useful and too powerful. And as we start seeing all his upheaval where models are getting banned, etc, I can even see the appeal of on-device AI increasing for a lot of use cases.
So I think Apple has the right instinct. In fact, I've had the thought multiple times that I really want a lot of workflows just running on my device. Workflows like fast vector search (already fast on the m4, but I want it more common place), or realtime transcription and summarization to be even faster, on device, etc.
To me AI is on par with the internet and what made it so powerful was piracy and porn and just the wide spectrum of things that are possible when you connect machines together. We are going to need the same thing again. Freedom to use any model that does any thing we want.
The worst case scenario is that we're at a plateau and LLMs max out around here. And it'd stand to reason that if that happens we'd see local models catch up at least to some extent. Compared to 5 years ago, that's a pretty good world.
So I think it's fair to say that AI isn't going away. That doens't mean that SpaceX, OpenAI and Anthropic won't crash. But I've long believed that within 5 years we'll have access to relatively cheap hardware that can run sufficient but not cutting-edge models locally. You can buy a 5090 PC for <$5000 already so I guess it's already true but I think we'll do even better.
So what happens? Nothing. If Apple make M7 Max/Ultra computes with 128-768GB of RAM and nobody buys them then... nobody buys them. Apple isn't betting the entire company on AI just like Google isn't. The rest of the internals are the same Macbook, Mac Mini or Mac Studio. You're just selling something with less RAM.
Google sold (will sell?) about $70bn worth of Google shares to fund AI infrastructure build outs. It's also issued bonds (=debt; I forget the number, $30bn?) to pay for more infrastructure. Fairly sure it also has established a shadow company, a Special Purpose Vehicle (SPV) to stash away unpleasant financial things it doesn't want to show, also for the AI build out.
Amazon, Google, Meta, Oracle are overstretching at the moment. They are predicted to become cash flow negative (more money going out than coming in) if they keep going at this rate, some time in 2027 or 2028.
Now, they won't go bankrupt but it's possible they will be hit by huge restructuring waves once the dust settles.
I find it very unlikely that nobody buys them, some people will definitely buy them to run giant open LLMS. But there's also not much risk to apple because those configs would probably be made to order
Without AI everyone’s computing needs were pretty well satisfied with current phones and laptops. LLMs are the one thing that could drive new demand if they can run locally.
AI was the only reason I bought a new computer (a refurb M3 max with 64GB). Without AI, no idea what we should bother with, it depends on what application comes out to drive local computing power (maybe better games? Yawn).
this is the backup strategy. the "AI doesn't pan out" scenario is basically if claude and openai go bankrupt, we continue running local models on our hardware.
there isn't a future where we all just decide that nah, we don't want AI anymore. usefuly things don't disappear.
In between flat material-ish (hehe) design windows and 3d compiz cube with burn effects we have settled on transparency and blur effects with a bit of visual planes thrown in.
It's highly unlikely we will end up tokenmaxxing everything, it's highly unlikely the genie can lose enough weight to fit back into the bottle. We will end up somewhere in between that strikes a balance between nice, productive and cost effective.
> What's their backup plan if the AI world doesn't pan out? What if it turns out people want base compute capability and lots of RAM for filestore cache and programs?
I think reducing the die area dedicated to ai stuff is not going to be a problem.
And in fairness apple already has essentially ai-less hardware in the form of the MacBook neo and it’s been an astonishing success.
I have one and it’s a very good laptop, particularly for the price i paid it.
Anything AI focused in silicon is also valuable for a ton of other use cases. If LLMs and GenAI don’t pan out, that silicon just gets used for other processing. Then they scale back on the dedicated die space in subsequent generations.
Do we have a choice? It's being forced upon us by folks who have the power to distort any market they want. Energy prices are rising, and the PC industry is about to be destroyed by component prices. It will be dumb clients that run the software our feudal overlords of the data centers will have the grace to grant us. And the government lets it happen because it furthers their interests.
AI isn't going anywhere, this is akin to the .com bubble. It burst, but the internet didn't go anywhere. While companies can fail, this technology is with us for the long run now, short of societal collapse.
Seems like a made-up distinction that shouldn't be necessary since M6 has not even released. I suspect this is a marketing ploy to meant to drive up both interest while also increasing prices for the next generation of Mac hardware.
What it's saying is that the M6 will be released, but not the M6 Pro or M6 Max. Instead, Apple will wait to release new Max/Pro chips for a future generation.
It's not simply marketing since the Pro/Max chips of a generation use the same cores as the regular version, just more of them or different combinations of performance and efficiency cores.
> Seems like a made-up distinction that shouldn't be necessary since M6 has not even released.
The claim is that M6 will be released, but the only variants will be lower end.
When they get to the M7 generation, they will make high end variants.
It's a real distinction because each generation of parts shares an architecture.
The article has an entire section speculating what the M6 parts will be, but says they'll top out around 200GB/s memory bandwidth and 12 graphics cores.
> Seems like a made-up distinction that shouldn't be necessary since M6 has not even released.
Why would it? Each generation of the M series has an architectural improvement on their chipsets. The difference between an M1 and an M1 Pro is the allocation and arrangement not the architecture. M6 to M7 presumably will have architectural changes.
Made up how? They'll do a refresh of lower end devices, but not the high core count versions.
It's the same thing as how the Mac Studio got an M4 Max refresh, but they didn't make an M4 Ultra so if you want the 28+ core CPU or 60+ core GPU, that's still using an M3 Ultra.
This time it'll be across all the Pro, Max, and Ultra versions, if you want those they'll stay at the previous generation for the M6 cycle.
Not that weird - Apple has a huge set of chips and hardware and software products. Putting every single thing on a fixed identical update cycle together won't always make sense.
Whether it matters for the consumer (who only sees released and announced end results) or not is irrelevant.
It can still be a very real, not made-up distinction, if the actual facts on the ground are that Apple designed an M6 line, but then scrapped that design and asked the team to create a new design with emphasis on AI-focused specs.
It's not the name that's important (the M7 could still come out as M6), is them skipping a design, or cpu "Tick-Tock model" step.
Perhaps to support demand for the products with recent price hikes, and/or the upcoming Mac Studio with M5 Ultra, rather than have customers sit on the sidelines thinking they'll wait this generation out.
I am still skeptical that Apple intentionally leaked this because they normally are so tight-lipped, but there are reasons in favor of leaking this.
Well, I guess this is the silver lining to the price increases. I'd been thinking about an M5 128GB for local inference (eg DS4), probably off the table now given that it jumped $2k overnight. But I was on the fence about it for a long time given that even the M5 is not that good compared to even a 4090. It would have been good, but not "omg" good.
If they are pulling out all the stops to make the M7 more competitive.. guess I can wait for that?
The M7 Pro and M7 Max are scheduled for as early as the end of 2027, while the M7 Ultra is on track for 2028.
This means there won't be a redesigned MBP this year since there won't be M6 Pro/Max chips. People were expecting a redesigned slimmer MBP with OLED display later this year, myself included.
I was holding out for one until I decided to switch from an M1 Pro 16" MBP to an M5 Air 15" due to the expected price increase. I think many M1 Pro/Max generation people were waiting to upgrade this year.
Current MBPs are such a delight, I really don't want to think about a thinner MBP again, I just get shivers remembering the Ive butterfly keyboard models
I can see why people would want a more powerful machine but as someone who moves around a lot, the 16" MBP weight is a pain. The 14" MBP screen is not big enough.
Isn't that switch basically a downgrade? You get some more single core performance and some weight savings, but also a worse (and smaller) screen, less multicore performance, less GPU performance, less video encoding performance and a smaller battery? I'm on an M2 Max myself, and glad they introduced a larger form factor Air, but it seems like a long way from an upgrade.
