I chased down what the "4x faster at AI tasks" was measuring:
> Testing conducted by Apple in January 2026 using preproduction 13-inch and 15-inch MacBook Air systems with Apple M5, 10-core CPU, 10-core GPU, 32GB of unified memory, and 4TB SSD, and production 13-inch and 15-inch MacBook Air systems with Apple M4, 10-core CPU, 10-core GPU, 32GB of unified memory, and 2TB SSD. Time to first token measured with an 8K-token prompt using a 14-billion parameter model with 4-bit quantization, and LM Studio 0.4.1 (Build 1). Performance tests are conducted using specific computer systems and reflect the approximate performance of MacBook Air.
>Time to first token measured with an 8K-token prompt using a 14-billion parameter model with 4-bit quantization
Oh dear 14B and 4-bit quant? There are going to be a lot of embarrassed programmers who need to explain to their engineering managers why their Macbook can't reasonably run LLMs like they said it could. (This already happened at my fortune 20 company lol)
So it's not measuring output tokens/s, just how long it takes to start generating tokens. Seems we'll have to wait for independent benchmarks to get useful numbers.
For many workflows involving real time human interaction, such as voice assistant, this is the most important metric. Very few tasks are as sensitive to quality, once a certain response quality threshold has been achieved, as is the software planning and writing tasks that most HN readers are likely familiar.
I think these aren't meant to be representative of arbitrary userland-workload LLM inferences, but rather the kinds of tasks macOS might spin up a background LLM inference for. Like the Apple Intelligence stuff, or Photos auto-tagging, etc. You wouldn't want the OS to ever be spinning up a model that uses 98% of RAM, so Apple probably considers themselves to have at most 50% of RAM as working headroom for any such workloads.
On my 24GB RAM M4 Pro MBP some models run very quickly through LM Studio to Zed, I was able to ask it to write some code. Course my fan starts spinning off like the worlds ending, but its still impressive what I can do 100% locally. I can't imagine on a more serious setup like the Mac Studio.
For anyone who has been watching Apple since the iPod commercials, Apple really really has grey area in the honesty of their marketing.
And not even diehard Apple fanboys deny this.
I genuinely feel bad for people who fall for their marketing thinking they will run LLMs. Oh well, I got scammed on runescape as a child when someone said they could trim my armor... Everyone needs to learn.
Yesterday I ran qwen3.5:27b with an M1 Max and 64 GB of ram. I have even run Llama 70B when llama.cpp came out. These run sufficiently well but somewhat slow but compared to what the improvements with the M5 Max it will make it a much faster experience.
I don't know that there would be a huge overlap between the people who would fall for this type of marketing and the people who want to run LLMs locally.
There definitely are some who fit into this category, but if they're buying the latest and greatest on a whim then they've likely got money to burn and you probably don't need to feel bad for them.
Reminds me of the saying: "A fool and his money are soon parted".
That's how they make loot on their 128GB MacBook Pros. By kneecapping the cheap stuff. Don't think for a second that the specs weren't chosen so that professional developers would have to shell out the 8 grand for the legit machine. They're only gonna let us do the bare minimum on a MacBook Air.
A bit strange to use time to first token instead of throughput.
Latency to the first token is not like a web page where first paint already has useful things to show. The first token is "The ", and you'll be very happy it's there in 50ms instead of 200ms... but then what you really want to know is how quickly you'll get the rest of the sentence (throughput)
As far as benchmarketing goes they clearly went with prefill because it's much easier for apple to improve prefill numbers (flops-dominated) than decode (bandwidth-dominated, at least for local inference); M5 unified memory bandwidth is only about 10% better than the M4.
To add to the sibling "good is relative" it also depends what you're running, not just your relative tolerances of what good is. E.g. in a MoE the decode speedup means the speed of prompt processing delay is more noticeable for the same size model in RAM.
Not strange, for the kind of applications models at that size are often used for the prefill is the main factor in responsiveness. Large prompt, small completion.
No you don't. Not as a sticky mushy human with emotions watching tokens drip in. There's a lot of feeling and emotion not backed by hard facts and data going around, and most people would rather see something happening even if it takes longer overall. Hence spinner.gif, that doesn't actually remotely do a damned thing, but it gives users reassurance that they're waiting for something good. So human psychology makes time to first token an important metric to look at, although it's not the only one.
"Scaling up performance from M5 and offering the same breakthrough GPU architecture with a Neural Accelerator in each core, M5 Pro and M5 Max deliver up to 4x faster LLM prompt processing than M4 Pro and M4 Max, and up to 8x AI image generation than M1 Pro and M1 Max."
Are they doubling down on local LLMs then?
I still think Apple has a huge opportunity in privacy first LLMs but so far I'm not seeing much execution. Wondering if that will change with the overhaul of Siri this spring.
I think its just marketing, and the marketing is working. Look how many people bought Minis and ended up just paying for API calls anyway. (Saw it IRL 2x, see it on reddit openclaw daily)
I don't mind it, I open Apple stock. But I'm def not buying into their rebranding of integrated GPU under the guise of Unified Memory.
> Look how many people bought Minis and ended up just paying for API calls anyway. (Saw it IRL 2x, see it on reddit openclaw daily)
Aren't the OpenClaw enjoyers buying Mac Minis because it's the cheapest thing which runs macOS, the only platform which can programmatically interface with iMessage and other Apple ecosystem stuff? It has nothing to do with the hardware really.
Still, buying a brand new Mac Mini for that purpose seems kind of pointless when a used M1 model would achieve the same thing.
Itās exactly that. They are buying the base model just for that. You are not going to do much local AI with those 16GB of ram anyway, it could be useful for small things but the main purpose of the Mini is being able to interact with the apple apps and services.
16GB should be enough for TTS/Voice models running locally no ? I was thinking about having a home assistant setup like that where the voice is local and the brain is API based
Sure, thatās why I said maybe itās useful for a few things. But the main reason people were recommending the Mini was for its price (base model) and having access to the Apple services for clawdbot to leverage. Not precisely for local AI.
No one is buying a base model Mac for local LLM. Everyone is forgetting the PC prices have drastically increased due to RAM and SSD. Meanwhile, Macs had no such price changeā¦ at least for the models that didnāt just drop today. Macās are just a good deal at the moment.
Yeah because Mac upgrade prices were already sky high, long before the component shortage. 32GB of DDR5-6000 for a PC rocketed from $100 to $500, while the cost of adding 16GB to a Mac was and still is $400.
I'm kind of curious how Apple's supply contracts actually work, because it's currently more attractive to buy a Mac with a lot of RAM than it usually is, relative to a PC. So if it's "we negotiated a price and you give us as much RAM as we sell machines" the company supplying the RAM is getting soaked because they're having to supply even more RAM to Apple for a below-market price.
But if the contract was for a specific amount of RAM and then people start coming to Apple more for high RAM machines, they're going to exhaust their contract sooner than usual and run out of cheap memory to buy. Then they have to decide if they want to lower their margins or raise the already-high price up to nosebleed levels.
Worse than that, they hold their value, so buying a used M1 mini is still a few hundred bucks, and saving $200-300 by purchasing a 5 generation older mini seems like a bad deal in comparison.
Someone came to be excited they got a "deal" on the newest Intel Mac Mini for hosting OpenClaw. 8GB model for $300. I kind of regret bursting their bubble by telling them you can walk over to Costco (nearest one at time of discussion was walking distance) and pay $550 for one with an M4 and 16GB of RAM.
> Aren't the OpenClaw enjoyers buying Mac Minis because it's the cheapest thing which runs macOS
That's likely only part of the reason. Mac Mini is now "cheap" because everyone exploded in price. RAM and SSD etc have all gone up massively. Not the mention Mac mini is easy out of the box experience.
It's not cheap, though. Two weeks ago I bought a computer with a similar form factor (GMKtec G10). Worse CPU and GPU but same 16GB memory and a larger SSD for 40% the price of a base mac mini ($239 vs $599). It came with Windows preinstalled, but I immediately wiped that to install linux. Even a used (M-series) mac mini is substantially more expensive. It will cost me about an extra penny per day in electricity costs over a mac mini, but I won't be alive long enough for the mac mini to catch up on that metric.
I considered the mac mini at the time, but the mac mini only makes sense if you need the local processing power or the apple ecosystem integration. It's certainly not cheaper if you just need a small box to make API calls and do minimal local processing.
If you just need "a small box to make API calls and do minimal local processing" you an also just buy a RPI for a fraction of the price of the GMKtec G10.
All 3 serve a different purpose; just because you can buy a slower machine for less doesn't mean the price:performance of the M1 Mac Mini changes.
> you an also just buy a RPI for a fraction of the price of the GMKtec G10.
Sadly not really. The Pi 5 8gb canakit starter set, which feels like a more true price since it's including power supply, MicroSD card, and case, is now $210. The pi5 8gb by itself is $135.
A 16gb pi5 kit, to match just the RAM capacity to say nothing of the difference in storage {size, speed, quality} and networking, is then also an eye watering $300
Bro. The used M1 mini and studio are all gone. I was thinking of buying one for local AI before openclaw came out and went back to look and the order book is near empty. Swappa is cleared out. eBay is to the point that the m1 studio is selling for at least a thousand more.
This arb youāre talking about doesnāt exist. An m1 studio with 64 gb was $1300 prior to openclaw. Youāre not getting that today.
I would have preferred that too since I could Asahi it later. Itās just not cheap any more. The m4 is flat $500 at microcenter.
Why not? The integrated GPUs are quite powerful, and having access to 32+ GB of GPU memory is amazing. There's a reason people buy Macs for local LLM work. Nothing else on the market really beats it right now.
My M4 MacBook Pro for work just came a few weeks ago with 128 GB of RAM. Some simple voice customization started using 90GB. The unified memory value is there.
Jeff Geerling had a video of using 4 Mac Studios each with 512GB RAM connected by Thunderbolt. Each machine is around $10K so this isn't cheap but the performance is impressive.
Itās what a small business might have paid for an onprem web server a couple of decades ago before clouds caught on. I figure if a legal or medical practice saw value in LLMs it wouldnāt be a big deal to shove 50k into a closet
You would still have to do some pretty outstanding volume before that makes sense over choosing the "Enterprise" plan from OpenAI or Anthropic if data retention is the motivation.
Assuming, of course, that your legal team signs off on their assurance not to train on or store your data with said Enterprise plans.
But why? Spending several thousand dollars to run sub-par models when the break-even point could still be years away seems bizarre for any real usecase where your goal is productivity over novelty. Anyone who has used Codex or Opus can attest that the difference between those and a locally available model like Qwen or Codestral is night and day.
To be clear, I totally get the idea of running local LLMs for toy reasons. But in a business context the sell on a stack of Mac Pros seems misguided at best.
I ran the qwen 3.5 35b a3b q4 model locally on a ryzen server with 64k context window and 5-8 tokens a second.
It is the first local model I've tried which could reason properly. Similar to Gemini 2.5 or sonnet 3.5. I gave it some tools to call , asked claude to order it around, (download quotes, print charts, set up a gnome extension) even claude was sort of impressed that it could get the job done.
Point is, it is really close. It isn't opus 4.5 yet, but very promising given the size. Local is definitely getting there and even without GPUs.
But you're right, I see no reason to spend right now.
Getting Opus to call something local sounds interesting, since that's more or less what it's doing with Sonnet anyway if you're using Claude Code. How are you getting it to call out to local models? Skills? Or paying the API costs and using Pi?
Assuming you ran the gamut up from what you could fit on 32 or 64GB previously, how noticeable is the difference between models you can run on that vs. the 512GB you have now?
I've been working my way up from a 3090 system and I've been surprised by how underwhelming even the finetunes are for complex coding tasks, once you've worked with Opus. Does it get better? As in, noticeably and not just "hallucinates a few minutes later than usual"?
I'm not really into AI and LLMs. I personally don't like anything they output. But the people I know who are into it and into running their own local setups are buying Studios and Minis for their at home local LLM set ups. Really, everyone I personally know who is doing their build your own with local LLMs are doing this. I don't know anyone anymore buying other computers and NVIDIA graphics cards for it.
I think people buying those don't realize requirements to run something as big as Opus, they think those gigabytes of memory on Mac studio/mini is a lot only to find out that its "meh" on context of LLMs. Plus most buy it as a gateway into Apple ecosystem for their Claws, iMessage for example.
> But I'm def not buying into their rebranding of integrated GPU under the guise of Unified Memory.
But it is Unified Memory? Thanks to Intel iGPU term is tainted for a long time.
I've tried to use a local LLM on an M4 Pro machine and it's quite painful. Not surprised that people into LLMs would pay for tokens instead of trying to force their poor MacBooks to do it.
Local LLM inference is all about memory bandwidth, and an M4 pro only has about the same as a Strix Halo or DGX Spark. That's why the older ultras are popular with the local LLM crowd.
And while it is stupid slow, you can run models of hard drive or swap space. You wouldnāt do it normally, but it can be done to check an answer in one model versus another.
Try a software called TG Pro lets you override fan settings, Apple likes to let your Mac burn in an inferno before the fans kick in. It gives me more consistent throughput. I have less RAM than you and I can run some smaller models just fine, with reasonable performance. GPT20b was one.
What models are you using? Iāve found that SOTA Claudes outperform even gpt-5.2 so hard on this that itās cheaper to just use Sonnet because num output tokens to solve problem is so much lower that TCO is lower. Iām in SF where home power is 54Ā¢/kWh.
Sonnet is so fast too. GPT-5.2 needs reasoning tuned up to get tool calling reliable and Qwen3 Coder Next wasnāt close. I havenāt tried Qwen3.5-A3B. Hearing rave reviews though.
If youāre using successfully some model knowing that alone is very helpful to me.
We had a workshop 6 months ago and while I've always been sceptical of OpenAI,etc's silly AGI/ASI claims, the investments have shown the way to a lot of new technology and has opened up a genie that won't be put back into the bottle.
Now extrapolating in line with how Sun servers around year 2000 cost a fortune and can be emulated by a 5$ VPS today, Apple is seeing that they can maybe grab the local LLM workloads if they act now with their integrated chip development.
But to grab that, they need developers to rely less on CUDA via Python or have other proper hardware support for those environments, and that won't happen without the hardware being there first and the machines being able to be built with enough memory (refreshing to see Apple support 128gb even if it'll probably bleed you dry).
The only "push" towards Metal compatibility there's been has been complaints on github issues. Not only has none of the work been done, absolutely nobody in their right mind wants to work on Metal compatibility. Replacing proprietary with proprietary is absolutely nobody's weekend project. or paid project.
I think that might be partly because on regular PC's you can just go and buy an NVidia card insteaf of fuzzing around with software issues, and for those on laptops they probably hope that something like Zluda will solve it via software shims or MS backed ML api's.
Basically, too many choices to "focus on" makes non a winner except the incumbent.
I certainly only use Macs when being project assigned, then there are plenty of developers out there whose job has nothing to do with what Apple offers.
Also while Metal is a very cool API, I rather play with Vulkan, CUDA and DirectX, as do the large majority of game developers.
Honestly though, gamedevs really are among the biggest Windows stalwarts due to SDK's and older 3d software.
Only groups of developers more tied to Windows that I can think of are probably embedded people tied due to weird hardware SDK's and Windows Active Directory dependent enterprise people.
Outside of that almost everyone hip seems to want a Mac.