M5 is faster than the M1 Pro in ST, MT, GPU. Not sure about video encoding as it's something I rarely use. It's a smaller battery but overall a battery life improvement since my 5 year old M1 Pro only had 79% battery capacity left.
Well this kind of sucks. I've been waiting for the M6 MBPs because they're rumored (strong rumors, though) to finally remove the notch that has been a historic self-own. But it sounds like I might as well wait longer for the M7 lineup. Or maybe get a Framework Pro instead.
I agree. It was very annoying to me to spend the money (and on the nano matte one too) and still have that stupid notch. But it never makes any difference at all which is good news.
Same, have a very old MBP. Not sure what to do because I don’t want to wait a year and a half. That coupled with today’s price increases make it a tougher decision.
In the long run I truly believe local AI will win and Apple will be the world's most important AI company because of these chips. Imagine something like today's Opus running for free and in complete privacy on your local machine with a beautiful Apple UX on top. For most tasks for most people, that's a much better proposition than a frontier model in the cloud you have to pay for and send all your data to and that only works when you're online.
>In the long run I truly believe local AI will win
What do you mean by 'win'?
For a normal coder/person's use cases, yes. But AI companies are becoming more specialised in different fields and these tailored models will be leagues ahead in those niches.
The way I see it - Opus 4.8 xhigh can do any programming task with a programmer instructing it. If Apple releases local model together with a device that can run said model it would render OpenAI/Anthropic useless for vast majority of usecases.
And if a local mcahine can run something like Opus 4.8, who is to say that those "specialized" models would just not come at a later date, or even loading open models wouldn't be an option with something like M7-verified flag from huggingface that would make it extremely easy for any consumer to just play around.
There is built-in demand for local LLMs. An obvious example is law firms where using remote AI tools may be breaking privilege [1]. Any medical applications may likewise run into legal issues.
The problem is basically that we can't have nice things. AI chat logs themselves become another commodity to sell and to train on. We recently had a story about how Chinese firms are reselling Claude tokens [2]. The chat logs are a commodity here.
The only way to avoid this is to run LLMs locally. Even if you trust someone like Anthropic or Google, case law simply hasn't been established that the chat logs aren't discoverable.
Add to that that a sub-$5000 PC with a 5090 can already run a 31B model at reasonable inference speeds. Not amazing but good enough for many applications. Obviously that can't compete with Mythos but it doesn't have to. It also shows where the trend line is going for hardware. A $10k Nvidia GPU from 10 years ago now sells for scrap. What a consumer-level computer in 5 years can run locally will probably shock a lot of people.
I would say local AI is very real. I use it but so many here am on other forums do so nowadays as well. This is the reason I just cannot fathom the valuations of the AI firms out there.
Mac mini Pro line is doomed, they never made enough of it; skipped M5 Pro, now skipping M6 Pro, it is like 2014-2018 again. Now ordering a custom M4 Pro build take 3 months+ to ship with an increased price.
I was waiting for a MacBook Pro M6 Max and now I don’t know what to do, especially with the price increase I feel like I really screwed up not just getting an MBP M5 Max a month ago
because America can't compete. Build a fab in the US, labor unions, labor costs, regulations, land, energy, taxes, government, water, etc all make this not economical. Everything would cost twice as much and you'd rather buy the cheaper product and it'll be bankrupt. There were reasons why all the manufacturing went overseas to Asia. You're right, the demand right now is HUGE but it won't always be huge. At this point, we don't have the talent or the knowledge to do it well anyway which is why we needed TSMC and Samsung to bring employees over to train people. https://www.cppionline.org/wp-content/uploads/2017/07/The-De...
I am waiting till apple copies the "allocation" concept from high end car manufacturers. "Sure, buy the 25 iphones ans we will gladly put you on the waitlist."
Apple to skip high-end versions of M6 Mac chips...
I read it as the M6 being "high-end" in general, and Apple skipping the whole generation, which made no sense to me. But they are going to use the M6 at all, just not bother to create Max and Ultra versions of it.
So the big question: Is this an excuse to save on memory costs and delaying stuff like the M5 Ultra, M6 Max, etc until 2027 when memory prices come back down?
Given that M6 will be on TSMC smaller 2nm node and the first smaller node size in 3-years, it seems like the oddest of all years for the high-end Macs to skip.
1. NVidia aggressively segments the market on VRAM and will continue to do so. A 5090 with 32GB of RAM, ~21k CUDA cores and 1800GB/s of memory bandwidth is $3-4k. An RTX 6000 Pro with 96GB of RAM, ~24k CUDA cores and 1800GB/s memory bandwidth is ~$11k;
2. The 5090 won't be replaced until late 2028 or even 2029. There has been no mid-cycle refresh (eg 4080 Super vs 4080) and likely won't be either at all or for at least a year. If there is in a year, it basically confirms that the 6000 series won't be until 2028/2029. Also, the x090 never got a mid-cycle refresh so the current consumer high-end is staying that way for years;
3. The 6090 whenever it comes will still have 32GB of VRAM unless the memory market drastically changes;
4. Many have anticipated an M5 Max/Ultra refresh of the Mac Studio line in Q3. Given that Apple chose to hike the prices on Studios rather than discontinue them, I now think this isn't going to happen. We may not see a Studio refresh for up to 2 years. Apple has done this before with the Mac Pro;
5. M7 Max/Ultra will probably go to a memory bandwidth of 1.2-1.8TB/s vs the current tops of M3 Ultra, M4 Max and M5 Max of 600-900GB/s. This simply needs to go up to boost inference speed;
6. You'll also see the number of GPU cores go up. All of this will add up to an M7 Max being 50-80%+ of the performance of a 5090. That's huge given the shared memory architecture;
7. We may see the return of Apple using its massive cash pile for vendor-financing of an exclusive memory supply. This was one of Tim Apple's [sic] big innovations.
Do you really think the average Apple user will use it when there’s already better AI provided by OpenAI and Anthropic which don’t require advanced local hardware?
Apple is very late to the AI party. By the time M7 is shipped, Nvidia will announce 6090 and people will be buying used (3|4|5)090 GPUs to run local models at much better performance than heat throttled M7.
What people? Are you seriously thinking the hundreds of millions of customers Apple have is going to be buying run-to-the-ground GPUs second hand and build local workstations for AI? Might as well ask them to self host email while you’re at it.
The difference between these two is that one of them is an unsolved research problem that we’ve all spent far too much time on, and the other is just running an LLM.
I would prefer a Studio if it does a decent enough job even if throttles a bit under load, way less power usage and noise than those GPUs plus the PC you need to put those in.
RAM is a commodity and nvidia will be paying the same prices. The used market will reflect the cost of RAM. nvidia owns the top of the market but many of us don't need that.
Apple isn't just transitioning to TSMC's 2nm node, they are also transitioning to a chiplet based design using TSMC's advanced packaging.
> What sets the A20 apart isn’t just the node shrink—it’s the revolution in packaging. Apple is transitioning to Wafer-Level Multi-Chip Module (WLCM) integration, meaning that RAM will no longer be situated beside the chip, but rather on the chip wafer itself, integrated alongside the CPU, GPU, and Neural Engine.
This shift eliminates the need for silicon interposers and substrates, thereby enhancing signal integrity, improving thermal dissipation, and facilitating faster memory access with lower latency. The benefits? Better multitasking, smoother AI processing (hello, Apple Intelligence), improved battery life, and potentially a smaller chip footprint—freeing up space for other components.