That's the broad developer community. 90%+ of the engineers at Big Tech and the technorati startups are on MacOS with 5% on Linux and the other 5% on Windows.
Youāll see a lot of MacBooks in Beijingās zhongguangcun where all the tech companies are, but they also have a lot of students there as well, so who knows. You need to go out to the suburbs where Lenovo has offices to stop seeing them. I know Apple is common in Western Europe having lived there for two years (but that was 20 years ago, I lived in China for 9 years after that).
It wouldnāt surprise me if the deepseek people were primarily using Macās. Maybe Alibaba might be using PCs? Iām not sure.
I think it's reasonable to say that the people responding to surveys on Stack Overflow aren't the same people who work on pushing the state of the art in local LLM deployment. (which doesn't prove that that crowd is Apple-centric, of course)
It's not the whole answer, but SO came from the .NET world and focused on it first so it had a disproportionately MS heavy audience for some time. GitHub had the same issue the other way around. Ruby was one of GitHub's top five languages for its first decade for similar reasons.
Except CUDA feels really cozy, because like Microsoft, NVidia understands the Developers, Developers, Developers mantra.
People always overlook that CUDA is a polyglot ecosystem, the IDE and graphical debugging experience where one can even single step on GPU code, the libraries ecosystem.
And as of last year, NVidia has started to take Python seriously and now with cuTile based JIT, it is possible to write CUDA kernels in pure Python, not having Python generate C++ code that other tools than ingest.
Neural Accelerators (aka NAX) accelerates matmults with tile sizes >= 32. From a very high level perspective, LLM inference has two phases: (chunked) prefill and decode. The former is matmults (GEMM) and the latter is matrix vector mults (GEMV). Neural Accelerators make the former (prefill) faster and have no impact on the latter.
There already are a bunch of task-specific models running on their devices, it makes sense to maintain and build capacity in that area.
I assume they have a moderate bet on on-device SLMs in addition to other ML models, but not much planned for LLMs, which at that scale, might be good as generalists but very poor at guaranteeing success for each specific minute tasks you want done.
In short: 8gb to store tens of very small and fast purpose-specific models is much better than a single 8gb LLM trying to do everything.
Given all the supply issues w/ Nvidia, I think Apple's AI strategy should be - local AI everything (not just LLMs), but also make Metal competitive w/ CUDA. Their ace in the hole is the unified memory model.
The hardware capabilities that make local LLMs fast are useful for a lot of different AI workloads. Local LLMs are a hot topic right now so thatās what the marketing team is using as an example to make it relatable.
But memory bandwidth (bottleneck for LLM inference) is only marginally improved, 614 GB/s vs 546 GB/s for M4/M5 Max - where is this 4x improvement coming from?
Honestly, I think that's the move for apple. They do not seem to have any interest in creating a frontier lab/model -- why would they give the capex and how far behind they are.
But open source models (Kimi, Deepseek, Qwen) are getting better and better, and apple makes excellent hardware for local LLMs. How appealing would it be to have your own LLM that knows all your secrets and doesnt serve you ads/slop, versus OpenAI and SCam Altman having all your secrets? I would seriously consider it even if the performance was not quite there. And no need for subscription + cli tool.
I think apple is in the best position to have native AI, versus the competition which end up being edge nodes for the big 4 frontier labs.
RE Frontier models/hardware: I'm interested to see what happens with their "private cloud compute" marketing concept now that they're moving from running Siri AI experiences on Apple servers to Google servers instead.
I love the push to local llms. But itās hilarious how apple a few years ago was so reluctant to even mention āAIā in its keynotes and fast forward a couple years theyāve fully embraced it. I mean I like that they embraced it rather than be ādifferentā (stubborn) and stay behind the tech industry. Itās the smart choice. I just think itās funny.
Apple's AI strategy really kind of threads the needle cleverly.
"AI" (LLMs) may or may not have a bubble-pop moment, but until it does Apple get to ride it on these press releases and claims. But if the big-pop occurs, then Apple winds up with really fantastic hardware that just happens to be good at AI workloads (as well as general computing).
For example, image classification (e.g. face recognition/photo tagging), ASR+vocoders, image enhancement, OCR, et al, were popular before the current boom, and will likely remain popular after. Even if LLM usage dries up/falls out of vogue, this hardware still offers a significant user benefit.
What is more likely to happen though is that it doesn't take multiple $10B of datacenter and capital to build out models--and the performance against LLM benchmarks starts to max out to the point where throwing more capital at it doesn't make enough of a difference to matter.
Once the costs shrink below $1B then Apple could start building their own models with the $139B in cash and marketable securities that they have--while everyone else has burned through $100B trying to be first.
Of course the problem with this strategy right now is that Siri really, really sucks. They do need to come up with some product improvements now so that they don't get completely lapped.
They could run fine on the CPU too. But these are mobile devices, therefore battery usage is another significant metric. Dedicated hardware is more energy efficient than general hardware, and GPU in particular is a power-hog.
Exactly. It's the same thing as video or audio encoding and decoding. Sure the CPU could do it, potentially use the GPU, but having actual hardware encoders and decoders for the most common codecs will save a lot of energy.
Not if GPU RAM is a limiter. Which it is for most models.
Unified memory is a serious architectural improvement.
How many GPUs does it take to match the RAM, and make up for the additional communication overhead, of a RAM-maxed Mac? Whatever the answer, it wonāt fit in a MacBook Proās physical and energy envelopes. Or that of an all-in-one like the Studio.
It is simply marketing nonsense - what they really mean (I think) is they support matrix multiplication (matmul) at the hardware level which given AI is mostly matrix multiplications you'll get much faster inference (and some increase in training too) on this new hardware. I'm looking forward to seeing how fast a local 96gb+ LLM is on the M5 Max with 128gb of RAM.
We've already established in this thread that memory bandwidth isn't that much greater than M4 Max - 12%? However, I wonder if batched inference will benefit greatly from the vastly improved compute. My guess is that parallel usage of the same model will be a couple times faster. So, single "threaded" use not that much better, but say you want to run a lot of batch jobs, it'd be way faster?
Itās not necessarily doubling down on local. The reality is your LLM should be inferencing every tick ā¦ the same way your brain thinks every. Fucking. Nano. Second.
So yes, the LLM should be inferencing on your prompt, but it should also be inferencing on 25,000 other things ā¦ in parallel.
Those are the compute needs.
We just need compute everywhere as fast as possible.
I've been so disappointed in Apple's lack of execution on this. There is so much potential for fantastic local models to run and intelligently connect to cloud models.
I just don't get why they're dropping the ball so much on this.
A useful llm that needs 64gb of ram and mid double digit cores is not useful for 99% of their customers. The LLMs they have on iphone 17's certainly cannot do anything useful other than summerization and stuff. It's a hardware constraint that they have.
Apple absolutely has a massive opportunity here because they used a shared memory architecture.
So as most people in or adjacent to the AI space know, NVidia gatekeeps their best GPUs with the most memory by making them eye-wateringly expensive. It's a form of market segmentation. So consumer GPUs top out at 16GB (5090 currently) while the best AI GPUs (H200?) is 141GB (I just had to search)? I think the previou sgen was 80GB.
But these GPUs are north of $30k.
Now the Mac Studio tops out currently at 512GB os SHARED memory. That means you can potentially run a much larger model locally without distributing it across machines. Currently that retails at $9500 but that's relatively cheap, in comparison.
But, as it stands now, the best Apple chips have significantly lower memory bandwidth than NVidia GPUs and that really impacts tokens/second.
So I've been waiting to see if Apple will realize this and address it in the next generation of Mac Studios (and, to a lesser extend, Macbook Pros). The H200 seems to be 4.8TB/s. IIRC the 5090 is ~1.8TB/s. The best Apple is (IIRC) 819GB/s on the M3 Ultra.
Apple could really make a dent in NVidia's monopoly here if they address some of these technical limitations.
So I just checked the memory bandwidth of these new chips and it seems like the M5 is 153GB/s, M5 Pro is ~300 and M5 Max is ~600. I was hoping for higher. This isn't a big jump from the M4 generation. I suspect the new Studios will probably barely break 1TB/s. I had been hoping for higher.
Hard to get 6000+ bit memory bus HBM bandwidth out of a 512 or 1024 bit memory bus tied to DDR... I think it's also just tough to physically tie in 512 gigs close enough to the GPU to run at those speeds. But yeah, I wish there was a very competitive local option, too, short of spending $50k+.
The topic is MacBook, so my criticism is a little off. However, I really dont believe in this "local LLM" promise from Apple. My phone already gets noticeably warm if I answer 5 WhatsApp messages. And looses 5% of battery during the process. I highly doubt Apple will have a useable local LLM that doesn't drain my battery in minutes, before 2030.
Something is not right if WhatsApp is seriously draining your phone like that. Admittedly Iām not a big WhatsApp user my iPhone hasnāt had any trouble like that with it.
What % of users actually care that much about local LLMs? It appears to still be an inferior (though maybe decent) service compared to ChatGPT etc., and requires very top-end hardware. Is privacy _that_ important to people when their Google search history has been a gateway to the soul for years? I wonder if these machines would cost significantly less (or put the cost to other things, e.g. more CPU cores) without this emphasis on LLMs.
> I still think Apple has a huge opportunity in privacy first LLMs
This correlation of Apple and privacy needs to rest. They have consistently proven to be otherwise - despite heavily marketing themselves as "privacy-first"
No other company makes you tell them every application you install on your device. No other company makes you tell them every location you read from your GPS sensor.
I think it's all about relativity. Are they private compared to an open source privacy focused OS like grapheneOS and the fantastic folks running that project? No. Are they more private than a company like meta or google who has much worse incentives for privacy than Apple? Probably.
Do I wish Apple was way more transparent and gave users more control over gatekeeper and other controversial features that erode privacy? Absolutely.
Not for everything. Apple has initially focused on edge AI that runs locally per device. It didnāt work out well the first try, but I would still bet on them trying again once compute catches up. Besides, they still have a better track record than the other tech giants.
> The new 14- and 16-inch MacBook Pro with M5 Pro and M5 Max mark a major leap for pro users. Thereās never been a better time for customers to upgrade from a previous generation of MacBook Pro with Apple silicon or an Intel-based Mac.
I read as "Whoops we made the M1 Macbook Pro too good, please upgrade!"
I think I will get another 2-5 years out my mine.
Apple: If you document the hardware enough for the Asahi team to deliver a polished Linux experiene, I'll buy one this year!
My 32gb m1 max was probably the best purchase I've made. Still plenty of headroom in performance left in this beast. Wonder what reason they'll use to end software support in the future. Bet it'll be some security hardware they make up for the sake of forcing upgrades.
my tinfoil hat theory is that they make small features depend on new hardware.
for example, let's say the new os depends on m5's exclusive thumbnail generator accelerator, and let's say it improves speed by a 20%.
now, your M1 notebook than on previous OSes uses standard gpu acceleration for thumbnails will not have this specialized hardware acceleration, it will have software fallback that will be 90% slower.
you won't notice it a first thought because it's stuff, fast, but it eats a bit of the processor.
multiply this by 1000 features and you have a slow machine.
I don't know how else to explain how an ipad pro cannot even scroll a menu without stuttering, it's insane how fast these things were on release
yes pretty much this. make useless features use up resources and make basic scrolling slow.
the Liquid Glass for example probably is not so great when it comes to resources. Probably works better with latest metal and hardware blocks on the GPU in M5 as opposed to using GPU cores and unified memory on 8gb M1 making latest macOS work not so great. I have the M1 8gb air and it is really slow on Tahoe. It was snappy just a couple of years ago on a fresh install.
I downgraded today for the first time in my life. Sequoia is crazy fast in my MacBook Air m2 16gb
Not upgrading any of my Macs ever again. I was a fanboy looking for every new update like a present, for 13 years, not anymore. It took one Tahoe burn all that trust. Never upgrading major OS versions on hardware from Apple again.
I think this could go equally for Windows as well, and many other software (not just OS). I purpose refrained from Tahoe because I didn't like the design but I wanted to know what the consensus was on it before upgrading. Apparently it's bad!
Win 11 is bad compared to Win 10 as well. I'm fairly new to Linux so I can't really form an opinion there.
Ditto, I don't see myself upgrading in the near future, the 64GB M1 Max I paid 2499 at the end of 2023 still feels like a new machine, nothing I do can slow it down. Apple kept OS updated for around 6 years in Intel times, I don't see how they can drop support for this one tbh. I'm still paying for apple care since I depend on it so much
Some of my M1 MBP Max keys are losing their coating, and the battery is at 74% capacity. At some point soon I'll need a service. But other than that, I have no real complaints. Even the case edge where my arms constantly rest doesn't look too bad.
My next MBP will have 128GB memory, but these prices just wanna make me wait longer.
I've been on a Macbook M1 Pro since 2022 (bought refurbished on Amazon for cheap) and it's still such a powerhouse. It doesn't struggle at all with anything that I throw at it. Kind of amazing.
Nothing has broken and I consistently get 4-6 hours of heavy work time while on battery. An amazing machine for the price I paid.
> I read as "Whoops we made the M1 Macbook Pro too good, please upgrade!"
As there target for that marketing, I can report it hits home!
But objectively, there is nothing wrong with my current experience at all.
I have never had that experience over many generations and types of machines. The M1 keeps looking better and better in hindsight.
ā-
Looking forward, either the M5 is the next M1, a bump of good that will last. Or Apple will be really firing on all cylinders if it can āobsoleteā the M5 anytime soon.
There was a magical window at Google where you could be issued an iMac Pro 5k. (To this day, the standard issue monitor is still 1440p.)
~9 years later, there are a lot of people still using it as their main machine, waiting until we get kicked off the corp network for lack of software support.
Wait, they throw them away, not sell or give to employees? I feel like as long as the computer is reset, indeed it is stupid to just throw it away instead of giving or selling it to someone who wants it.
They could resell, but maybe another way to phrase this, tying the screen to the obsolete computer greatly reduces the useful lifespan of the screen. Then again at that time, DisplayPort didn't do enough bandwidth to have that kind of display externally.
Same, in fact the only reason right now that I would upgrade my m1 pro is if they threaten to change the design by getting rid of the hdmi or sd card slot, or doing something stupid like when they added the touch bar. I was locked into my old intel pro for so long because of all the bad hardware choices they were making.
The only useful thing I remember about the touch bar was the DJ trying to play some beats on the touch bar. That was just weird imo.
Barring removal of Esc key, I think the touch bar was useful because it showed contextual actions. But not every app used it so it didn't really get a chance to shine.
I guess I'm just a luddite that spends my life on a CLI or text editor. Taking my hands away from my keyboard to leave finger prints on my screen just doesn't make sense to me.
I think people that do do tasks where a touch screen makes sense are probably just doing most of their work on an iphone or an ipad anyway.
Now gesture control on VR/AR setups? Sure, that feels like a new human/computer interaction system that makes sense. Jabbing at my laptop screen with one hand on my keyboard, not so much.
Itās not. I had a thinkpad with a touchscreen and while I used the touchscreen seldomly, it was useful in some applications. Notably to easily develop touch based applications.
I have a M1 MacBook Pro with the touch bar since. Itās crap. I remember the keynote where they introduced it and a DJ mixed music using it. It was ridiculous that it got approved.
My late-2021 M1 Pro is working fine but I think one of the fans is broken. When loaded it starts beeping every 7 seconds and won't stop until I reboot. It might be just dust but I'm reluctant to open it up. Maybe I should and if I break it I have a better reason to upgrade lol.