Do we have any explanations of what WLCM means that are more industry focused? I couldn't find anything that didn't look like blogspam. And that explanation of the DRAM being on the same wafer doesn't really make sense. For one, at that point there's no "multi chip" part if you're integrating more onto the same die rather than less.
And their explanation isn't really passing the smell test for me for other reasons, for instance the fact that DRAM processes are pretty radically different than bulk logic processes, which wouldn't really let you put it all on the same wafer, much less the same die. Even back in the day when you had eDRAM blocks (like the Xbox 360's eDRAM die), that was really a DRAM process with a bit of logic cells that wouldn't be competitive if they weren't sitting right next to the DRAM blocks.
I could be wrong here though, my examples are more than a bit long in the tooth.
The terms to search for are fan-out wafer level packaging (FOWLP) and TSMC InFO. The chiplets come from different wafers and are reconstituted into a molded plastic wafer, allowing multiple die side-by-side. Then multiple layers of wires are built on top, terminating in a BGA.
You can start by reading up on TSMC's name for the tech (although there are many versions at TSMC and TSMC isn't the only company packaging chiplets and memory on top of a silicon interposer).
A kind request - please try to write HN replies without AI, but if you're going to, please at least edit out any "it's not X its Y" or "isn't just X, but also Y" AI tics. A lot of us come here to get away from talking to AIs all day.
So far the only thing I've seen useful out of apple intelligence is running parakeet natively and effectively... which should have been their very first feature... given it's been on phones for 10+ years.
As someone who wants to run effective llms locally for many things their other big benefit has been the unified memory studios for a small bit.
Apple is actually interesting. They are one of the few companies with a chip / PC play with real power AND basically no play I'm the hyperscalar market.
That means they're actually incentivized at least short term, to benefit PCs becoming strong enough to do local LLMs. Which makes this play make even more sense. Though, I've been saying for a while that the local AI inflectiom point is the death knell for these frontier labs.
> Though, I've been saying for a while that the local AI inflectiom point is the death knell for these frontier labs.
"Death knell" is a touch hyperbolic. Hardware that can only run quantized models that take up GBs in VRAM falls short of even an A100 (by almost an order of magnitude[0]), which in turn falls short of what an 8xH100 cluster can do (also by another order of magnitude[0]).
I'm an avid believer in local LLMs, but I cannot deceive myself - data center accelerators will win on power dissipation numbers alone[1], even when giving generous allowances for higher efficiency on Apple chips - and assuming the Apple-efficiency advantage persists on the same TSMC process node.
0. Based on my unscientific fine-tuning training experiments across local and rented GPUs. YMMV for inference.
1. Unless Apple surprises everyone and brings back the XServe with M7, if not, then laptop and desktop for factors simply can't dump heat fast enough to compete head-to-head, and will be designed for lower input wattage.
Doesn’t need to be a winner head to head. If it can do 90% of the tasks the big boys do, at 50% speed, for virtually no extra overhead cost save for the power consumed by a prompt - that’s gonna work for a lot of people. And that’s also basically where we’re at today. Qwen3.6 35b running quantized on 10 year old hardware solves basically all of my uses cases for agents except for coding.
The frontier models are faster, and better at coding, but not so much that i’ll pay $200/month for them.
18 replies →
We'll likely see a transformation in how frontier models are trained as a result of a push towards local inference. While it seems unlikely now, given current pricing for RAM, in 10-15 years it's not unthinkable to assume we could see individual machines with 10-12TB (and well beyond that) of RAM which are accessible to the GPU. Min/max system RAM increased a LOT from 2010-2025 and largely because it was cheap. Once the hyperscalers aren't generating revenue for the RAM manufacturers, I wouldn't be surprised to see a massive push towards consumers in order to maintain gross profit. Not to mention new players who enter the market because the margins are measurably absurd right now.
At some point there will be diminishing returns towards the "just throw more RAM at it" approach the current frontier models are taking. Commoditization is just as inevitable as it ever was... and in doing so will enable actual leaps of what AI/ML is capable of. That's not to say there won't be a place for 99.999999% accurate vs 99.99999% but those cases will be limited and likely prime to disruption based on real innovation vs access to capital.
5 replies →
The established AI players have no financial interest to make LLM available locally. They aren't hardware companies and if running LLM requires paying them to host the models as well then they can naturally capture more of the value chain = more revenue.
Apple is the only player here where it would play into their natural hardware incentive to get you to pay more for better hardware. It would make sense for them to find a way to run LLM locally (eg, newer architectures that others here have pointed out).
Interesting times.
Is it hyperbolic though? One of the best things about the compute and memory shortage is that people are going to insane lengths to optimize things to run on lower memory / lower compute devices. If we keep this up for a while and then ramp up memory and local compute production, that AI inflection point may actually come.
Of course, these are a lot of ifs.
2 replies →
The big question for local LLMs is whether there is a 100 tok/s model which requires less than 16 GB of memory and is competitive on most tasks with the cloud models.
There is some signal that this is possible through both hardware innovation and training/data improvements.
Cloud models have their own constraints - I can’t have opus4.8 spend 4 hours on a deep research question I had in the shower without spending money. I can’t do real time video game upscaling and graphics work in the cloud period.
A laptop is about an order of magnitude cheaper than a cloud server thanks to economies of scale, uptime requirements, and other factors.
11 replies →
The thing is, with the level of hard investment AI vendors have, even a small reduction of their addressable market is significant. They aren’t profitable, and inference is getting commoditized fast, so even if they eventually become profitable (not via financial engineering) they won’t be able to have good margin. The pressure of both open models AND local models is pretty bad imho
> Hardware that can only run quantized models that take up GBs in VRAM
That's the today hardware.
Now suppose Apple goes to any of Samsung/Micron/Hynix and says "we'll pay you the entire cost of building another DRAM fab and in exchange we want its entire output" and then releases M7 devices with enough memory and compute to run bigger models.
> Unless Apple surprises everyone and brings back the XServe with M7, if not, then laptop and desktop for factors simply can't dump heat fast enough to compete head-to-head, and will be designed for lower input wattage.
Laptops maybe. Desktops can dissipate more heat than the amount of electricity you can draw from a typical household wall outlet.
2 replies →
I'm not paying for a super computer to do my taxes if a cheap pc can do it for free.
So yeah, commercially it might be a death knell. Yes there's still a market for super computers, but would your rather own Apple or Cray?
1 reply →
I think this is right but it also depends on what "compete" means
Indeed. Local models becoming available and halfway decent don't obviate the laws of scale. And because there's no ceiling to what scaling more will buy you in terms of capability, there's no reason not to scale more, there's no incentive for billionaires not to grab all the fab capacity they can.
Enjoy paying $1000 or more for a little 4 GiB cloud terminal that connects you to all your online accounts where all your actual work gets done. This is the future.
4 replies →
Indeed. If Apple makes it feasible to run models like GLM 5.2 at home, I will become their customer.
It's plausible but is the Apple Tax for a 1TB memory machine on top of current memory prices really worth it? I paid around $4000 for 4090m laptop with 16GB VRAM back in 2023, it's great but DoA for even quantized LLMs. I can run SLMs and fine tune it but that's it.
We need one of those specialized inference chip startups to succeed and a PC manufacturer willing to bet on them against Nvidia for the local AI to find mass market appeal.
21 replies →
you're not a customer of any of their products at all already? not a single apple device in your household?
14 replies →
Tangential: About 8 years ago ex-Apple chip engineers left to design server-grade chips, this was Nuvia, and they got sued by Apple to the point that they had to get acquired by Qualcomm.
Then, after getting acquired by Qualcomm they got sued by ARM.