I read it the same way. I should've gotten way more RAM back when I got my M1 and RAM was still cheap although this was of course before the LLM boom so there was no way to really know.
I maxed my M1 out when I bought it because I was frustrated with the 16GB max in the previous machines. I use my machine for all sorts of things and some days you just don't feel like exiting apps to make space for new ones.
I still don't have a strong urge to upgrade. I could probably get by on 32GB (like my work-issued machine is) but 64GB is the right amount of headroom for me.
Ditto. Though, I fixed my M1. I have an M4 max for work; the nano screen is a win. The perf is better, but it's really marginal unless actually doing stuff with the GPU, then it's super slow compared to a decent GPU anyway (i.e. h100, gb etc)
I have an M1 Max with 64 GB and an M4 Max with 128 GB and the latter feels noticeably snappier than the former. The latest MacOS release fucked up the M1ās performance. Wish I could downgrade easily. I want off that ride.
I have the M3 Pro (32gb) and an M4 Pro 16" (48gb), and the latter is sufficiently snappier to make me happy I waited to upgrade from my horrible Intel 13" i5 with 16gb. The M1 Pro I used for work a few years ago was great too. I'm not on Tahoe on either computer, thank god.
I have an M1 Max Macbook Pro, and having used many employer's newer variants of M-series macbook's since then, I'm still very satisfied with my M1 Max but
the air series is really good, and very light
my M1 is now noticeably heavy and I don't think upgrading to another Macbook Pro is the move the resell value of the M1 did not hold, specifically the bumped up storage models. There doesn't seem to be a market for 8TB of space specifically, but the base 1 - 2TB holds its value because the baseline of the MBP holds its value
M5 Max looks tempting if there is a very compelling tradein, but the M1 Max is pretty old so I don't have real hope of that, but I'll look. For AI Inference the difference doesn't seem good enough yet and necessary enough. I'll still need to use the cloud or aspire to have a specialized machine with more RAM or circuitry on my network.
I typed āRAMā to search for it and boy they hammer home how lucky I am to be getting 1TB SSD standard, but no mention of RAM anywhere on this page. Anyway, the MacBook Pro starts with 16GB of RAM. Itās $400 to go from 16GB to 32GB.
Interestingly, 36-128GB models are showing as ācurrently unavailableā on the store page, and you canāt even place an order for them right now? But for anyone curious, itās quoting $5099 for the 128GB RAM 14ā MacBook Pro model.
No change from the previous models then, 16GB->32GB was already $400. They're cutting into their previously enormous margins to keep the prices stable, rather than hiking the prices to maintain their margins.
They bought the fab time for that RAM 2-3 years ago. Apple is renowned for their foresight and preparation. We'll eventually see price increases from Apple's RAM upgrade, but we're not there yet.
Commodity futures made sense to me at FedEx- they would pay money with a supplier for the option to buy gas/oil at X price at Y date in the future. It costs more than just agreeing to pay for it at that price in the future, but if deliveries went way down (or prices) it'd be less costly to "back out".
I wonder if there's a fab time secondary market where Wall Street types are making millions off speculating fab time.
This is not exactly correct. If you have an M5 Pro chip instead of m5 Chip - I just built a 16inch, M5 Pro chip, it is $400 to go from 24 -> 48gb. An additional $200 ($600 over base) to go to 64gb. So the memory prices change based on chip. M5 Max Chip starts with 48gb of memory.
M5 Max starts at 36GB memory at $3599. M4 Max started at the same memory at $3199.
They have doubled the default storage from 1TB to 2TB, that's a $400 increase I'm paying even if I don't want the extra 1TB.
They advertise local LLMs which will be servery limited with 16GD of RAM. Plus the GPU could in theory provide decent gaming performance but again might suffer from the RAM limit.
Most people can totally live with 16gigs but it is kind of a waste for the horsepower. They know what they are doing. Apple is a master in upselling.
Though personally I don't mid the aggressive upsellign as long as the quality is there. Problem is, the hardware quality is great but the software side is severely lacking and getting worse.
RAM is still RAM, the switch from crusty HDDs to fast NVMe SSDs may have helped to smooth things over when you spill into swap but it's not going to do miracles.
I know RAM is scarce and everything, but doubling down on LLM local acceleration with all of that dedicated silicon while at the same time sticking with Apple's traditional lack of RAM availability makes for a very weird product proposition to me.
> M5 Pro supports up to 64GB of unified memory with up to 307GB/s of memory bandwidth, while M5 Max supports up to 128GB of unified memory with up to 614GB/s of memory bandwidth
Ah yeah youāre right, thanks. I tried to at least make my post useful and pull up prices for the different tiers. Overall, those prices are surprisingly competitive now compared to the rest of the laptop market!
Fair chance that Apple has price/purchase agreements already in place. Consumers are left to fight over the excess capacity after megabuyers get their orders filled.
> Interesting that this hasn't budged since the memory shortages appeared.
Apple has had enough war chests with the ability of buying the entirety of TSMC's new capacity years in advance in the past.
If I were to guess, Apple locked in their entire BOM and production capacity two years ago. That's something even the large players cannot replicate because they run cash-lean and have too many different SKUs, and the small players (Framework, System76, even Steam) are entirely left to the forces of the markets.
The price hasn't changed between the M4 and M5. I honestly don't know how they did it. But I had a standing order for a maxed-out M4 (128 GB RAM, 2 TB drive) and the price is the same as the M5 so I cancelled my M4 order and will pre-order the M5 MAX instead.
that is ... not at all how that works. RAM is a separate chip, that is placed on top of the substrate that holds the main dies. It is bought from normal ram manufacturers like micron. it is not "embedded in the chip" by any possible meanings of those words.
My wifeās 8GB MacBook Air crashed yesterday with Firefox and Find My open and nothing else because of running out of RAM, so, sort of, but theyāre not magic. (Find My was using 3GB of memory!)
If you mean it showed the out of memory dialog, that wouldn't be caused by an app using 3GB. The dialog shows up at ~48GB swap space used on an 8GB Mac, or when you're out of disk space and can't write a swap file.
Itās a losing battle me trying to tell my wife to close her Firefox tabs, haha, but yes, Firefox does use a lot of ram when you have 500 tabs. Maybe Iāll get her a 64GB MacBook Pro for the premium web browsing experience she so desires!
I do it myself and I'm sure a lot of people on HN do too. But I've tried to embrace the "zen" of closing all tabs lately and it's been nice. If I really want to find something later I can search my history or, like you said, just bookmark it.
More to do with the faster storage allowing you to swap without noticing it as much. There was this whole trend when m1 first came out of people saying it didn't matter if you got the lowest spec because the ssd was so fast it made up for the lack of ram... totally ignoring that swapping like that was destroying their drives really fast.
You mean bumped $100. M4 MacBook Pro and M5 MacBook Pro started at $1599 with 512GB SSD.
Now it starts at $1699, a $100 bump but comes with a 1TB SSD. Previously it would have cost $1799 for the 1T SSD, so it's a $100 bump on base price but you are also getting 1TB SSD for $100 less than before.
To me, this is kind of like Telecom providers giving you bandwidth headroom that realistically should have been there for a long time, but removing the option to get a cheaper plan whether you'd otherwise pay for the upgrade or not.
Like for my last upgrade, I bit the bullet and upgraded to 1TB for the first time ever instead of base storage at Apple's absurd prices, so it's good, but if I'd not have been willing to spend money on that at all, they lifted the floor.
My cell phone plan has been increasing every year by small amounts, but my usage pattern hasn't changed, and meanwhile they've restricted HD streaming using Deep Packet Inspection or whatever, so I theoretically have a 100GB full speed cap but can't practically use more than 20gb anyway, so they're pricing the bandwidth into the contract but I can't save money by getting a lower ceiling
To be fair, ever since the advent of high power USB-C PD that really, really is not needed any more, way too many power bricks are effectively e-waste.
People already have USB-C power bricks and docks everywhere and unlike pre-USB-C generations, you can use them not just across different generations of hardware, but across vendors as well.
> unless they are upgrading from another USB-C laptop.
Which MacBooks have been for almost a decade - the 2016 MBP with Touch Bar was the first that went fully USB-C PD. Anyone who has had a MacBook in that time frame will have had at least one high power USB-C PD wall wart.
The Windows world, as usual, has been different, but even there, I'm not aware of any mainstream model being sold in the last two years without even a single PD capable port.
EU doesn't forbid including. The new law requires there to be an option without the adapter. If the manufacturer chooses so they can have an option with and without the adapter.
Except that it's literally not true and people are repeating it for some stupid reason, I assume you just never actually looked it up - laptops are specifically excluded from that regulation, and in fact Apple does bundle a power adapter with their laptops, just not on the cheapest models.
> in fact Apple does bundle a power adapter with their laptops, just not on the cheapest models.
Here in the UK, they no longer include the power adapter even with the top models. I just specced out a fully-loaded M5 Max Macbook Pro, 128GB RAM, 8TB storage on the Apple Store, and it doesn't include a power adapter by default.
The 140W power adapter can be added as an option to the MacBook Pro for an additional Ā£99 + VAT, or purchased separately. If you purchase separately you can of course choose a lower-power adapter for a lower price.
Now that a power adapter isn't included and you have to pay for it separately, it might make more sense to get one of the good brands of GaN power adapters instead, because they are smaller than the Apple ones for the same power, and have more ports.
I feel like Apple pulled an Instant Pot with the M1 MacBook Pro. I still haven't had a single situation where I felt like spending more money would improve my experience. The battery is wearing out a bit, but it started out life with so much runtime that losing a few hours doesn't seem to matter.
> The battery is wearing out a bit, but it started out life with so much runtime that losing a few hours doesn't seem to matter.
this is my exact opposite experience. my M3 Max from 2 years ago now has <2hrs battery life at best. wondering if any experts here can help me figure out what is going on? what should i be expecting?
As others have said, keep the battery in the 80%-30% range. Use the `batt` CLI tool to hard limit your max charge to 80%. Sadly, if you're already down to <2hrs, this might not make sense for you. Also prevent it being exposed to very hot or cold temps (even when not in use)
I type this from an M3 Max 2023 MBP that still has 98% battery health. But admittedly it's only gone through 102 charge cycles in ~2 years.
(use `pmset -g rawbatt` to get cycle count or `system_profiler SPPowerDataType | grep -A3 'Health'` to get health and cycles)
What is your maximum capacity in Settings > Battery Health? What processes are running with significant CPU? What's the typical temperature of the laptop according to a stats app? (Temperature is a good proxy for general energy use.)
I'm typing this on an M3 Max; its max battery capacity is 88%. I've got some things running (laptop average temp is 50-55C, fans off), screen is half brightness, and it's projected to go from 90% to 0% in five hours. I don't usually baby it enough to test this, but 8-10 hours should be achievable.
My M3 Max can burn through battery much faster than my M1 Max ever could.
And some apps are really inefficient. New Codex app drains my battery. If you are using Codex I recommend minimizing it, since itās the UI that uses most power.
A couple weeks ago I was working remote and didn't bring a power adapter, and I realized a couple hours in that my battery was getting kind of low. I clicked on the battery icon and got a list of what was using a lot of power: 1 was an hour long video chat using Google Meet, the other was Claude desktop (which I hadn't used at all that morning).
What in the world is an idle Claude Desktop doing that uses so much power?
Charge habits with batteries make a huge difference. If your use pattern is that once per day, you take the device from 100% to 10%, you put a lot more wear on the battery than if it kind of hovers in the 30%-80% range for example, or if it just hangs out nearish top-of-charge all day when you're at your desk.
Hot take: people should get used to, and expect to, replace device batteries 1 or 2 times during the device lifetime. They're the main limiting factor on portable device longevity, and engineers make all kinds of design tradeoffs just to make that 1 battery that the device ships with last long enough to not annoy users. If we could get people used to taking their device in for a battery once every couple of years, we could dramatically reduce device waste, and also unlock functionality that's hidden behind battery-preserving mechanisms.
BatFi is a macOS application which will prevent your battery from charging to over 80% by default. macOS does have a version of this built-in but itās āintelligent chargingā I donāt really trust, and Iād rather just have a hard 80% limit except when I override that.
I set Claude loose on my computer and said āwhy is my battery life so bad?ā and it found an always-running audio subsystem kernel extension (Parrot) which didnāt need to be there and was preventing the CPU from going into low-power states. My battery life got noticeably better when I deleted it.
Iām not even sure how it got installed, possibly when I installed Zoom for an interview once but I donāt know. Point is, at least in one case, AI can help track down battery hogs.
M1 pro MacBook pro here as well. Just today I was thinking I have no need to upgrade until M7 and by then maybe even MacBook Air would do. Especially since I will have my home server (dgx spark) available for anything serious anyway. So excited for the Mac studio configs though. M5 ultra 1TB would be a huge leap for serious home server builders.
You can very easily replace the battery yourself for less than $100 USD too if it ever becomes enough of an issue that you feel you actually need to do something about it. My M1 Max is at about 88% battery health, but it still gets 4X-6X longer on battery (At full performance too boot) compared to my old PoS Razer laptop, so I likely won't be replacing my battery any time soon.
The hardware looks amazing! Too bad they will ship with Tahoe installed. Iām not upgrading until I see in which direction the next Mac OS release goes
This. I have been a big (and loud) fan of M-series hardware from the beginning, but if Apple is going to keep making their software worse, I will find myself lingering on older generations that run Asahi Linux or going back to a traditional x86_64 laptop instead of buying into new generations.
Same here. I know some people are unhappy with some of the UX tweaks but honestly I don't notice much of it. The whole liquid glass thing is a bit gimmicky. Other than that, I don't see much difference. The rounded corners on windows are a bit silly. But I don't spend a lot of time fiddling with windows. Most of my windows are maximized (not full screen). I'm sure there are other issues people dislike that I just haven't noticed.
I use my laptop for development. I don't actually use most of the built in applications. My browser is Firefox, I use codex, vs code, intellij, iterm2, etc. Most of that works just fine just as it did on previous versions of the OS. I actually on purpose keep my tool chains portable as I like to have the option to switch back to Linux when I want to. I've done that a few times. I come back for the hardware, not the OS.
In my experience, if you don't like Apple's OS changes that is unfortunate but they don't seem to generally respond to a lot of the criticism. Your choices are to get further and further out of date, switch to something else, or just swallow your pride. Been there done that. Windows is a "Hell No" for me at this point. I'll take the UX, with all the pastel colors that came and went and all the other crap that got unleashed on macs over the last ten years. Definitely a case of the grass not being greener on Windows. Even with the tele tubby default desktop in XP back in the day.
I can deal with Linux (and use that on and off on one of my laptops). However, that just doesn't run that well on mac hardware. And any other hardware seems like a big downgrade to me. Both Windows and Linux are arguably a lot worse in terms of UX (or lack thereof). Linux you can tweak. And you kind of have to. But it just never adds up to consistent and delightful. Windows, well, at this point liking that is probably a form of Stockholm Syndrome. If that doesn't bother you, good for you.
So, Mac OS it is for me as everything else is worse. I've in the past deferred updates to new versions of Mac OS as well. Generally you can do that for a while but eventually it becomes annoying when things like homebrew and other development toys start assuming you run something more recent. And of course for security reasons you might just not drag your feet too long. Just my personal, pragmatic take.
Closing Tabs in Safari till takes more than a second though. And if you hold Cmd-W to close all of them it just completely locks up and crashes. Still not fixed since the release of Safari 26.
I will say that 26.4 beta 2 was the first time I've regretting using betas since Sonoma beta 2. The Sonoma beta ruined the firmware on my machine and Apple had to replace the logic board; the latest Tahoe beta broke all networking on my machine and I had to erase the installation to fix everything. I've since dropped off the beta train for the time being.
I already left the beta train on my iPhone because I had too many issues getting my grocery apps to allow me to place orders without going to my laptop and doing it in a web browser.
I'm on an M4 Pro MacBook-- basically the fastest computer you could buy from Apple before today-- and opening/closing the tab sidebar in Safari on Tahoe takes multiple seconds, even if I have only 4-6 tabs open, and seems to drop to 5 FPS. It's comically bad.
It's so bad I switched back to Chrome. I had thought Chrome had a major battery life penalty compared to Safari on Macs, but I checked more up-to-date info and apparently that's outdated.
The next macOS will be touch screen centric with elements getting bigger when you're close to touching them, rumors say. That being said, I run Tahoe and it works perfectly fine to me, I am not sure what issues people have with it. Sure, some corner radii aren't exactly the same but I honestly couldn't give less of a shit as long as it runs the programs I need.
Safari routinely using 20+ Gb of memory with a handful of tabs open. Safari tabs refusing to close. Unresponsive System Settings window. Random application freezes and crashes, Apple Music not playing music. This is on a 32Gb M1 Max. My M1 Air on Sequoia doesn't experience any of these issues, even if it has half the unified memory.
Not necessarily, because I never used Apple apps, it's not like I'm avoiding them now because they're ostensibly buggy (as others don't seem to have the same issues in this thread).
I moved away from mac because of the OS and couldn't be happier. The hardware may be great but non-Apple hardware is fine too, and Linux is significantly better experience than MacOS these days.
On M4 Max 128GB we're seeing ~100 tok/s generation on a 30B parameter model in our from scratch inference engine. Very curious what the "4x faster LLM prompt processing" translates to in practice. Smallish, local 30B-70B inference is genuinely usable territory for real dev workflows, not just demos. Will require staying plugged in though.
The memory bandwith on M4 Max is 546 GB/s, M5 Max is 614GB/s, so not a huge jump.
The new tensor cores, sorry, "Neural Accelerator" only really help with prompt preprocessing aka prefill, and not with token generation. Token generation is memory bound.
Hopefully the Ultra version (if it exists) has a bigger jump in memory bandwidth and maximum RAM.
The thing about context/KV cache is that you can swap it out efficiently, which you can't with the activations because they're rewritten for every token. It will slow down as context grows (decode is often compute-limited when context is large) but it will run.
I strongly agree. People see local "GPT-4 level" responses, and get excited, which I totally get. But how quickly is the fall-off as the context size grows? Because if it cannot hold and reference a single source-code file in its context, the efficiency will absolutely crater.
That's actually the biggest growth area in LLMs, it is no longer about smart, it is about context windows (usable ones, note spec-sheet hypotheticals). Smart enough is mostly solved, combating larger problems is slowly improving with every major release (but there is no ceiling).
That should be covered by the harness rather than the LLM itself, no? Compaction and summarization should be able to allow the LLM to still run smoothly even on large contexts.
4x faster is about token prefill, i.e. the time to first token. It should be on par with DGX Spark there while being slightly faster than M4 for token generation. I.e. when you have long context, you don't need to wait 15 minutes, only 4 minutes.
The marketing subterfugue might be about this exactly, technically prompt processing means the prefill phase of inference. So prompt goes in 4x as fast but generates tokens slower.
This seems even likely as the memory bandwidth hasn't increased enough for those kinds of speedups, and I guess prefill is more likely to be compute-bound (vs mem bw bound).
So prompt goes in 4x as fast but generates tokens slower.
I'd take that tradeoff. On my M3 Ultra, the inference is surprisingly fast, but the prompt processing speed makes it painful except as a fallback or experimentation, especially with agentic coding tools.
I find time to first token more important then tok/s generally as these models wait an ungodly amount of time before streaming results. It looks like the claims are true based on M5: https://www.macstories.net/stories/ipad-pro-m5-neural-benchm... so this might work great.
I run gpt-oss 120b model on ollama (the model is about 65 GB on disk) with 128k context size (the model is super optimized and only uses 4.8 GB of additional RAM for KV cache at this context size) on M4 Max 128 GB RAM Mac Studio and I get 65 tokens/s.
Have you tried the dense(27B,9B) Qwen3.5 models? Or any diffusion models (Flux Klein, Zimage)? I'm trying to gauge how much of a perf boost I'd get upgrading from an m3 pro.
I don't think the "new" Performance cores are just "renamed" "E" / "Efficiency" cores; Apple has retroactively renamed the baseline M5 nomenclature to say it has "10-core CPU with 4 super cores and 6 efficiency cores"; so they're clearly keeping the "efficiency cores" nomenclature around.
I think this is a new design, with Apple having three tiers of cores now, similar to what Qualcomm has been doing for a while.
I think how it breaks down is:
- "Super" are the old "P" cores, and the top tier cores now
- "Performance" cores are a new tier and seen for the first time here, slotting between "old" P and E in performance
- "Efficiency" / "E" are still going to be around; but maybe not in desktop/Pro/Max anymore.
Interesting. This is clearly a big CPU change if so. I wonder why no E cores. Iām sure E cores would be more efficient at OS tasks than the new performance cores.
For example, 6 super, 8 performance, and 4 efficiency.
Whoah, both the Pro and Max CPUs feature 18 cores. This hasn't happened since M1 Pro/Max. This is a surprise.
Replying to my own post. In hindsight, this shouldn't be any surprise because these chips are now chiplets. Apple is connecting a CPU die with a GPU die. This means they're designing just one CPU die rather than two. An Ultra would just be two of these CPU dies.
I was looking into this. The M5 performance cores can be scaled down to match efficiency cores in performance and power usage.
I believe they lower the clock speed, limit how much work is done in parallel on each core, and limit how aggressive the speculative execution is so less work is wasted.
> The industry-leading super core was first introduced as performance cores in M5, which also adopts the super core name for all M5-based products
But new "performance" is claimed to be new design (= not just overclocked efficiency core from M5?):
> M5 Pro and M5 Max also introduce an all-new performance core that is optimized to deliver greater power-efficient, multithreaded performance for pro workloads.
1.35x speed up in single core versus M3 Max. Insane. Everyone else has failed to bump single core performance in years. Where are these single core gains coming from?
The most interesting change for the M5 Pro and Max is Apple moving to a bonded chiplet strategy from a single monolithic die.
> The tech giant says the chips are engineered around its new Fusion Architecture, an advanced design that merges two dies into a single, high-performance system on a chip (SoC), which includes a powerful CPU, scalable GPU, Media Engine, unified memory controller, Neural Engine, and Thunderbolt 5 capabilities.
They also replaced the efficiency cores on the CPU chiplet with a new higher performance design.
> The CPU now features six āsuper cores,ā which is Appleās term for its highest-performance cores, alongside 12 all-new performance cores. Collectively, the CPU boosts performance by up to 30% for pro workloads.
If thereās anything this past three years has taught me, itās that modern cpus can performantly do every task except for streaming text over the internet.
I had to upgrade the CPU in a 10-year old machine (from i5 to i7) to have decently -working javascript on websites. Every other piece of software worked fine, though.
I've found current-generation Macs so capable that I've switched to using a Macbook Air. Would strongly recommend - it's still a powerful machine and it's significantly lighter and cheaper.
I have a powerful older Mac that doesnāt really āchokeā on anything, but I could always use more speed.
The high memory Macs have been great for being able to run LLMs, but the prompt processing has always been on the slow side. The new AI acceleration in these should help with that.
There are also workloads like compiling code where Iāll take all the extra speed I can get. Every little bit of reduced cycle time helps me finish earlier in the day.
And then thereās gaming. I donāt game much, but the M1 and M2 era Apple Silicon feels sluggish relative to what I have on the nVidia side.
AI video generation can fairly easily choke anything that's not NVIDIA's flagship model. Even the latest local image gen models are so large that they can be frustratingly slow with non-optimal hardware even if they fit in the VRAM. IIRC when I had an M2, it was about 4x slower at running the venerable Stable Diffusion (and SDXL) than my meager RTX 3060.
Sounds pretty beefy. What kind of local LLM is that thing capable of running? Does it open up real alternatives to cloud providers like OpenAI and Claude, or are the local models this hardware is capable of running still pretty far behind?
You might have confused Hacker News with your e-mail inbox again. This is an Apple press release, directed to everybody in the world who might be interested in a new computer or their first computer.
Whatās with the attitude? My machine is aging like a fine wine, Iām acknowledging how resilient their custom silicon is despite the world demanding more and more compute.
It was a joke, should have put a smiley face. But every thread on a new Apple product here on HN have the same "why should I upgrade" comment, forgetting that there are people who might have very old devices they want to upgrade, or they might want to switch from Windows/Android to Apple.
Even if a new device is a small upgrade from last year's model, it can be a giant upgrade for other people.
Are you one of the folks thinking of upgrading? If so, from what generation? What makes you excited? Isn't this a more interesting way to have the conversation?
Got it. I guess it feels unfair to gaslight people who are celebrating not needing upgrades, anecdotally sharing their experiences - because some people just need a new computer for xyz reason in time.
Honest question. Is it possible to install an earlier version of macOS on these machines?
Liquid glass looks so.. unprofessional to my eyes. And I hear it's also unstable.
Yes. This page has several ways to get older macOS versions: https://support.apple.com/en-us/102662, but the earliest macOS version you can use on Apple Silicon is macOS 11.
If you move your home directory to a different disk partition, you can even share it between two different macOS versions!
these Macs can't go below Tahoe. People on Mac Rumours were complaining about M5 MacBooks unable to install Sequoia, so it's safe to assume Pro/Max chips will be the same.
"The new MacBook Pro gets up to 24 hours of battery life, giving Intel-based upgraders up to 13 additional hours"
I have a Intel-based 2019 Macbook Pro still and I have NEVER in its lifetime gotten even half of what they are claiming here. These days if I run it from battery I might get 90 mins.
That said I had a maxed out Macbook Pro M4 Max on order but just cancelled it right now and will get this new M5 Max one for basically the same price. Once I saw that they didn't up the price of memory (I don't know how it doesn't affect them) I canceled my order.
I had intel MacBook Pro. It is a NIGHT and DAY difference. I wish I didnāt get the 16gb of memory though. It is ok, but running 5-10 cursor ai agents at the same time does start to choke the memory.
Battery is absolutely amazing! And the best part - it stays cold!! No more irritated from heat fingers when using touchpad.
They are at least nice for comparing it with the max of the Intel. That should really say gives them up to 22 additional hours given the wear on their batteries lol
One thing I haven't seen mentioned in this thread is M5 Pro now supporting 64GB ram . I believe prior gens you had to go Max to get 64. m5 Pro 64GB is $3000 meanwhile to upgrade ram on the max you need the 40 gpu core variant with 64GB is $4300. $1300 dollar mark up for twice the gpu compute and 50% higher mem bandwidth isn't great value imo.
Anyone who cares about value isnāt getting a non-base model Mac. They are buying the silver shiny thing or their company is paying.
For example, grab yourself an Omen Transcend 14, spec it to 64GB RAM and the RTX 5070. Youāre under $2000 and getting better graphics performance for anything that isnāt AI, and youāve got an upgradable 1TB SSD and removable WiFi card.
Youāre also getting an OLED screen which most people would prefer.
This model in particular Iāve chosen because itās just as quiet as the M4 MacBook Pro models within 3dB during high intensity usage and gets very similar battery life, actually better battery life than the M4 Pro/Max models for light tasks.
Interesting that they're showing VFX/CG software (Autodesk MAYA and Foundry Nuke) so prominently - obviously people using "Pro" machines are the target audience for this, but both of those apps (any many others in the industry) use Qt for the interface, rather than being totally platform-native.
Contrary to HN popular belief, there are neither incentives nor benefits to building native ui apps, for neither consumer nor professional apps. The exception is apps that only make sense on a single platform, such as window management and other deep integration. On iOS/macos you have a segment of indie/smaller apps that capture a niche market of powerusers for things like productivity apps. But the point is it makes no sense for anything from Slack, VSCode, Maya, DaVinci Resolve, and so on, to build native UIs. Even if they wanted to build and maintained 3 versions, advanced features arenāt always available in these frameworks. In the case of Windows, even MS has given up on their own tech, and have opted to launch webview based apps. Apple is slightly more principled.
Qt delegates to native UI in a lot of cases. I think a lot of people who rail against native UI fail to delineate between native UI and first party frameworks. Using third party frameworks, even cross platform ones, does not mean you lose out on native UI elements.
Strong disagree. I think Microsoftās decision to wrap web apps for the desktop is one of the stupidest they have ever made. It provides poor user experience, uses more battery power and needs more memory and CPU to be performant and creates inconsistencies and wierd errors compared to native apps.
The increased adoption of webviews has resulted in a death by a thousand cuts effect on Windows 11 performance. The speed bump that comes from going from an up to date Windows 11 install to a up to date Windows 10 install on the same machine is stunningā¦ W10 is much more snappy in every regard despite being nearly identical functionally speaking.
I wonāt try to claim that Electron and friends have no place is software development but we absolutely should be pushing back harder against stuffing it everywhere it possibly can be.
Every modern desktop uses webviews in some capacity. macOS renders many apps with webviews, GNOME uses gjs to script half the desktop. The time to push back was 10-20 years ago, it's too late to revert now.
Theyāre still fairly uncommon in macOS, mostly being used in places related to cloud service settings. SwiftUI and Catalyst (iOS bridge) are both much more common than webviews, and AppKit remains ubiquitous.
Meanwhile on Windows major features like the Start menu are written in React.
Worth noting that WebKit webviews also tend to be more lightweight than their Chromium brethren.
$200 price bump across the board. The cheapest 16" is now $2699 and 14" Pro $2199. I think it's a fair price considering M2Pro 14" was $1999 (though it was discounted) only had 512GB and 16GB RAM.
It's not $200 across the board. M4 MacBook Pro and M5 MacBook Pro started at $1599 with 512GB SSD.
Now it starts at $1699, a $100 bump but comes with a 1TB SSD. Previously it would have cost $1799 for the 1T SSD, so it's a $100 bump on base price but you are also getting 1TB SDD for $100 less than before.
To clarify, I meant, model with Pro chip, not just Macbook Pro name.
For example, up until MacBookPro M2, MacBookPro M2 came with M2 Pro chip.
However, starting with M3, Apple lowered the MacBookPro MSRP to $1599, but its base configuration was downgraded to M3 chip from M3 Pro. To get the M3 Pro, you had to pay $1999. There's substantial performance between the two.
Same with M4. To get the M4 Pro chip, you had to pay $1999.
Now to get M5 Pro chip, it's $2199. Still a good value, but just saying it's a deviation from the trend.
I checked the fine print on the product website: by āup to 4x faster LLM prompt processing,ā theyāre specifically referring to time to first token. So itās not about token generation rate (tokens per second).
Yes. This is known. They added neural accelerators, aka Tensor core equivalent, in the GPU. This will make prompt processing competitive vs similar class GPUs.