So maybe they were assholes.
1 reply →
I worked at a hyperscaler when the M1 came out. A MacBook Air M1, running a Linux VM was faster and more energy efficient than anything we had in the data center.
I'm certainly willing to believe the M1 was the most energy efficient, but your data center didnt have anything faster than a laptop?
2 replies →
They do stand in front of a great opportunity that would also benefit consumers, which seems rare in the llm era.
If people can get opus4.6/gpt5.5-like models locally, labs could raise their prices and sell token speed, better reasoning, mobile-focused improvements, you name it.
Not all consumers are power users and many will be happy to pay for flexibility.
Most people don't actually want to manage models, updates, context limits, quantization, etc. They just want the thing to work everywhere
3 replies →
>AND basically no play I'm the hyperscalar market.
I do wish they have Xserve back, or a Mac Pro that is Rack Based and support multiple node with M6 Ultra. The Hyperscaler market is so large along with AI their old business case of Xserve didn't make sense no long hold true.
I really wish people stopped saying things "I've been saying that"
why not just say "I think that"
do you see yourself as some kind of visionary about this particular topic? literally EVERYONE is saying that, it's the most obvious fact about AI
I'm not sure it's a death knell for frontier labs so much as a narrowing of what people need them for
When you've raised hundreds of billions in funding, every result except "to the moon" is a death knell.
1 reply →
768GB RAM pipe dreams make no sense to Apple. By discontinuing 256GB / 512GB M3 Ultra and raising prices $5000 -> $7000 on Macbook pro with 128GB they basically confirmed how badly RAM shortage affecting them.
768GB is 64-times of 12GB which is rumored to be amount of RAM in new iPhones. Imagine what profit margin 768GB Mac Studio gonna need in order to justify making one instead of 64 iPhones.
Apple is the company that is okay about selling microfiber cloth for $100 and wheels for $700. Imagine how bad price hike for M3 Ultra 256GB / 512GB had to be in order for them to just discontinue them instead of getting free money out of desperate local AI folks.
They could treat the extreme spec machines separately from the prosumer ones, like they did with the Xserve. Let business customers spec up to 768GB (say) who are prepared for a $20-25k price tag, while keeping them away from the stores and usual consumer supply chains (Amazon et al). It may not be a big enough market segment for them to care about anymore, though.
They can do it, but that gonna need to be different SKU not Mac Studio. Otherwise news will be full of discussions about Apple price hike from $8000 to $24,000 or who the hell knows $48,000.
So yeah the only way I see them selling it is usual "call us" enterprise price tag.
But since its not what Apple usually do its easier to sell 4x Mac Studio 256GB RAM boxes with interconnect for lets say $12,000 - $15,000 each.
15 replies →
> Let business customers spec up to 768GB who are prepared for a $20-25k price tag
There is a clear difference between $25k and $100k.
64 iPhones at retail price is already around $64k. For something at 768GB to be profitable at Apple's terms, this has to retail at $100k for it to be profitable. That was the OP's point.
They'll sell more $20-25k Macs when Goldman green lights Apple Card credit limits that will fit one of them.
1 reply →
Honestly you're still looking at (from my understanding) ~3 minutes prefill (TTFT) even with architectural improvements and so on with a 32k context window (against a large model). How is this going to be competitive with Nvidia and all of the tricks massive scale get's you to parallelise context across many machines?
1 reply →
The message I’m getting is that Apple will never compromise on its healthy margins. If something becomes basically unaffordable for their target market, they’d cut the production and even discontinue the product, than take a hit on margins. Their business model is refreshingly simple.
That works only if the product is the product.
Iphones/tablets drive app sales/apple subscription services, if they force a user to move to android they may never return.
Why do you think they sell the iPhone 17e/se? They need to maximise their user base as its ongoing recurring income stream.
1 reply →
Apple is not gonna risk their iphones, as they are their flagship (aside even from giving them higher margins). My opinion is that, as we are talking about ram SHORTAGE (not just for ram price hike) they have to cut the more ram hungry models to be able to keep up with their projected production/demand (at reasonable ram prices). Getting iphones "sold out" is not a great thing for apple.
Once/if the ram shortage ends, they will continue increasing the ram caps as they were already doing, because then selling ram-heavy macs will not interfere with the rest of their products.
It's just a planned economy failing the way planned economies often do: the central planner failed to predict the demand correctly. Instead of trying to secure additional stock from the market at spot prices, they are simply waiting for the next batches they had planned for.
3 replies →
I actually think Apple is right in increasing prices, and in fact should have increased it more.
Their target market is composed of people that would pay for it nonetheless. They should have tightened the screws a bit more.
I think you have an excellent point and I'll bet someone at Apple has all this in spreadsheet and is making that case.
However, I think without the very high end machines Apple is also seeding a lot of professional middle market too.
If the choice is between, say, a Framework desktop vs nothing from Apple I'll obviously pick the Framework.
If I get used to a Framework desktop running Linux then I'd probably stop buying MacBook Pros.
Right now Apple has a chance at capturing local AI but that opportunity won't last forever.
If they cared about local AI market they would price hike M3 Ultra instead of discontinuing them. After all they conviniently introduced RDMA just few months before that.
Initially when it happened everyone expected they did it because they planned to announce M5 Ultra shortly, but its not looks like this is happening.
Now IMHO its indicates they simply run out of RAM supply.
If you’re truly serious about local AI you’re not using a Mac. A Mac is for people who want the best of both worlds, GPUs are much faster if memory is equal.
do you mean ceding that market?
1 reply →
This is only true under the assumption that RAM price per GB scales linearly.
It's even worse than that. Demand is so high so every next GB will be sligly more expensive. There is a lot of smaller hardware manufacturers that unable to secure DRAM chips at any price, there just no free capacity on market.
Of course Apple is massive, but if they announce inference boxes that everyone wants they need to make 10,000s or even 100,000s of them.
And it's very much likely they'd rather sell 600,000 - 10,000,000 more iPhones or Macbooks Neo. End users bring Apple money with every OpenAI / Claude subscriprion sold through their platform.
And inference boxes is just one-off sale of hardware that will bring no further income.
Forward planning though.
They are assuming that they are able to get ram in the future, once the AI bubble either dissipates or pops. Its far easier to build something you planned for 3 years ago, than crash build it in 3 months.
Of course if RAM prices crash Apple might of bring high RAM options back. We just cant bet on it as consumers.
Right now RAM shortages are bad to the point where likely even Apple have to decide what products they make and what they discontinue.
There been short time where M3 Ultra with 256GB / 512GB been best offet on market because Apple lagged with price increase. Now HN crowd expect Apple of all companies jump into price war with Nvidia and to subsidize their inference hardware.
[dead]
The article says base M7 memory bandwidth is targeted at 240GB/s.
M1 had 70 GB/s, M1 Pro: 200, M1 Max 400, M1 Ultra 800.
Modern RTX 6000: ~1,600 or so.
If we get a 1,200-1,500 GB/s bandwidth M7 variant in late 2027 with 512GB of RAM, that will be a very interesting chip. Tracking LLM size and performance improvements, I can imagine that being a sort of inflection point for local inference. I wonder what the power budget would be in desktop format.
A hypothetical M7 Ultra with LPDDR6 14.4Gbps memory would be 1.85 Tb/s.
You're look at about 100 tokens/s for a 1T MoE 37B active 4bit model.
It'd probably cost $30k or more I'm guessing if memory prices do not come down. Even at $30k, it could still be a relative bargain since an RTX Pro 6000 Blackwell 96GB card costs $12k today. The M3 Ultra with 512GB was around $8k before Apple discontinued it. I expect an M7 Ultra to have 768GB or 1024GB.