I was considering it but got cold feet when I've been told that you could damage it when cleaning it. When I open/close my laptop I leave a ton of finger prints. I'm not too good with delicate hardware stuff.
MacBook Pro with M5 Pro now comes standard with 1TB of storage, while MacBook Pro with M5 Max now comes standard with 2TB. And the 14-inch MacBook Pro with M5 now comes standard with 1TB of storage.
> M5 Pro supports up to 64GB of unified memory with up to 307GB/s of memory bandwidth, while M5 Max supports up to 128GB of unified memory with up to 614GB/s of memory bandwidth.
This is the important statement. 614GB/s is quite decent, however a NVIDIA RTX 5090 already offers 1,792 GB/s (roughly 3x) of memory bandwidth, for comparison.
You're right a $3600 graphics card is worse than a $2600 laptop; but from my perspectives they're very different products. Not least of all because even at $3600 for a RTX 5090 you still have the whole rest of the computer left to purchase.
The RTX 5090 only has 32gb of VRAM. So the tradeoff is NVIDIA is for blazing speed in a tiny memory pool, but Apple Silicon has a larger memory pool at moderate speed.
That's a fun comparison, but can you run those 2 m5 pros in parallel to accomplish 2x the work? Otherwise, you just told me you can buy 2 toyota corollas for the price of 1 F-150 while trying to convince me you can haul your boat behind both corollas at the same time.
All I'm saying is that the comparison doesn't make sense. The 5090 is faster on a small subset of tasks if attached to a computer which ends up being 3x the price of a m5 machine that fit the same model or the same price as a machine that fits models 5x bigger
So you're saying that buying 2 Corollas for the cost of 1 Ferrari engine would be better? Even though the Ferrari engine is much more powerful, it's useless without the rest of the car.
Was hoping to see Apple break the 128GB barrier in a laptop that they previously set, though 128GB is still pretty sweet for local LLM inference on consumer hardware. My 128GB M3 Max is still shredding tokens pretty well (with that annoying slow initial prompt processing), so no major complaints there. I guess the question is, given access to the same amount of RAM, does the M5 really do an order-of-magnitude better than 128GB on a M3 or M4?
I don't see it mentioned much, but the most exciting thing to me is that they're shipping their own WiFi chip in it, which leads me to be hopeful that they'll eventually get around to shipping a cell modem so I don't have to tether to my phone constantly. Still no new colours unfortunately. I think those are the two things that would/will be exciting in the future. Give me a green 5g+ capable MBP and I'll be happy. I'm so deeply bored of the drab grey and darker grey versions; we can have tattoos at work now, give me a different colour laptop for christ's sake
I donāt know if theyāll ever do that. Colors add another dimension, so you either need to have more stock on hand or do more custom models. Right now, the profit margins on all upgrades is huge.
Phones have less configurability, they sell more, and colors seem more important.
Because the M1 was too good, a qualitative leap over previous Macs and really every other laptop and even some desktops back in 2020. Now, Apple Silicon is just iterative.
Me either. I guess it's just fatigue, at least for me. I also don't really get that excited by new LLM releases either. Not to say the tech isn't impressive, but I guess all the hype has me inured.
For me going way back, it was exciting when I had to save a bit (but not too much!) for a new 512 DIMM, and when I opened the box and smelled the chip smell, put it in always worried I was going to fuck it up, and then computer literally felt faster that next boot...that was pretty fun!! Now it's like oh great $5k for a slab of stone that can do pretty much anything, neat. I still think computers are cool, just not particularly exciting.
Because it's the same shit every year for the past 5 years with the M line. 2010 to 2015 was a major improvement, 2015 to 2020 was a major improvement, now they pretty much solved the computer/laptop problem for 99% of people. I'm on a 16gb m1 air, I see absolutely no reason to update.
TL;DW: 2010s intel mac era laptops have seen at very best 35% single core CPU performance over in 5 years time! This happens almost every year now with M line macs.
Rant:
Retina macs were great and had great form factor over unibody macs. Touch-bar macs in the mid 2010s was IMHO a disaster. Terrible keyboard, poorer thermal capacity, missing essential ports, adapters galore.
But when it comes to performance - early 2010s macbooks with dedicated gpus had serious overheating issues.
Retina macbooks were decent, both form factor and performance.
Touch-bar macs were totally abysmal, all performance gains over previous generations was all through pumping more heat. CPUs constantly pegged at 90C+, cannot have laptop on your lap, Apple planning and delaying release schedules around intel fumbling their tik/tok cycles (as far as i remember some macs did not get any improvements for 2 years+ if not way more). Upgrades sometimes were total jokes, because of thermal throttling there was no point to put more hardware than it could work with. From reviews buying higher level cpu sometimes didnāt give noticeable real life gains because, again, thermal throttling kicking in instantly. 2020 intel macbook pro has fans spinning almost all the time. Having a remote call - your battery is dead in 2h max (essentially 1% per 1min).
M1 mac gave insane perceived performance boost - no noticeable throttling. Macbook airs are fully passively cooled, never heard M Macbook pro with fans screeching.
Also real full work day battery doing real work without power adapter at full performance. Cool to touch most of the time.
I made homework for a job in 2020 on a 2013 personal macbook. Apart from memory footprint - I could not feel noticeable difference on development experience. Editing images was frustrating on both. With M macs - its silent, smooth fast.
Number of parallel cores matching best intel cpus on base models, GPU blowing any mobile gpu in price range out of the water with thermal capacity to peg it 100% no problem. Unified memory for those GPUs to do what you could only imagined doing on GPUs that cost 3 times more than the macbook.
Itās a such excellent architecture that yeah - itās āboringā you can nitpick about M69 Ultra Pro Max performance, but take a base MBP of any M line and it blows almost any laptop out of the water, even to this day.
Hot take - Local LLM computing will move to stationary, always on devices (Mac mini & studio). Developers and users will move to lighter, portable devices to interface with their long running agent workers (MacBook Airs & iPads).
So is this a minimal upgrade before the M6 Macbook Pros w/ OLED & a redesign later this year?
It doesn't even look like they added cellular as an option with their own C1X chip (getting around the licensing / cost issues since it's their own chip now).
For those who don't already know, you can get a lot of PC gaming performance out of these machines using Sikarugir. You can install all of Steam via winetricks and go from there, or launch DRM-free games directly.
Can someone comment on the new dual die thing theyāre promoting for how they make the M5 Pro and M5 Max chips?
How is that different from the silicon interposer they were using before?
The big change is the two dies donāt have to fabbed next to each other in a single wafer, which is fantastic for costs and yields. But would this affect the interconnect speed somehow?
How would the two be wired together?
Could this mean the Ultra comes back in M6 since it would be easier to fab?
the new dual die thing theyāre promoting for how they make the M5 Pro and M5 Max chips?
It's chiplets just like GB10, Strix Halo, etc. One die has the CPU and the other die has the GPU.
How is that different from the silicon [bridge] they were using before?
It's probably similar.
the two dies donāt have to fabbed next to each other
They never were; this is a widespread misunderstanding.
But would this affect the interconnect speed somehow?
Apple never documented the internal interconnect for the M4 Pro/Max and now they don't document it for the M5 Pro/Max so we don't know. It's probably better to read reviews and avoid theorycrafting and backseat driving.
They seem to market it as a technological advancement, which it is, but rather than being excited im actually worried about hidden latencies that could come with that approach.
Have you found any interesting info on that yet?
Never - data centers will always offer more power if you only care about raw inference speed. HOWEVER I think that we'll reach the 'good enough' bar super soon. In 2-3 years I expect apple macs to be able to run a model as 'good' as Claude 4.6 sonnet at 90% of the inference speed we're used to from a cloud API.
Yes, I'm sure by then there will be better models on offer via cloud providers, but idk if I'll even care. I'm not doing science / research or complex mathematical proofs, I just want a model good enough to vibe code personal projects for fun. So I think at that point I'll stop being a OpenAI / Anthropic customer.
I bought an M1 Max with 64G RAM a long time ago, and am perfectly happy with it. I thought about getting a refurbed M4 Max when the M5 Max comes out, and decided my next computer will be a Dell Rugged, just because I want a Rugged laptop for auto diag stuff, and I thought I could kill two birds with one stone and get something with an NVIDIA card for learning CUDA. I've been using the Rugged basically nonstop while the M1 Max gathers dust. I think I may be done with Apple laptops now, a rugged laptop running linux is so nice. I love the keyboard, I love the upgradability, the OS is snappy, and I can use so much nice software. I added a 4TB SSD and now have 7 auto diag virtual machines with volvo, VAG, BMW software, and keep the host linux to myself. I have not had so much fun with a computer in a very long time. Both battery bays are full and my mac mini takes care of blue bubbles and is a home server for inventory management and backups. If for some reason I miss the Apple Experience, I can always RDP into the mini. Keeping a mini under the desk at home and a rugged laptop outside the home is my new sweet spot.
I just bought a M5 Macbook Pro 2 weeks ago. Thinking of returning it and getting a M5 Pro with the same configuration but only $200 more. How should I compare M5 vs M5 Pro?
I thought a Studio would be my local LLM machine 2026, but this is $2000+ for the 126gb option - not for me. I assume $6000 for that Studio machine but it looks now more like $8000.
I wonder how this compares to my M4 air with 10 GPU cores and 32 MB of RAM. My system can only run ~14B sized models at any reasonable speed. The accuracy of these sized models can be underwhelming. I am looking forward to a time when it would be nice to run models locally at a reasonable price, at a reasonable speed and with reasonable accuracy. I don't think we are there just yet.
I thought that new models were typically released in October. Have I misremembered or is this an unusual timing vs previous years? If so, I wonder why the earlier release?
I think at this point Apple will just release new versions of laptops whenever new CPU revisions and yields allow. M5 Pro wasn't ready for October so delayed until now.
My M3 Pro with 18gb of ram still feels like a beast. The only thing I can make it suffer with so far is generating meshes from 3D scanning, and even then I'm just patient. Apple is suffering from success with these older laptops, it's a tough sell to upgrade, even from the M1 Max folks.
I mean, they had to make them good because of the new cpu architecture, but since the emulation worked so well and overall adoption was really fast it now is a problem for them as a company. A really good problem to have though
It's hard to find any fault with the M1 models released 5 years ago. According to second-hand listings on Swappa, US$1200 would get you a capable M1 Max; the equivalent M5 Max is US$3600.
Considering these max out at 128GB of unified ram my guess is the hope of an M5 Ultra with 1TB of unified ram is unlikely to come true... Super disappointing.
Is the M5 Max the first laptop with significantly more memory bandwidth than the M1 Max? Looks like about a 20% jumpā¦ might finally be time to re-benchmark CFD workloads.
Checking Apple's store, I can't find a cheaper configuration than $5100 for the M5 + 128GiB version.
Here in Europe, including 21% VAT, that's ā¬6.124,00 ($7.094,35 equivalent).
Because of pricing strategies and such, the 128GiB version comes with a 2TiB SSD at minimum, and also requires the M5 Max (not Pro) at its highest configuration.
Not sure if this is new, but it should be noted that these laptops don't come with a charger any more.
70W USB-C Power Adapter (included with M5 Pro with 16-core GPU)
96W USB-C Power Adapter (included with M5 Pro with 20-core GPU, configurable with M5 Pro with 16-core GPU)
USB-C to MagSafe 3 Cable (2 m)
Devices should be offered without a charger. There's no law that states that that should be the default configuration. Nor that the charger should cost extra.
> M5 Pro supports up to 64GB of unified memory with up to 307GB/s of memory bandwidth, while M5 Max supports up to 128GB of unified memory with up to 614GB/s of memory bandwidth
Which roughly translates to 30B Q8 size LLM at 10t/s for the M5 Pro and 60B Q8 size LLM at 10t/s for the M5 Max
For reference, RTX 3090 24GB has a memory bandwidth of approx. 936.2 GB/s, DGX Spark 128GB features a unified memory bandwidth of up to 273 GB/s
Why would you want to do that? Do you like the hardware that much, and also that much more than just an M2 (soon M3) running Asahi?
Linux in a VM would work with the usual caveats. Periphery like the built-in webcam most likely won't work. Getting codecs and DRM to run will be pain and you'll be back to use macOS for that quickly (but that's just standard pain of ARM Linux).
$5000 laptop you have to pay to add a power adapterā¦ gratuitous penny pinching from Tim Cook's Apple.
It's one of those things, yes if I'm spending that much on a laptop I can afford to spend $80 on the adapter too, but does it feel good as a customer to do that or are you souring the experience of buying from you just to earn a few more dollars.
This is one thing I don't really blame Apple for, and I think everyone else will follow suit -- and not just because Apple is doing it.
The EU requires that users must be able to buy a device without a charger. It's a huge supply chain challenge to add two variants of every single SKU, one with a charger and one without. So the obvious solution is to sell the charger separately, since you need that regardless, and always sell the device without a charger. You avoid having two variants of everything that way.
Now, you could maybe argue that Apple should default to bundle a charger with your laptop, so that you'd have to uncheck a "bundle charger" checkbox on their website. But do you really care whether your laptop costs $2200 and you can buy a charger for $60 or your laptop costs $2260 and you can save $60 by removing the charger?
You can make an argument that doing it Apple's way hides a price increase. And yeah, that's probably fair. But it's not like Apple is afraid of non-hidden price increases either.
I have a huge tote box full of power bricks, most of them white Apple ones. I have a stack of 60-90W Apple USB-C ones too that I don't use cause they only have one port and are larger and worse than modern GaN units that can do 140W on one port while also pushing 30 or 60 on the others.
So, if you want one of mine, you can have one. On me. Because I'm fucking drowning in the things and appreciate not having to deal with another one.
I am very excited by this, but I am a bit dampened that the maximum memory available is 128GB. I was really hoping for 256GB, which would allow me to run frontier models locally. I think with 128GB it's still feasible to use this with something like Qwen3-Coder-Next and MiniMax-M2.5, but things like Kimi-K2.5 will require significant quantization to fit and model performance will really suffer.
I'm really wanting to build proper local-first AI workflows at home, and I think Apple has an opportunity to make that possible in a way other companies aren't really focused on, but we need significantly larger memory capabilities to do it, which I know is tough in the current memory market but should be available for a cost.
And your native CLI tools will continue to be from 2011 with 0 attention paid to the dev experience until itās Swift, and weāll continue to lock you out of running programs from other human beings we didnāt approve without a 6 step ritual in the OS. Oh and all apps will continue to constantly phone home i.e. pay for the machine so Google Adobe and Microsoft can run updaters and telemetry on it all day.
Right, actually instead of having first class tools and systems that respect us we should all go live in a hut in the forest āif it bothers usā. Apple is right there next to them abusing our machines and makes 0 effort to protect users from this.
Can Apple marketing please reduce the insane quantity of adjectives in its releases, it has been nauseating to read for decades and sickens me when visiting their sites. Early exit from me and ex-OSX dev for over a decade, wont be back until their core culture changes.
Private AI assistants will be a big thing. You don't want to send all your private data they have access to to a cloud AI API provider. You shouldn't, anyway.
Local LLMs. Lots of people buy Macs due to their unified memory which obviates the need to buy a much more expensive GPU to get the same amount of VRAM.
I barely push my M2 Pro MBPs. Most of my wants aren't hardware-related, they're software-related. How it runs some games from 10-20 years ago very well, but only through hacky compatibility layers that shouldn't be necessary. How some parts of the OS have gotten "out of sync" with each other.
Actually, I can think of one hardware want: have they gotten it to where you can do external GPUs and the like more easily?
Would still buy one over any other laptop on the market today for what I use them for.
Well that's. Just. Great. I bought a 64GB M4 Max MBP last month. I'm past the 14-day return window. I figured the M5 was near, but assumed M5 Max would come a bit later. Not sure where I came up with that.
You can console yourself with the fact that your laptop, unlike one of the new ones if you'd bought that instead, can run macOS Sequoia (without "Liquid Glass") rather than Tahoe.
This is always the gamble with buying a Mac. Either purchase right when the new is released, or be on the fence of your new becoming old a couple of weeks after purchase.
Yeah, I'm always envy of the Mac's power together with long battery times. But so tired of their software and dongles.
My current work laptop (Lenovo) is quite a beast as well when plugged in, but I can literally see the battery percentage tick down while unplugged, but colleagues with their Macs can go all day.
With an additional $200/month subscription from Anthropic, because they noticed that the Kimi K2.5 they were able to run on their M5 comes nowhere close to matching Opus 4.6.
I chased down what the "4x faster at AI tasks" was measuring:
> Testing conducted by Apple in January 2026 using preproduction 13-inch and 15-inch MacBook Air systems with Apple M5, 10-core CPU, 10-core GPU, 32GB of unified memory, and 4TB SSD, and production 13-inch and 15-inch MacBook Air systems with Apple M4, 10-core CPU, 10-core GPU, 32GB of unified memory, and 2TB SSD. Time to first token measured with an 8K-token prompt using a 14-billion parameter model with 4-bit quantization, and LM Studio 0.4.1 (Build 1). Performance tests are conducted using specific computer systems and reflect the approximate performance of MacBook Air.
>Time to first token measured with an 8K-token prompt using a 14-billion parameter model with 4-bit quantization
Oh dear 14B and 4-bit quant? There are going to be a lot of embarrassed programmers who need to explain to their engineering managers why their Macbook can't reasonably run LLMs like they said it could. (This already happened at my fortune 20 company lol)
I wonder if Apple has foresight into locally running LLMs becoming sufficiently useful.
Quite interesting that it's now a selling point just like fps in Crysis was a long time ago.
Next is the fps of an AI playing Crysis.
Or tasks per minute of the AI doing your job for you
That measurement will be AI assembling MacBook pros vs human assemblers: number of units per hour, day, or whatever unit is most applicable.
That is talking about battery life, not AI tasks. Footnote 53, where it says, "Up to 18 hours battery life":
https://www.apple.com/macbook-pro/
So it's not measuring output tokens/s, just how long it takes to start generating tokens. Seems we'll have to wait for independent benchmarks to get useful numbers.
For many workflows involving real time human interaction, such as voice assistant, this is the most important metric. Very few tasks are as sensitive to quality, once a certain response quality threshold has been achieved, as is the software planning and writing tasks that most HN readers are likely familiar.
Does that include loading the model again? Apple seems to be the only company doing such shenanigans in their measurements
14-billion parameter model with 4-bit quantization seems rather small
I think these aren't meant to be representative of arbitrary userland-workload LLM inferences, but rather the kinds of tasks macOS might spin up a background LLM inference for. Like the Apple Intelligence stuff, or Photos auto-tagging, etc. You wouldn't want the OS to ever be spinning up a model that uses 98% of RAM, so Apple probably considers themselves to have at most 50% of RAM as working headroom for any such workloads.
It's not much for a frontier AI but it can be a very useful specialized LLM.
On my 24GB RAM M4 Pro MBP some models run very quickly through LM Studio to Zed, I was able to ask it to write some code. Course my fan starts spinning off like the worlds ending, but its still impressive what I can do 100% locally. I can't imagine on a more serious setup like the Mac Studio.
How is the output quality of the smaller models?
For anyone who has been watching Apple since the iPod commercials, Apple really really has grey area in the honesty of their marketing.
And not even diehard Apple fanboys deny this.
I genuinely feel bad for people who fall for their marketing thinking they will run LLMs. Oh well, I got scammed on runescape as a child when someone said they could trim my armor... Everyone needs to learn.
Yesterday I ran qwen3.5:27b with an M1 Max and 64 GB of ram. I have even run Llama 70B when llama.cpp came out. These run sufficiently well but somewhat slow but compared to what the improvements with the M5 Max it will make it a much faster experience.
I don't know that there would be a huge overlap between the people who would fall for this type of marketing and the people who want to run LLMs locally.
There definitely are some who fit into this category, but if they're buying the latest and greatest on a whim then they've likely got money to burn and you probably don't need to feel bad for them.
Reminds me of the saying: "A fool and his money are soon parted".
It is.
That's how they make loot on their 128GB MacBook Pros. By kneecapping the cheap stuff. Don't think for a second that the specs weren't chosen so that professional developers would have to shell out the 8 grand for the legit machine. They're only gonna let us do the bare minimum on a MacBook Air.
Seems very reasonable to me
A bit strange to use time to first token instead of throughput.
Latency to the first token is not like a web page where first paint already has useful things to show. The first token is "The ", and you'll be very happy it's there in 50ms instead of 200ms... but then what you really want to know is how quickly you'll get the rest of the sentence (throughput)
As far as benchmarketing goes they clearly went with prefill because it's much easier for apple to improve prefill numbers (flops-dominated) than decode (bandwidth-dominated, at least for local inference); M5 unified memory bandwidth is only about 10% better than the M4.
In previous generations, throughout was excellent for an integrated GPU, but the time to first token was lacking.
So throughput was already good but TTFT was the metric that needed more improvement?
To add to the sibling "good is relative" it also depends what you're running, not just your relative tolerances of what good is. E.g. in a MoE the decode speedup means the speed of prompt processing delay is more noticeable for the same size model in RAM.
Good is relative but first token was clearly the biggest limitation.
Not strange, for the kind of applications models at that size are often used for the prefill is the main factor in responsiveness. Large prompt, small completion.
I assume itās time to first output token so itās basically throughput. How fast can it output 8001 tokens
No you don't. Not as a sticky mushy human with emotions watching tokens drip in. There's a lot of feeling and emotion not backed by hard facts and data going around, and most people would rather see something happening even if it takes longer overall. Hence spinner.gif, that doesn't actually remotely do a damned thing, but it gives users reassurance that they're waiting for something good. So human psychology makes time to first token an important metric to look at, although it's not the only one.
Some kinds of spinners serve as a coal-mine canary indicating if the app has gotten wedged. Not hugely useful, but also not entirely useless.
I would consider it reasonable if this was 4x TTFT and Throughput, but it seems like it's only for TTFT.
"Scaling up performance from M5 and offering the same breakthrough GPU architecture with a Neural Accelerator in each core, M5 Pro and M5 Max deliver up to 4x faster LLM prompt processing than M4 Pro and M4 Max, and up to 8x AI image generation than M1 Pro and M1 Max."
Are they doubling down on local LLMs then?
I still think Apple has a huge opportunity in privacy first LLMs but so far I'm not seeing much execution. Wondering if that will change with the overhaul of Siri this spring.
I think its just marketing, and the marketing is working. Look how many people bought Minis and ended up just paying for API calls anyway. (Saw it IRL 2x, see it on reddit openclaw daily)
I don't mind it, I open Apple stock. But I'm def not buying into their rebranding of integrated GPU under the guise of Unified Memory.
> Look how many people bought Minis and ended up just paying for API calls anyway. (Saw it IRL 2x, see it on reddit openclaw daily)
Aren't the OpenClaw enjoyers buying Mac Minis because it's the cheapest thing which runs macOS, the only platform which can programmatically interface with iMessage and other Apple ecosystem stuff? It has nothing to do with the hardware really.
Still, buying a brand new Mac Mini for that purpose seems kind of pointless when a used M1 model would achieve the same thing.
Itās exactly that. They are buying the base model just for that. You are not going to do much local AI with those 16GB of ram anyway, it could be useful for small things but the main purpose of the Mini is being able to interact with the apple apps and services.
16GB should be enough for TTS/Voice models running locally no ? I was thinking about having a home assistant setup like that where the voice is local and the brain is API based
Sure, thatās why I said maybe itās useful for a few things. But the main reason people were recommending the Mini was for its price (base model) and having access to the Apple services for clawdbot to leverage. Not precisely for local AI.
I run ministral for my home knowledge database on 24G iMac and some other non-agentic LLM things.
No one is buying a base model Mac for local LLM. Everyone is forgetting the PC prices have drastically increased due to RAM and SSD. Meanwhile, Macs had no such price changeā¦ at least for the models that didnāt just drop today. Macās are just a good deal at the moment.
> Meanwhile, Macs had no such price change
Yeah because Mac upgrade prices were already sky high, long before the component shortage. 32GB of DDR5-6000 for a PC rocketed from $100 to $500, while the cost of adding 16GB to a Mac was and still is $400.
I'm kind of curious how Apple's supply contracts actually work, because it's currently more attractive to buy a Mac with a lot of RAM than it usually is, relative to a PC. So if it's "we negotiated a price and you give us as much RAM as we sell machines" the company supplying the RAM is getting soaked because they're having to supply even more RAM to Apple for a below-market price.
But if the contract was for a specific amount of RAM and then people start coming to Apple more for high RAM machines, they're going to exhaust their contract sooner than usual and run out of cheap memory to buy. Then they have to decide if they want to lower their margins or raise the already-high price up to nosebleed levels.
the new models cost $200 more for each 8GB of Ram you add.. Ouch...
That's been the case for years. Not new to the M5's
There are so few used Mac Mini around, those are all gone and what is left is to buy new.
Worse than that, they hold their value, so buying a used M1 mini is still a few hundred bucks, and saving $200-300 by purchasing a 5 generation older mini seems like a bad deal in comparison.
Someone came to be excited they got a "deal" on the newest Intel Mac Mini for hosting OpenClaw. 8GB model for $300. I kind of regret bursting their bubble by telling them you can walk over to Costco (nearest one at time of discussion was walking distance) and pay $550 for one with an M4 and 16GB of RAM.
Up until a week ago, the base m4 mini (16gb ram/256gb ssd) was $399 at microcenter, now $499. Pretty shocking how good of a value that is IMO.
Just like with GPUs and Bitcoin they'll be a flood of old hardware on the market eventually.
Can't they simply run MacOS on a VM on existing Mac hardware?
You arenāt going to run a network connected 24/7 online agent from a laptop because itās battery powered and portable.
Not if you want it to be able to use the hardware identifiers to register for use with iMessage.
Not true as of macOS 15 onwards [1].
[1]: https://developer.apple.com/documentation/virtualization/usi...
> Aren't the OpenClaw enjoyers buying Mac Minis because it's the cheapest thing which runs macOS
That's likely only part of the reason. Mac Mini is now "cheap" because everyone exploded in price. RAM and SSD etc have all gone up massively. Not the mention Mac mini is easy out of the box experience.
It's not cheap, though. Two weeks ago I bought a computer with a similar form factor (GMKtec G10). Worse CPU and GPU but same 16GB memory and a larger SSD for 40% the price of a base mac mini ($239 vs $599). It came with Windows preinstalled, but I immediately wiped that to install linux. Even a used (M-series) mac mini is substantially more expensive. It will cost me about an extra penny per day in electricity costs over a mac mini, but I won't be alive long enough for the mac mini to catch up on that metric.
I considered the mac mini at the time, but the mac mini only makes sense if you need the local processing power or the apple ecosystem integration. It's certainly not cheaper if you just need a small box to make API calls and do minimal local processing.
It's cheap for what you get.
If you just need "a small box to make API calls and do minimal local processing" you an also just buy a RPI for a fraction of the price of the GMKtec G10.
All 3 serve a different purpose; just because you can buy a slower machine for less doesn't mean the price:performance of the M1 Mac Mini changes.
> you an also just buy a RPI for a fraction of the price of the GMKtec G10.
Sadly not really. The Pi 5 8gb canakit starter set, which feels like a more true price since it's including power supply, MicroSD card, and case, is now $210. The pi5 8gb by itself is $135.
A 16gb pi5 kit, to match just the RAM capacity to say nothing of the difference in storage {size, speed, quality} and networking, is then also an eye watering $300
>you an also just buy a RPI for a fraction of the price
lol. you need to look at rpi 5 prices again. they are insane.
If you need the CPU power in the Mac Mini then it is a pretty good price-to-performance ratio.
> It came with Windows preinstalled, but I immediately wiped that to install linux.
Do you really need Openclaw now? And not claude code + zapier or Claude code + cron?
That's the point. If you have worse CPU and GPU Windows will be sluggish (it's bloated).
Bro. The used M1 mini and studio are all gone. I was thinking of buying one for local AI before openclaw came out and went back to look and the order book is near empty. Swappa is cleared out. eBay is to the point that the m1 studio is selling for at least a thousand more.
This arb youāre talking about doesnāt exist. An m1 studio with 64 gb was $1300 prior to openclaw. Youāre not getting that today.
I would have preferred that too since I could Asahi it later. Itās just not cheap any more. The m4 is flat $500 at microcenter.
yes, and its funny that all these critical people dont know this
Why not? The integrated GPUs are quite powerful, and having access to 32+ GB of GPU memory is amazing. There's a reason people buy Macs for local LLM work. Nothing else on the market really beats it right now.
My M4 MacBook Pro for work just came a few weeks ago with 128 GB of RAM. Some simple voice customization started using 90GB. The unified memory value is there.
Jeff Geerling had a video of using 4 Mac Studios each with 512GB RAM connected by Thunderbolt. Each machine is around $10K so this isn't cheap but the performance is impressive.
https://www.youtube.com/watch?v=x4_RsUxRjKU
If 40k is the barrier to entry for impressive, that doesn't really sell the usecase of local LLMs very well.
For the same price in API calls, you could fund AI driven development across a small team for quite a long while.
Whether that remains the case once those models are no longer subsidized, TBD. But as of today the comparison isn't even close.
Itās what a small business might have paid for an onprem web server a couple of decades ago before clouds caught on. I figure if a legal or medical practice saw value in LLMs it wouldnāt be a big deal to shove 50k into a closet
You would still have to do some pretty outstanding volume before that makes sense over choosing the "Enterprise" plan from OpenAI or Anthropic if data retention is the motivation.
Assuming, of course, that your legal team signs off on their assurance not to train on or store your data with said Enterprise plans.
At least with the server you know what you are buying.
With Anthropic you're paying for "more tokens than the free plan" which has no meaning
With M3 Max with 64GB of unified ram you can code with a local LLM, so the bar is much lower
But why? Spending several thousand dollars to run sub-par models when the break-even point could still be years away seems bizarre for any real usecase where your goal is productivity over novelty. Anyone who has used Codex or Opus can attest that the difference between those and a locally available model like Qwen or Codestral is night and day.
To be clear, I totally get the idea of running local LLMs for toy reasons. But in a business context the sell on a stack of Mac Pros seems misguided at best.
I started doing it to hedge myself for inevitable disappearance of cheap inference.
Sometimes you can't push your working data to third party service, by law, by contract, or by preference.
I ran the qwen 3.5 35b a3b q4 model locally on a ryzen server with 64k context window and 5-8 tokens a second.