Apple Silicon Macs were on their way to becoming cheap local LLM machines relative to professional GPUs before this memory crisis. It may still emerge as such in a few years.
Here's some interesting math: At 512GB, an Ultra chip could make 42 pro iPhones. Assume a 55% profit margins, and $1200 ASP, you're looking at $28,160 in profit from making iPhones instead. No wonder Apple discontinued the M3 Ultra 512GB. If they only have a limited supply of RAM for all their products, it makes no sense to produce an $8000 M3 Ultra 512GB when you can produce 42 pro iPhones. You can only configure an M3 Ultra up to 96GB today as of June 2026.
Apple would have to raise the price of a 512GB Ultra Mac to around $50k to match iPhone profits.
> Assume a 55% profit margins, and $1200 ASP, you're looking at $28,160 in profit from making iPhones instead. No wonder Apple discontinued the M3 Ultra 512GB.
How would that work? They purchase 512GB from Samsung and then it doesn't matter if that's like 128x 4GB or 4x 128GB?
6 replies →
Where did you get 55% from? iPhone and Mac gross margins behave been 40% or so for years IIRC.
1 reply →
An ‘ypothetical!
3 replies →
> A hypothetical M7 Ultra with LPDDR6
That’s indeed very hypothetical considering that Apple silicon uses on-package HBM.
1 reply →
> The M3 Ultra with 512GB was around $8k before Apple discontinued it
The base model was $9k, that much RAM got you into $14k range.
2 replies →
I’d assume by next year the open weights models will be outlawed the way things are going nowadays :/
Edit: for those of you downvoting I don’t celebrate this prospect. I’m merely realistic about where things are going given the rapid vibe shift from the administration on AI since the start of June.
2 replies →
M5 is 153GB/s, M5 Pro 307GB/s, M5 Max 614GB/s.
The article didn't state the M5 Ultra won't be released. It will probably provide 1228GB/s of memory bandwidth this year.
Problem is affording the ram…
Apple is finally going to realize Jobs vision where sand comes into the factory, is turned into RAM and CPU chips, then installed in a Mac or iPhone then shipped to a customer.
3 replies →
As some like to call it, 'the last moat'.
Well yes. But similar to the Apple TSMC relationship, could Apple step in with large orders to established RAM makers such that the RAM makers can invest with stability?
3 replies →
192gb or 256gb of RAM would be enough ! We could run real time large MoE models, REAPed for our usage (e.g. english agentic coding), dynamic quant 2-4bits
At this point and given the cost of memory, it will probably make sense to invest in faster SSD to allow for good performance with less memory
late 2027 is a very long time.
Well yeah but NVidia just released a contender to their silicon and the M6 is probably already set in stone. Best to reshift resources to a great M7 than having a mediocre M6 and M7.
(This is assuming Apple will deliver, but this area is one of the biggest ones they have in AI, and they need the developer ecosystem to exist and survive)
That would cost as much as a new car.
Don't worry, they'll just make cars more expensive
5 replies →
Maxed out 2019 Mac Pro was $50k+. The wheels on that thing were $400. This is a bargain compared to that.
Former AnandTech editor Gavin Bonshor had reports that the M7 would be manufactured on Intel's 18A node.
https://bontechlabs.com/news/apple-is-reportedly-using-intel...
Given the risks involved in establishing Apple Silicon designs with a new fab, I would expect early M7 parts to be in test production right now.
The fundamental M7 design is already set in stone.
Mark Gurman's Bloomberg article does not mention fabrication partners or processes.
I think that people are still underestimating the technical merits of Intel's 18A fabrication process.
I haven't seen any competitor even try to address the backside power delivery of 18A. I suspect that Samsung,TSMC have something similar and doesn't talk about it.
The design rules for the standard cell (sort of corresponding to the die area required by a transistor) for the Intel 18A seem to target dense, high performance designs. That's not a particularly meaningful insight - of course Intel wants to have the highest performance of all the fabs.
Intel's packaging expertise used to be a generation ahead, and indeed their server chips currently use a mad mix of chiplets and through-silicon visas for direct stacking, all heaped onto a reticule-limited monster interposer die. All of this expensive complexity might be sustainable as long as Intel can keep its enterprise customers happy. That hasn't turned out too well for them.
AMD has found a mass-market winner with mainstream gaming CPU with extra level 3 cache die stacked on top. Compared to Intel servers, it's brutally simple. But extremely effective in its consumer market.
But the Intel chiplets and packaging could be a great toolbox for M7 generation of Apple Silicon. Now that the M5 Pro and Max are multi chip packages, they more resemble the Intel and AMD designs, with chiplets dedicated to I/O or GPU.
(Speculation and dreams. That's all I got, and I'm writing it in the face of an absolutely psychotic autocorrect on a tablet.)
> I suspect that Samsung,TSMC have something similar and doesn't talk about it.
They do, just not as hyped up as Intel. TSMC will have it after 20A. Either 18A or 14A. GAA was supposed to be in 3nm but didn't happen due to multiple reasons. So it is now delayed to 20A. Backside delivery was supposed to be 20A and also got pushed back as well.
I find this rumor at least plausible.
As we all know, Intel used to be famous for their engineering and their ability to scale up a newer, smaller process with way earlier commercial viability. This all ended with the Sisyphean 10nm move that was years late and honestly Intel just don't seem to have recovered from it.
So Intel seemingly has underutilized fab capacity whereas the likes of TSMC and Samsung can probably produce every chip they make with demand to spare. Given the CHIPS Act that was passed under Biden, the Trump admin taking a stake in Intel and the environment of tariffs and a push for American manufacturing, everything seems to be lining up for someone to take advantage of Inte's physical fabs and American production and that could be Apple.
Wouldn't this help Intel compete?
If they have Apple's designs months prior to launch, rather than after launch.
Ripping off designs from your own fab customers is a pretty sure way to crater your fab business, and get sued into the ground at the same time.
9 replies →
What's their backup plan if the AI world doesn't pan out? What if it turns out people want base compute capability and lots of RAM for filestore cache and programs?
Maybe this strategy works, even in that world.
Remember when we all thought (were told we thought) the world was heading to 3D views of our 2D lived experience like a solid Cube of GUI we could rotate around and live inside? Well Apple took the simple 2D square pane of virtual desktops and .. made it a SONY strip. One variable: sideways.
So here we are being told AI is the future. Apple seems to be saying "yes but it will run local" which might be a safe bet if AI comes true but I wonder how many of us want the AI outcome, which is morally speaking the 3D immersive GUI cube here: what if we don't want that?
I can't imagine any world where we put this AI stuff back in the box. It is simply too useful and too powerful. And as we start seeing all his upheaval where models are getting banned, etc, I can even see the appeal of on-device AI increasing for a lot of use cases.
So I think Apple has the right instinct. In fact, I've had the thought multiple times that I really want a lot of workflows just running on my device. Workflows like fast vector search (already fast on the m4, but I want it more common place), or realtime transcription and summarization to be even faster, on device, etc.
To me AI is on par with the internet and what made it so powerful was piracy and porn and just the wide spectrum of things that are possible when you connect machines together. We are going to need the same thing again. Freedom to use any model that does any thing we want.
7 replies →
The worst case scenario is that we're at a plateau and LLMs max out around here. And it'd stand to reason that if that happens we'd see local models catch up at least to some extent. Compared to 5 years ago, that's a pretty good world.