It is the first local model I've tried which could reason properly. Similar to Gemini 2.5 or sonnet 3.5. I gave it some tools to call , asked claude to order it around, (download quotes, print charts, set up a gnome extension) even claude was sort of impressed that it could get the job done.
Point is, it is really close. It isn't opus 4.5 yet, but very promising given the size. Local is definitely getting there and even without GPUs.
But you're right, I see no reason to spend right now.
Getting Opus to call something local sounds interesting, since that's more or less what it's doing with Sonnet anyway if you're using Claude Code. How are you getting it to call out to local models? Skills? Or paying the API costs and using Pi?
It's not. I've got a single one of those 512GB machines and it's pretty damn impressive for a local model.
Assuming you ran the gamut up from what you could fit on 32 or 64GB previously, how noticeable is the difference between models you can run on that vs. the 512GB you have now?
I've been working my way up from a 3090 system and I've been surprised by how underwhelming even the finetunes are for complex coding tasks, once you've worked with Opus. Does it get better? As in, noticeably and not just "hallucinates a few minutes later than usual"?
I'm not really into AI and LLMs. I personally don't like anything they output. But the people I know who are into it and into running their own local setups are buying Studios and Minis for their at home local LLM set ups. Really, everyone I personally know who is doing their build your own with local LLMs are doing this. I don't know anyone anymore buying other computers and NVIDIA graphics cards for it.
I think people buying those don't realize requirements to run something as big as Opus, they think those gigabytes of memory on Mac studio/mini is a lot only to find out that its "meh" on context of LLMs. Plus most buy it as a gateway into Apple ecosystem for their Claws, iMessage for example.
> But I'm def not buying into their rebranding of integrated GPU under the guise of Unified Memory.
But it is Unified Memory? Thanks to Intel iGPU term is tainted for a long time.
The biggest problem with personal ML workflows on Mac right now is the software.
I'm curious to know what software you're referring to.
Yes
I've tried to use a local LLM on an M4 Pro machine and it's quite painful. Not surprised that people into LLMs would pay for tokens instead of trying to force their poor MacBooks to do it.
Local LLM inference is all about memory bandwidth, and an M4 pro only has about the same as a Strix Halo or DGX Spark. That's why the older ultras are popular with the local LLM crowd.
Qwen 3.5 35B-A3B and 27B have changed the game for me. I expect we'll see something comparable to Sonnet 4.6 running locally sometime this year.
Could be, but it likely won't be able to support the massive context window required for performance on par with sonnet 4.6
Iām super happy with it for embedding, image recog, and semantic video segmentation tasks.
What are the other specs and how's your setup look? You need a minimum of 24GB of RAM for it to run 16GB or less models.
Tokens per second is abysmal no matter how much ram you have
Some models run worse than others but I have gotten reasonable performance on my M4 Pro with 24 GB of RAM
This is typically true.
And while it is stupid slow, you can run models of hard drive or swap space. You wouldnāt do it normally, but it can be done to check an answer in one model versus another.
48 GB MacBook Pro. All of the models I've tried have been slow and also offered terrible results.
Try a software called TG Pro lets you override fan settings, Apple likes to let your Mac burn in an inferno before the fans kick in. It gives me more consistent throughput. I have less RAM than you and I can run some smaller models just fine, with reasonable performance. GPT20b was one.
Local LLMs are useful for stuff like tool calling
What models are you using? Iāve found that SOTA Claudes outperform even gpt-5.2 so hard on this that itās cheaper to just use Sonnet because num output tokens to solve problem is so much lower that TCO is lower. Iām in SF where home power is 54Ā¢/kWh.
Sonnet is so fast too. GPT-5.2 needs reasoning tuned up to get tool calling reliable and Qwen3 Coder Next wasnāt close. I havenāt tried Qwen3.5-A3B. Hearing rave reviews though.
If youāre using successfully some model knowing that alone is very helpful to me.
We had a workshop 6 months ago and while I've always been sceptical of OpenAI,etc's silly AGI/ASI claims, the investments have shown the way to a lot of new technology and has opened up a genie that won't be put back into the bottle.
Now extrapolating in line with how Sun servers around year 2000 cost a fortune and can be emulated by a 5$ VPS today, Apple is seeing that they can maybe grab the local LLM workloads if they act now with their integrated chip development.
But to grab that, they need developers to rely less on CUDA via Python or have other proper hardware support for those environments, and that won't happen without the hardware being there first and the machines being able to be built with enough memory (refreshing to see Apple support 128gb even if it'll probably bleed you dry).
I feel like the push by devs towards Metal compatibility has been 10x than AMD. I assume that's because the majority of us run MacBooks.
The only "push" towards Metal compatibility there's been has been complaints on github issues. Not only has none of the work been done, absolutely nobody in their right mind wants to work on Metal compatibility. Replacing proprietary with proprietary is absolutely nobody's weekend project. or paid project.
If coding by AI was truly solved then it would be done with AI, right?
I think that might be partly because on regular PC's you can just go and buy an NVidia card insteaf of fuzzing around with software issues, and for those on laptops they probably hope that something like Zluda will solve it via software shims or MS backed ML api's.
Basically, too many choices to "focus on" makes non a winner except the incumbent.
Which majority?
I certainly only use Macs when being project assigned, then there are plenty of developers out there whose job has nothing to do with what Apple offers.
Also while Metal is a very cool API, I rather play with Vulkan, CUDA and DirectX, as do the large majority of game developers.
Honestly though, gamedevs really are among the biggest Windows stalwarts due to SDK's and older 3d software.
Only groups of developers more tied to Windows that I can think of are probably embedded people tied due to weird hardware SDK's and Windows Active Directory dependent enterprise people.
Outside of that almost everyone hip seems to want a Mac.
80% of the desktop market has to have their applications developed by someone, at least until software replicators replace them.
Everyone hip alright, or at least those that would dream to earn a salary big enough to afford Apple taxes.
Remember there are world regions where developers barely make 1 000 euros per month.
Who is "us" in this case? Majority of devs that took the stack overflow survey use Windows:
https://survey.stackoverflow.co/2025/technology/#1-computer-...
That's the broad developer community. 90%+ of the engineers at Big Tech and the technorati startups are on MacOS with 5% on Linux and the other 5% on Windows.
Source?
> 90%+ of the engineers at Big Tech and the technorati startups
The US 1s? Is that why we have Deepseek and then other non-US open source LLMs catching up rapidly?
World view please. The developer community is not US only.
Youāll see a lot of MacBooks in Beijingās zhongguangcun where all the tech companies are, but they also have a lot of students there as well, so who knows. You need to go out to the suburbs where Lenovo has offices to stop seeing them. I know Apple is common in Western Europe having lived there for two years (but that was 20 years ago, I lived in China for 9 years after that).
It wouldnāt surprise me if the deepseek people were primarily using Macās. Maybe Alibaba might be using PCs? Iām not sure.
I think it's reasonable to say that the people responding to surveys on Stack Overflow aren't the same people who work on pushing the state of the art in local LLM deployment. (which doesn't prove that that crowd is Apple-centric, of course)
Perhaps. Though Windows has been the majority share even when stack overflow was at it's peak, and before.
It's not the whole answer, but SO came from the .NET world and focused on it first so it had a disproportionately MS heavy audience for some time. GitHub had the same issue the other way around. Ruby was one of GitHub's top five languages for its first decade for similar reasons.
Majority of devs are in the global south I presume
Torch mlp support on my local macbook outperforms CUDA T4 on Colab.
Except CUDA feels really cozy, because like Microsoft, NVidia understands the Developers, Developers, Developers mantra.
People always overlook that CUDA is a polyglot ecosystem, the IDE and graphical debugging experience where one can even single step on GPU code, the libraries ecosystem.
And as of last year, NVidia has started to take Python seriously and now with cuTile based JIT, it is possible to write CUDA kernels in pure Python, not having Python generate C++ code that other tools than ingest.
They are getting ahead of Modular, with Python.
> Are they doubling down on local LLMs then?
Apple is in the hardware business.
They want you to buy their hardware.
People using Cloud for compute is essentially competitive to their core business.
"Doubling down on already being the best hardware for local inference"
> Are they doubling down on local LLMs then?
Neural Accelerators (aka NAX) accelerates matmults with tile sizes >= 32. From a very high level perspective, LLM inference has two phases: (chunked) prefill and decode. The former is matmults (GEMM) and the latter is matrix vector mults (GEMV). Neural Accelerators make the former (prefill) faster and have no impact on the latter.
There already are a bunch of task-specific models running on their devices, it makes sense to maintain and build capacity in that area.
I assume they have a moderate bet on on-device SLMs in addition to other ML models, but not much planned for LLMs, which at that scale, might be good as generalists but very poor at guaranteeing success for each specific minute tasks you want done.
In short: 8gb to store tens of very small and fast purpose-specific models is much better than a single 8gb LLM trying to do everything.
Probably possible for pure coding models. I see on-device models becoming viable and usable in like 2-3 years on device
"Apple Intelligence is even more capable while protecting usersā privacy at every step."
Remains to be seen how capable it actually is. But they're certainly trying to sell the privacy aspect.
> Remains to be seen how capable it actually is.
It's the best. We all turned it off. 100% privacy.
Given all the supply issues w/ Nvidia, I think Apple's AI strategy should be - local AI everything (not just LLMs), but also make Metal competitive w/ CUDA. Their ace in the hole is the unified memory model.
Apple's stated AI strategy is local where it can and cloud where it needs. So "doubling down"? Probably not. But it fits in their strategy.
The hardware capabilities that make local LLMs fast are useful for a lot of different AI workloads. Local LLMs are a hot topic right now so thatās what the marketing team is using as an example to make it relatable.
But memory bandwidth (bottleneck for LLM inference) is only marginally improved, 614 GB/s vs 546 GB/s for M4/M5 Max - where is this 4x improvement coming from?
I think I'll pass on upgrading.
Itās prompt processing so prefill - thatās compute bound not memory.
4x is on Time To First Token it's on the graph.
> Are they doubling down on local LLMs then?
Honestly, I think that's the move for apple. They do not seem to have any interest in creating a frontier lab/model -- why would they give the capex and how far behind they are.
But open source models (Kimi, Deepseek, Qwen) are getting better and better, and apple makes excellent hardware for local LLMs. How appealing would it be to have your own LLM that knows all your secrets and doesnt serve you ads/slop, versus OpenAI and SCam Altman having all your secrets? I would seriously consider it even if the performance was not quite there. And no need for subscription + cli tool.
I think apple is in the best position to have native AI, versus the competition which end up being edge nodes for the big 4 frontier labs.
RE Frontier models/hardware: I'm interested to see what happens with their "private cloud compute" marketing concept now that they're moving from running Siri AI experiences on Apple servers to Google servers instead.
> Are they doubling down on local LLMs then?
I love the push to local llms. But itās hilarious how apple a few years ago was so reluctant to even mention āAIā in its keynotes and fast forward a couple years theyāve fully embraced it. I mean I like that they embraced it rather than be ādifferentā (stubborn) and stay behind the tech industry. Itās the smart choice. I just think itās funny.
Apple's AI strategy really kind of threads the needle cleverly.
"AI" (LLMs) may or may not have a bubble-pop moment, but until it does Apple get to ride it on these press releases and claims. But if the big-pop occurs, then Apple winds up with really fantastic hardware that just happens to be good at AI workloads (as well as general computing).
For example, image classification (e.g. face recognition/photo tagging), ASR+vocoders, image enhancement, OCR, et al, were popular before the current boom, and will likely remain popular after. Even if LLM usage dries up/falls out of vogue, this hardware still offers a significant user benefit.
LLM usage is not very likely to "dry up".
What is more likely to happen though is that it doesn't take multiple $10B of datacenter and capital to build out models--and the performance against LLM benchmarks starts to max out to the point where throwing more capital at it doesn't make enough of a difference to matter.
Once the costs shrink below $1B then Apple could start building their own models with the $139B in cash and marketable securities that they have--while everyone else has burned through $100B trying to be first.
Of course the problem with this strategy right now is that Siri really, really sucks. They do need to come up with some product improvements now so that they don't get completely lapped.
those things could likely just run fine on the gpu though
They could run fine on the CPU too. But these are mobile devices, therefore battery usage is another significant metric. Dedicated hardware is more energy efficient than general hardware, and GPU in particular is a power-hog.
Exactly. It's the same thing as video or audio encoding and decoding. Sure the CPU could do it, potentially use the GPU, but having actual hardware encoders and decoders for the most common codecs will save a lot of energy.
Not if GPU RAM is a limiter. Which it is for most models.
Unified memory is a serious architectural improvement.
How many GPUs does it take to match the RAM, and make up for the additional communication overhead, of a RAM-maxed Mac? Whatever the answer, it wonāt fit in a MacBook Proās physical and energy envelopes. Or that of an all-in-one like the Studio.
Honestly, they can keep waiting for another year or two for on-device models at the size they're looking for to be powerful enough.
have you seen that github repo where they unlock the true power of NE?
Have a link?
Didn't they announce a partnership with Google Gemini?
looks like this will be their angle for the whole agentic AI topic
It is simply marketing nonsense - what they really mean (I think) is they support matrix multiplication (matmul) at the hardware level which given AI is mostly matrix multiplications you'll get much faster inference (and some increase in training too) on this new hardware. I'm looking forward to seeing how fast a local 96gb+ LLM is on the M5 Max with 128gb of RAM.
We've already established in this thread that memory bandwidth isn't that much greater than M4 Max - 12%? However, I wonder if batched inference will benefit greatly from the vastly improved compute. My guess is that parallel usage of the same model will be a couple times faster. So, single "threaded" use not that much better, but say you want to run a lot of batch jobs, it'd be way faster?
Is this a reply to a different comment?
Itās not necessarily doubling down on local. The reality is your LLM should be inferencing every tick ā¦ the same way your brain thinks every. Fucking. Nano. Second.
So yes, the LLM should be inferencing on your prompt, but it should also be inferencing on 25,000 other things ā¦ in parallel.
Those are the compute needs.
We just need compute everywhere as fast as possible.
I've been so disappointed in Apple's lack of execution on this. There is so much potential for fantastic local models to run and intelligently connect to cloud models.
I just don't get why they're dropping the ball so much on this.
Because it wonāt sell enough hardware to matter to them.
They arenāt dropping the ball, they are being smart and prudent.
Downvote all you want. Point blank, they are dropping the ball.
> doubling down on local LLMs
Do think it'll be common to see pros purchasing expensive PCs approaching Ā£25k or more if they could run SoTA multi-modal LLMs faster & locally.
A useful llm that needs 64gb of ram and mid double digit cores is not useful for 99% of their customers. The LLMs they have on iphone 17's certainly cannot do anything useful other than summerization and stuff. It's a hardware constraint that they have.
Apple absolutely has a massive opportunity here because they used a shared memory architecture.
So as most people in or adjacent to the AI space know, NVidia gatekeeps their best GPUs with the most memory by making them eye-wateringly expensive. It's a form of market segmentation. So consumer GPUs top out at 16GB (5090 currently) while the best AI GPUs (H200?) is 141GB (I just had to search)? I think the previou sgen was 80GB.
But these GPUs are north of $30k.
Now the Mac Studio tops out currently at 512GB os SHARED memory. That means you can potentially run a much larger model locally without distributing it across machines. Currently that retails at $9500 but that's relatively cheap, in comparison.