So I think it's fair to say that AI isn't going away. That doens't mean that SpaceX, OpenAI and Anthropic won't crash. But I've long believed that within 5 years we'll have access to relatively cheap hardware that can run sufficient but not cutting-edge models locally. You can buy a 5090 PC for <$5000 already so I guess it's already true but I think we'll do even better.
So what happens? Nothing. If Apple make M7 Max/Ultra computes with 128-768GB of RAM and nobody buys them then... nobody buys them. Apple isn't betting the entire company on AI just like Google isn't. The rest of the internals are the same Macbook, Mac Mini or Mac Studio. You're just selling something with less RAM.
> Google isn't
Google sold (will sell?) about $70bn worth of Google shares to fund AI infrastructure build outs. It's also issued bonds (=debt; I forget the number, $30bn?) to pay for more infrastructure. Fairly sure it also has established a shadow company, a Special Purpose Vehicle (SPV) to stash away unpleasant financial things it doesn't want to show, also for the AI build out.
Amazon, Google, Meta, Oracle are overstretching at the moment. They are predicted to become cash flow negative (more money going out than coming in) if they keep going at this rate, some time in 2027 or 2028.
Now, they won't go bankrupt but it's possible they will be hit by huge restructuring waves once the dust settles.
4 replies →
I find it very unlikely that nobody buys them, some people will definitely buy them to run giant open LLMS. But there's also not much risk to apple because those configs would probably be made to order
AI already has massive, growing adoption, whereas "3D immersive GUI cubes" never really had any.
It has at the current subsidised prices.
2 replies →
Without AI everyone’s computing needs were pretty well satisfied with current phones and laptops. LLMs are the one thing that could drive new demand if they can run locally.
Not software developers, they were already flocking to Apple M series machines with more RAM and cores before LLMs.
AI was the only reason I bought a new computer (a refurb M3 max with 64GB). Without AI, no idea what we should bother with, it depends on what application comes out to drive local computing power (maybe better games? Yawn).
this is the backup strategy. the "AI doesn't pan out" scenario is basically if claude and openai go bankrupt, we continue running local models on our hardware.
there isn't a future where we all just decide that nah, we don't want AI anymore. usefuly things don't disappear.
"What if it turns out people want base compute capability and lots of RAM for filestore cache and programs?"
Can't it do both? The M1 Pro with 16gb+ is still more than nearly everyone needs.
In between flat material-ish (hehe) design windows and 3d compiz cube with burn effects we have settled on transparency and blur effects with a bit of visual planes thrown in. It's highly unlikely we will end up tokenmaxxing everything, it's highly unlikely the genie can lose enough weight to fit back into the bottle. We will end up somewhere in between that strikes a balance between nice, productive and cost effective.
> What's their backup plan if the AI world doesn't pan out? What if it turns out people want base compute capability and lots of RAM for filestore cache and programs?
I think reducing the die area dedicated to ai stuff is not going to be a problem.
And in fairness apple already has essentially ai-less hardware in the form of the MacBook neo and it’s been an astonishing success.
I have one and it’s a very good laptop, particularly for the price i paid it.
Anything AI focused in silicon is also valuable for a ton of other use cases. If LLMs and GenAI don’t pan out, that silicon just gets used for other processing. Then they scale back on the dedicated die space in subsequent generations.
It’s all fairly easy bets to make and correct.
> what if we don't want that?
Do we have a choice? It's being forced upon us by folks who have the power to distort any market they want. Energy prices are rising, and the PC industry is about to be destroyed by component prices. It will be dumb clients that run the software our feudal overlords of the data centers will have the grace to grant us. And the government lets it happen because it furthers their interests.
China might be the only spanner in those works, so expect further action taken against them. Most likely sanctions on their hardware
those billion people which use LLMs every week, are they all being forced to use it?
AI isn't going anywhere, this is akin to the .com bubble. It burst, but the internet didn't go anywhere. While companies can fail, this technology is with us for the long run now, short of societal collapse.
Seems like a made-up distinction that shouldn't be necessary since M6 has not even released. I suspect this is a marketing ploy to meant to drive up both interest while also increasing prices for the next generation of Mac hardware.
What it's saying is that the M6 will be released, but not the M6 Pro or M6 Max. Instead, Apple will wait to release new Max/Pro chips for a future generation.
It's not simply marketing since the Pro/Max chips of a generation use the same cores as the regular version, just more of them or different combinations of performance and efficiency cores.
> Seems like a made-up distinction that shouldn't be necessary since M6 has not even released.
The claim is that M6 will be released, but the only variants will be lower end.
When they get to the M7 generation, they will make high end variants.
It's a real distinction because each generation of parts shares an architecture.
The article has an entire section speculating what the M6 parts will be, but says they'll top out around 200GB/s memory bandwidth and 12 graphics cores.
> Seems like a made-up distinction that shouldn't be necessary since M6 has not even released.
Why would it? Each generation of the M series has an architectural improvement on their chipsets. The difference between an M1 and an M1 Pro is the allocation and arrangement not the architecture. M6 to M7 presumably will have architectural changes.
Is the point that M6 doesn't exist? What change are they making that justifies M5 to M7?
Or did this announcement also add an M6 chip, and they're just skipping pro?
3 replies →
Made up how? They'll do a refresh of lower end devices, but not the high core count versions.
It's the same thing as how the Mac Studio got an M4 Max refresh, but they didn't make an M4 Ultra so if you want the 28+ core CPU or 60+ core GPU, that's still using an M3 Ultra.
This time it'll be across all the Pro, Max, and Ultra versions, if you want those they'll stay at the previous generation for the M6 cycle.
Not that weird - Apple has a huge set of chips and hardware and software products. Putting every single thing on a fixed identical update cycle together won't always make sense.
Made up: “this one goes to 11”
1 reply →
Whether it matters for the consumer (who only sees released and announced end results) or not is irrelevant.
It can still be a very real, not made-up distinction, if the actual facts on the ground are that Apple designed an M6 line, but then scrapped that design and asked the team to create a new design with emphasis on AI-focused specs.
It's not the name that's important (the M7 could still come out as M6), is them skipping a design, or cpu "Tick-Tock model" step.
Why? The specs and benchmarks will show the differences, there’s no marketing around that.
It’s an amusing conspiracy theory, but I don’t get it.
Are you thinking Apple is leaking that there will be a long wait for much more expensive chips in order to… what?
Perhaps to support demand for the products with recent price hikes, and/or the upcoming Mac Studio with M5 Ultra, rather than have customers sit on the sidelines thinking they'll wait this generation out.
I am still skeptical that Apple intentionally leaked this because they normally are so tight-lipped, but there are reasons in favor of leaking this.
Well, I guess this is the silver lining to the price increases. I'd been thinking about an M5 128GB for local inference (eg DS4), probably off the table now given that it jumped $2k overnight. But I was on the fence about it for a long time given that even the M5 is not that good compared to even a 4090. It would have been good, but not "omg" good.
If they are pulling out all the stops to make the M7 more competitive.. guess I can wait for that?
I imagine they weren't planning for their plans to be leaked so publicly, as yes it will now mean some buyers will delay their purchases.
This means there won't be a redesigned MBP this year since there won't be M6 Pro/Max chips. People were expecting a redesigned slimmer MBP with OLED display later this year, myself included.
I was holding out for one until I decided to switch from an M1 Pro 16" MBP to an M5 Air 15" due to the expected price increase. I think many M1 Pro/Max generation people were waiting to upgrade this year.
Current MBPs are such a delight, I really don't want to think about a thinner MBP again, I just get shivers remembering the Ive butterfly keyboard models
I can see why people would want a more powerful machine but as someone who moves around a lot, the 16" MBP weight is a pain. The 14" MBP screen is not big enough.
4 replies →
Isn't that switch basically a downgrade? You get some more single core performance and some weight savings, but also a worse (and smaller) screen, less multicore performance, less GPU performance, less video encoding performance and a smaller battery? I'm on an M2 Max myself, and glad they introduced a larger form factor Air, but it seems like a long way from an upgrade.
M5 is faster than the M1 Pro in ST, MT, GPU. Not sure about video encoding as it's something I rarely use. It's a smaller battery but overall a battery life improvement since my 5 year old M1 Pro only had 79% battery capacity left.
> This means there won't be a redesigned MBP this year since there won't be M6 Pro/Max chips.
They can release a redesigned MBP with the base M6 chip.
They can, it wouldn't make sense from a marketing and optics perspective.
They don't want to tell the world how the new redesigned MBP is the best laptop in the world but it's slower than the older MBPs.
3 replies →
It seems likely the MB Ultra will ship with the M5 Ultra.
Well this kind of sucks. I've been waiting for the M6 MBPs because they're rumored (strong rumors, though) to finally remove the notch that has been a historic self-own. But it sounds like I might as well wait longer for the M7 lineup. Or maybe get a Framework Pro instead.
The notch does not matter at all, you will forget it's there.
Well… your menu items will disappear behind it still in 2026. You would need an extra app for that…
But in terms of “noticing it” you are correct. You won’t pay attention after a day or two.
EDIT: this menu managing app will need permissios to make screen captures. So much for the privacy. Forgot to mention.
5 replies →
Basically, you are saying "There are 4 lights"
1 reply →
I was surprised to even see it mentioned after all these years, literally haven’t thought about it a single time since I got my first MBP that had it.
3 replies →
I agree. It was very annoying to me to spend the money (and on the nano matte one too) and still have that stupid notch. But it never makes any difference at all which is good news.
Except that it hides stuff...
7 replies →
Same, have a very old MBP. Not sure what to do because I don’t want to wait a year and a half. That coupled with today’s price increases make it a tougher decision.
You can turn off the notch, I mean crop it out at least.
In the long run I truly believe local AI will win and Apple will be the world's most important AI company because of these chips. Imagine something like today's Opus running for free and in complete privacy on your local machine with a beautiful Apple UX on top. For most tasks for most people, that's a much better proposition than a frontier model in the cloud you have to pay for and send all your data to and that only works when you're online.
>In the long run I truly believe local AI will win
What do you mean by 'win'?
For a normal coder/person's use cases, yes. But AI companies are becoming more specialised in different fields and these tailored models will be leagues ahead in those niches.
The way I see it - Opus 4.8 xhigh can do any programming task with a programmer instructing it. If Apple releases local model together with a device that can run said model it would render OpenAI/Anthropic useless for vast majority of usecases.
And if a local mcahine can run something like Opus 4.8, who is to say that those "specialized" models would just not come at a later date, or even loading open models wouldn't be an option with something like M7-verified flag from huggingface that would make it extremely easy for any consumer to just play around.
1 reply →
There is built-in demand for local LLMs. An obvious example is law firms where using remote AI tools may be breaking privilege [1]. Any medical applications may likewise run into legal issues.
The problem is basically that we can't have nice things. AI chat logs themselves become another commodity to sell and to train on. We recently had a story about how Chinese firms are reselling Claude tokens [2]. The chat logs are a commodity here.
The only way to avoid this is to run LLMs locally. Even if you trust someone like Anthropic or Google, case law simply hasn't been established that the chat logs aren't discoverable.
Add to that that a sub-$5000 PC with a 5090 can already run a 31B model at reasonable inference speeds. Not amazing but good enough for many applications. Obviously that can't compete with Mythos but it doesn't have to. It also shows where the trend line is going for hardware. A $10k Nvidia GPU from 10 years ago now sells for scrap. What a consumer-level computer in 5 years can run locally will probably shock a lot of people.
[1]: https://news.ycombinator.com/item?id=48667495
I would say local AI is very real. I use it but so many here am on other forums do so nowadays as well. This is the reason I just cannot fathom the valuations of the AI firms out there.
At this point can Apple profit from selling any contracts they have with TSMC?
If they make a deal with say google to delay their own chips, could they profit more than by selling their production?
Demand is so crazy idk if this would begin to make sense
Mac mini Pro line is doomed, they never made enough of it; skipped M5 Pro, now skipping M6 Pro, it is like 2014-2018 again. Now ordering a custom M4 Pro build take 3 months+ to ship with an increased price.
I was waiting for a MacBook Pro M6 Max and now I don’t know what to do, especially with the price increase I feel like I really screwed up not just getting an MBP M5 Max a month ago
Just buy now. DRAM prices are not coming down any time soon, and Apple may be forced to raise prices again.
The question is what will you be using if you don't.
Are you upgrading from a perfectly good machine? Then wait.
There’s not a lot of detail in the article but that doesn’t mean we have to link to a pay walled thing. https://www.macrumors.com/2026/06/25/2027-macs-m7-chips/
really stupid question, but why doesn't the US gov work with someone like apple to build a american fab with like 1 trillion dollars budget?
some kind of private-public partnership
sorry if thats already happening in some capacity, like i said - "stupid question"
because America can't compete. Build a fab in the US, labor unions, labor costs, regulations, land, energy, taxes, government, water, etc all make this not economical. Everything would cost twice as much and you'd rather buy the cheaper product and it'll be bankrupt. There were reasons why all the manufacturing went overseas to Asia. You're right, the demand right now is HUGE but it won't always be huge. At this point, we don't have the talent or the knowledge to do it well anyway which is why we needed TSMC and Samsung to bring employees over to train people. https://www.cppionline.org/wp-content/uploads/2017/07/The-De...
i wonder, what about the manhattan project? they were able to do that very secretly, i understand it was a different time.
but can the gov not just fast track this as a "national security" or something?
i think the usa should be the one who make 1nm or smaller chips on demand, even if it takes 5-10. years to do.
and yes i realize i might sound dumb here but i'm the one suffering from high hardware prices!!
they’re doing m7 on the intel 18a fab, which is exactly that
À fab takes a good decade to build, then another one to become profitable
Everyone seems to miss it but the article also says that M5 Ultra Mac Studio is coming out later this year. Yay!
I wonder how much the rumored 768GB RAM version will cost.
I am waiting till apple copies the "allocation" concept from high end car manufacturers. "Sure, buy the 25 iphones ans we will gladly put you on the waitlist."
This makes no sense. Apple doesn't need to generate artificial demand for their products. Apple doesn't need (or want) a perception of exclusivity.
2 replies →
[dead]
Apple to skip high-end versions of M6 Mac chips...
I read it as the M6 being "high-end" in general, and Apple skipping the whole generation, which made no sense to me. But they are going to use the M6 at all, just not bother to create Max and Ultra versions of it.
So the big question: Is this an excuse to save on memory costs and delaying stuff like the M5 Ultra, M6 Max, etc until 2027 when memory prices come back down?
Is it safe to assume they will come down in 2027?
I think it is safe to assume they won't come down in 2027
Given that M6 will be on TSMC smaller 2nm node and the first smaller node size in 3-years, it seems like the oddest of all years for the high-end Macs to skip.
my 2 cents is that a new tech node is harder to produce variants on. it's easier to make new flavors of a mature tech node
2028 local and onprem agentic revolution. enterprises will pay for expensive mac line then
hyperscalers better all IPO in the next 8 quarters
I’m hoping they put a lot more silicon in the GPU so when I’m not running a local LLM the game I play runs smoother
Counter theory: the M6 is so good that they want to keep some oomph for the M7 line up.
My predictions:
1. NVidia aggressively segments the market on VRAM and will continue to do so. A 5090 with 32GB of RAM, ~21k CUDA cores and 1800GB/s of memory bandwidth is $3-4k. An RTX 6000 Pro with 96GB of RAM, ~24k CUDA cores and 1800GB/s memory bandwidth is ~$11k;
2. The 5090 won't be replaced until late 2028 or even 2029. There has been no mid-cycle refresh (eg 4080 Super vs 4080) and likely won't be either at all or for at least a year. If there is in a year, it basically confirms that the 6000 series won't be until 2028/2029. Also, the x090 never got a mid-cycle refresh so the current consumer high-end is staying that way for years;
3. The 6090 whenever it comes will still have 32GB of VRAM unless the memory market drastically changes;
4. Many have anticipated an M5 Max/Ultra refresh of the Mac Studio line in Q3. Given that Apple chose to hike the prices on Studios rather than discontinue them, I now think this isn't going to happen. We may not see a Studio refresh for up to 2 years. Apple has done this before with the Mac Pro;
5. M7 Max/Ultra will probably go to a memory bandwidth of 1.2-1.8TB/s vs the current tops of M3 Ultra, M4 Max and M5 Max of 600-900GB/s. This simply needs to go up to boost inference speed;
6. You'll also see the number of GPU cores go up. All of this will add up to an M7 Max being 50-80%+ of the performance of a 5090. That's huge given the shared memory architecture;
7. We may see the return of Apple using its massive cash pile for vendor-financing of an exclusive memory supply. This was one of Tim Apple's [sic] big innovations.
Local AI isn’t gonna help Apple, especially not with the rate hardware prices are increasing.
They need to pull out of this half assed bandwagon approach.
Local AI is going to help Apple, especially with a return to normal RAM pricing being an inevitability, even if it takes years.
They don't need to pull out of this approach.
How is it going to help them?
Do you really think the average Apple user will use it when there’s already better AI provided by OpenAI and Anthropic which don’t require advanced local hardware?
2 replies →
How about we release M5 Ultra first?
I'd even buy a M4 Ultra....
Bro just give me a new iPhone mini
You will have a massive phone and you will be happy.
No one buys the smaller phones because people care more about battery life than ergonomics
2 replies →
I will settle for a slightly larger iPhone that unfolds into a iPad mini.
Q
Come on Apple - just buy TSMC and fully kit out the RAM in all Mac Studios - you could even make (more of) a fortune selling the excess.
There's already reporting that M7 will be on Intel 18A - Apple's giving Nvidia and Broadcom and others more TSMC capacity back.
The URL above is wrong. At present it is https://www.bloomberg.com/news/articlehttps://www.bloomberg....
I guess it should be https://www.bloomberg.com/news/articles/2026-06-25/apple-to-...
Thanks for catching that - unfortunately I can't edit the submission URL, but I've emailed hn@ycombinator.com to see if the mods can fix it.
EDIT: gift link if paywalled (archive.is capture is truncated): https://www.bloomberg.com/news/articles/2026-06-25/apple-to-...
Fixed now. Thanks to you both!
[flagged]
[dead]
[dead]
[dead]
Apple is very late to the AI party. By the time M7 is shipped, Nvidia will announce 6090 and people will be buying used (3|4|5)090 GPUs to run local models at much better performance than heat throttled M7.
This a significant misunderstanding of which party it is Apple wants to attend.
And 6090 will have 48GB of RAM compared to something like an M7 Max that might have 192GB or an M7 Ultra that might have 768GB.
The M7 Max and M7 Ultra will likely prefill-bottlenecked at 100GB+ scale inference. Layered 6090s would not be.
1 reply →
What people? Are you seriously thinking the hundreds of millions of customers Apple have is going to be buying run-to-the-ground GPUs second hand and build local workstations for AI? Might as well ask them to self host email while you’re at it.
The difference between these two is that one of them is an unsolved research problem that we’ve all spent far too much time on, and the other is just running an LLM.
I would prefer a Studio if it does a decent enough job even if throttles a bit under load, way less power usage and noise than those GPUs plus the PC you need to put those in.
If you're fine overpaying for a throttling computer, you could buy 40-series cards and underclock them to the same TDP of a Mac Studio.
You'd probably get faster prefill speeds, as well as better drivers for accelerated transcode and gaming applications.
Yeah but you could heat your whole house!
RAM is a commodity and nvidia will be paying the same prices. The used market will reflect the cost of RAM. nvidia owns the top of the market but many of us don't need that.
same people who bought all mac mini for ai?
Theyve dropped the ball bigtime.
Apple isn't just transitioning to TSMC's 2nm node, they are also transitioning to a chiplet based design using TSMC's advanced packaging.
> What sets the A20 apart isn’t just the node shrink—it’s the revolution in packaging. Apple is transitioning to Wafer-Level Multi-Chip Module (WLCM) integration, meaning that RAM will no longer be situated beside the chip, but rather on the chip wafer itself, integrated alongside the CPU, GPU, and Neural Engine.
This shift eliminates the need for silicon interposers and substrates, thereby enhancing signal integrity, improving thermal dissipation, and facilitating faster memory access with lower latency. The benefits? Better multitasking, smoother AI processing (hello, Apple Intelligence), improved battery life, and potentially a smaller chip footprint—freeing up space for other components.
https://hwbusters.com/news/apples-a20-chip-ushers-in-a-new-e...
It's entirely possible that TSMC is ramping up more slowly than expected.
Do we have any explanations of what WLCM means that are more industry focused? I couldn't find anything that didn't look like blogspam. And that explanation of the DRAM being on the same wafer doesn't really make sense. For one, at that point there's no "multi chip" part if you're integrating more onto the same die rather than less.
And their explanation isn't really passing the smell test for me for other reasons, for instance the fact that DRAM processes are pretty radically different than bulk logic processes, which wouldn't really let you put it all on the same wafer, much less the same die. Even back in the day when you had eDRAM blocks (like the Xbox 360's eDRAM die), that was really a DRAM process with a bit of logic cells that wouldn't be competitive if they weren't sitting right next to the DRAM blocks.
I could be wrong here though, my examples are more than a bit long in the tooth.
The terms to search for are fan-out wafer level packaging (FOWLP) and TSMC InFO. The chiplets come from different wafers and are reconstituted into a molded plastic wafer, allowing multiple die side-by-side. Then multiple layers of wires are built on top, terminating in a BGA.
3 replies →
You can start by reading up on TSMC's name for the tech (although there are many versions at TSMC and TSMC isn't the only company packaging chiplets and memory on top of a silicon interposer).
> CoWoS (Chip-on-Wafer-on-Substrate)
https://semiwiki.com/wikis/industry-wikis/cowos-chip-on-wafe...
It's a more advanced update from their older InFO tech.
3 replies →
A kind request - please try to write HN replies without AI, but if you're going to, please at least edit out any "it's not X its Y" or "isn't just X, but also Y" AI tics. A lot of us come here to get away from talking to AIs all day.
The comment you're replying to doesn't sound like AI to me
3 replies →
Is there anything less interesting on this site than baseless claims that other people's posts are AI?
1 reply →
So far the only thing I've seen useful out of apple intelligence is running parakeet natively and effectively... which should have been their very first feature... given it's been on phones for 10+ years.
As someone who wants to run effective llms locally for many things their other big benefit has been the unified memory studios for a small bit.
[flagged]
Please don't use HN primarily for battle over geopolitical disputes. The guidelines make it clear we're trying to avoid that here. https://news.ycombinator.com/newsguidelines.html