But, as it stands now, the best Apple chips have significantly lower memory bandwidth than NVidia GPUs and that really impacts tokens/second.
So I've been waiting to see if Apple will realize this and address it in the next generation of Mac Studios (and, to a lesser extend, Macbook Pros). The H200 seems to be 4.8TB/s. IIRC the 5090 is ~1.8TB/s. The best Apple is (IIRC) 819GB/s on the M3 Ultra.
Apple could really make a dent in NVidia's monopoly here if they address some of these technical limitations.
So I just checked the memory bandwidth of these new chips and it seems like the M5 is 153GB/s, M5 Pro is ~300 and M5 Max is ~600. I was hoping for higher. This isn't a big jump from the M4 generation. I suspect the new Studios will probably barely break 1TB/s. I had been hoping for higher.
It will be interesting to see the specs on an m5 ultra. Probably have to wait until WWDC at the earliest to see it though
>So consumer GPUs top out at 16GB (5090 currently)
5090 has 32GB, and the 4090 and 3090 both have 24GB.
Hard to get 6000+ bit memory bus HBM bandwidth out of a 512 or 1024 bit memory bus tied to DDR... I think it's also just tough to physically tie in 512 gigs close enough to the GPU to run at those speeds. But yeah, I wish there was a very competitive local option, too, short of spending $50k+.
The topic is MacBook, so my criticism is a little off. However, I really dont believe in this "local LLM" promise from Apple. My phone already gets noticeably warm if I answer 5 WhatsApp messages. And looses 5% of battery during the process. I highly doubt Apple will have a useable local LLM that doesn't drain my battery in minutes, before 2030.
Something is not right if WhatsApp is seriously draining your phone like that. Admittedly Iām not a big WhatsApp user my iPhone hasnāt had any trouble like that with it.
Yeah is OP using an iPhone X?
What % of users actually care that much about local LLMs? It appears to still be an inferior (though maybe decent) service compared to ChatGPT etc., and requires very top-end hardware. Is privacy _that_ important to people when their Google search history has been a gateway to the soul for years? I wonder if these machines would cost significantly less (or put the cost to other things, e.g. more CPU cores) without this emphasis on LLMs.
Privacy is definitely not a cern for the layman, but it is for lots of people, especially pro users. I also havenāt made a google search in years.
I also havenāt seen any improvements in the frontier models in years, and Iām anxiously awaiting local models to catch up.
> I still think Apple has a huge opportunity in privacy first LLMs
This correlation of Apple and privacy needs to rest. They have consistently proven to be otherwise - despite heavily marketing themselves as "privacy-first"
https://www.theguardian.com/technology/2019/jul/26/apple-con...
I think it's a little telling that the best you can do is a seven year old article.
So, somehow now they are the beacons of privacy and we should just ignore their history of spying on their users?
No other company makes you tell them every application you install on your device. No other company makes you tell them every location you read from your GPS sensor.
I think it's all about relativity. Are they private compared to an open source privacy focused OS like grapheneOS and the fantastic folks running that project? No. Are they more private than a company like meta or google who has much worse incentives for privacy than Apple? Probably.
Do I wish Apple was way more transparent and gave users more control over gatekeeper and other controversial features that erode privacy? Absolutely.
Not for everything. Apple has initially focused on edge AI that runs locally per device. It didnāt work out well the first try, but I would still bet on them trying again once compute catches up. Besides, they still have a better track record than the other tech giants.
I love the following section of their copy:
> Even More Value for Upgraders
> The new 14- and 16-inch MacBook Pro with M5 Pro and M5 Max mark a major leap for pro users. Thereās never been a better time for customers to upgrade from a previous generation of MacBook Pro with Apple silicon or an Intel-based Mac.
I read as "Whoops we made the M1 Macbook Pro too good, please upgrade!"
I think I will get another 2-5 years out my mine.
Apple: If you document the hardware enough for the Asahi team to deliver a polished Linux experiene, I'll buy one this year!
My 32gb m1 max was probably the best purchase I've made. Still plenty of headroom in performance left in this beast. Wonder what reason they'll use to end software support in the future. Bet it'll be some security hardware they make up for the sake of forcing upgrades.
my tinfoil hat theory is that they make small features depend on new hardware.
for example, let's say the new os depends on m5's exclusive thumbnail generator accelerator, and let's say it improves speed by a 20%.
now, your M1 notebook than on previous OSes uses standard gpu acceleration for thumbnails will not have this specialized hardware acceleration, it will have software fallback that will be 90% slower.
you won't notice it a first thought because it's stuff, fast, but it eats a bit of the processor.
multiply this by 1000 features and you have a slow machine.
I don't know how else to explain how an ipad pro cannot even scroll a menu without stuttering, it's insane how fast these things were on release
yes pretty much this. make useless features use up resources and make basic scrolling slow.
the Liquid Glass for example probably is not so great when it comes to resources. Probably works better with latest metal and hardware blocks on the GPU in M5 as opposed to using GPU cores and unified memory on 8gb M1 making latest macOS work not so great. I have the M1 8gb air and it is really slow on Tahoe. It was snappy just a couple of years ago on a fresh install.
I downgraded today for the first time in my life. Sequoia is crazy fast in my MacBook Air m2 16gb
Not upgrading any of my Macs ever again. I was a fanboy looking for every new update like a present, for 13 years, not anymore. It took one Tahoe burn all that trust. Never upgrading major OS versions on hardware from Apple again.
I think this could go equally for Windows as well, and many other software (not just OS). I purpose refrained from Tahoe because I didn't like the design but I wanted to know what the consensus was on it before upgrading. Apparently it's bad!
Win 11 is bad compared to Win 10 as well. I'm fairly new to Linux so I can't really form an opinion there.
It's not tinfoil, that's just how publicly traded companies work - increasing the share value
Ditto, I don't see myself upgrading in the near future, the 64GB M1 Max I paid 2499 at the end of 2023 still feels like a new machine, nothing I do can slow it down. Apple kept OS updated for around 6 years in Intel times, I don't see how they can drop support for this one tbh. I'm still paying for apple care since I depend on it so much
Some of my M1 MBP Max keys are losing their coating, and the battery is at 74% capacity. At some point soon I'll need a service. But other than that, I have no real complaints. Even the case edge where my arms constantly rest doesn't look too bad.
My next MBP will have 128GB memory, but these prices just wanna make me wait longer.
If you don't mind a bit of DIY, apple runs self service repair.
https://support.apple.com/self-service-repair
Those keys are easily replaced, my friend.
I've been on a Macbook M1 Pro since 2022 (bought refurbished on Amazon for cheap) and it's still such a powerhouse. It doesn't struggle at all with anything that I throw at it. Kind of amazing.
Nothing has broken and I consistently get 4-6 hours of heavy work time while on battery. An amazing machine for the price I paid.
> I read as "Whoops we made the M1 Macbook Pro too good, please upgrade!"
As there target for that marketing, I can report it hits home!
But objectively, there is nothing wrong with my current experience at all.
I have never had that experience over many generations and types of machines. The M1 keeps looking better and better in hindsight.
ā-
Looking forward, either the M5 is the next M1, a bump of good that will last. Or Apple will be really firing on all cylinders if it can āobsoleteā the M5 anytime soon.
Well, I just upgraded from Intel late last year. There are lots of users still on Intel :)
There was a magical window at Google where you could be issued an iMac Pro 5k. (To this day, the standard issue monitor is still 1440p.)
~9 years later, there are a lot of people still using it as their main machine, waiting until we get kicked off the corp network for lack of software support.
Was that one of the ones that could do "target display mode" and become a monitor for another machine?
Nope - they removed that feature, so now come the end of the year, they're all e-waste.
It feels really stupid to have to throw away a perfectly capable machine with 64GB of RAM in 2026.
Wait, they throw them away, not sell or give to employees? I feel like as long as the computer is reset, indeed it is stupid to just throw it away instead of giving or selling it to someone who wants it.
They could resell, but maybe another way to phrase this, tying the screen to the obsolete computer greatly reduces the useful lifespan of the screen. Then again at that time, DisplayPort didn't do enough bandwidth to have that kind of display externally.
Same, in fact the only reason right now that I would upgrade my m1 pro is if they threaten to change the design by getting rid of the hdmi or sd card slot, or doing something stupid like when they added the touch bar. I was locked into my old intel pro for so long because of all the bad hardware choices they were making.
You may get your wish with all the rumors of a touch screen on the M6 MBPs.
Love that they didn't learn anything from the touchbar.
They just didn't do anything with the touchbar. It could have actually been more useful. The removal of the esc key was pretty dumb though.
The only useful thing I remember about the touch bar was the DJ trying to play some beats on the touch bar. That was just weird imo.
Barring removal of Esc key, I think the touch bar was useful because it showed contextual actions. But not every app used it so it didn't really get a chance to shine.
I wish theyād come back with physical keys, with tiny changeable displays on each one. Customisation, but touch feel without looking.
Comparing the touchbar to a touch screen is silly
I guess I'm just a luddite that spends my life on a CLI or text editor. Taking my hands away from my keyboard to leave finger prints on my screen just doesn't make sense to me.
I think people that do do tasks where a touch screen makes sense are probably just doing most of their work on an iphone or an ipad anyway.
Now gesture control on VR/AR setups? Sure, that feels like a new human/computer interaction system that makes sense. Jabbing at my laptop screen with one hand on my keyboard, not so much.
You are right the touch screen is even more stupid
Itās not. I had a thinkpad with a touchscreen and while I used the touchscreen seldomly, it was useful in some applications. Notably to easily develop touch based applications.
I have a M1 MacBook Pro with the touch bar since. Itās crap. I remember the keynote where they introduced it and a DJ mixed music using it. It was ridiculous that it got approved.
I do remember the cringy music demo. Can't believe someone really said "yeah let's rehearse this and actually sell this product."
Fortunately I just keep my laptop closed and use an attached display and keyboard and mouse, so I don't even remember if my M1 has a touch bar.
Also minor nit: it's seldom, not seldomly. Seldom certainly doesn't seem like an adverb, but it is.
My late-2021 M1 Pro is working fine but I think one of the fans is broken. When loaded it starts beeping every 7 seconds and won't stop until I reboot. It might be just dust but I'm reluctant to open it up. Maybe I should and if I break it I have a better reason to upgrade lol.
You can spray compressed air without opening the Macbook. Also iFixit has a nice guide if you do open it up: https://www.ifixit.com/Troubleshooting/Mac_Laptop/MacBook+Fa...
I read it the same way. I should've gotten way more RAM back when I got my M1 and RAM was still cheap although this was of course before the LLM boom so there was no way to really know.
I maxed my M1 out when I bought it because I was frustrated with the 16GB max in the previous machines. I use my machine for all sorts of things and some days you just don't feel like exiting apps to make space for new ones.
I still don't have a strong urge to upgrade. I could probably get by on 32GB (like my work-issued machine is) but 64GB is the right amount of headroom for me.
>I read as "Whoops we made the M1 Macbook Pro too good, please upgrade!"
>I think I will get another 2-5 years out my mine.
I only own a M4 because the M1 had a hardware fault and I needed a replacement ASAP. (I sold the M1 after repair.)
Although I'm glad to have a newer machine with longer future support, I have yet to notice any meaningful performance difference.
Ditto. Though, I fixed my M1. I have an M4 max for work; the nano screen is a win. The perf is better, but it's really marginal unless actually doing stuff with the GPU, then it's super slow compared to a decent GPU anyway (i.e. h100, gb etc)
I have an M1 Max with 64 GB and an M4 Max with 128 GB and the latter feels noticeably snappier than the former. The latest MacOS release fucked up the M1ās performance. Wish I could downgrade easily. I want off that ride.
I have the M3 Pro (32gb) and an M4 Pro 16" (48gb), and the latter is sufficiently snappier to make me happy I waited to upgrade from my horrible Intel 13" i5 with 16gb. The M1 Pro I used for work a few years ago was great too. I'm not on Tahoe on either computer, thank god.
I have an M1 Max Macbook Pro, and having used many employer's newer variants of M-series macbook's since then, I'm still very satisfied with my M1 Max but
the air series is really good, and very light
my M1 is now noticeably heavy and I don't think upgrading to another Macbook Pro is the move the resell value of the M1 did not hold, specifically the bumped up storage models. There doesn't seem to be a market for 8TB of space specifically, but the base 1 - 2TB holds its value because the baseline of the MBP holds its value
M5 Max looks tempting if there is a very compelling tradein, but the M1 Max is pretty old so I don't have real hope of that, but I'll look. For AI Inference the difference doesn't seem good enough yet and necessary enough. I'll still need to use the cloud or aspire to have a specialized machine with more RAM or circuitry on my network.
Please, please. I'd love to use it with Debian.
I typed āRAMā to search for it and boy they hammer home how lucky I am to be getting 1TB SSD standard, but no mention of RAM anywhere on this page. Anyway, the MacBook Pro starts with 16GB of RAM. Itās $400 to go from 16GB to 32GB.
Interestingly, 36-128GB models are showing as ācurrently unavailableā on the store page, and you canāt even place an order for them right now? But for anyone curious, itās quoting $5099 for the 128GB RAM 14ā MacBook Pro model.
> Itās $400 to go from 16GB to 32GB.
No change from the previous models then, 16GB->32GB was already $400. They're cutting into their previously enormous margins to keep the prices stable, rather than hiking the prices to maintain their margins.
They bought the fab time for that RAM 2-3 years ago. Apple is renowned for their foresight and preparation. We'll eventually see price increases from Apple's RAM upgrade, but we're not there yet.
Commodity futures made sense to me at FedEx- they would pay money with a supplier for the option to buy gas/oil at X price at Y date in the future. It costs more than just agreeing to pay for it at that price in the future, but if deliveries went way down (or prices) it'd be less costly to "back out".
I wonder if there's a fab time secondary market where Wall Street types are making millions off speculating fab time.
Their margins may not have changed actually. https://youtu.be/IGCzo6s768o
This is not exactly correct. If you have an M5 Pro chip instead of m5 Chip - I just built a 16inch, M5 Pro chip, it is $400 to go from 24 -> 48gb. An additional $200 ($600 over base) to go to 64gb. So the memory prices change based on chip. M5 Max Chip starts with 48gb of memory.
M5 Max starts at 36GB memory at $3599. M4 Max started at the same memory at $3199. They have doubled the default storage from 1TB to 2TB, that's a $400 increase I'm paying even if I don't want the extra 1TB.
They raised the base price by $200.
Apple's previous policy of price gouging for RAM means no need to raise prices yet, they still have a buffer.
They also have long term contracts with the suppliers in all likelihood
In practice, you can really go a long way on 16GB on a Mac with unified memory. I like to say it's comparable to 32GB during the old Intel days.
They advertise local LLMs which will be servery limited with 16GD of RAM. Plus the GPU could in theory provide decent gaming performance but again might suffer from the RAM limit.
Most people can totally live with 16gigs but it is kind of a waste for the horsepower. They know what they are doing. Apple is a master in upselling.
Though personally I don't mid the aggressive upsellign as long as the quality is there. Problem is, the hardware quality is great but the software side is severely lacking and getting worse.
If anything, it's less, because you're giving up more RAM to the GPU.
Which, I mean, I love unified memory, as one of those weirdos that does do local LLM stuff and am contemplating if it's time to upgrade my m2 max.
But if you needed 32gb then you still need at least 32gb now. Unless swap on nvme disks is enough for you - and it isn't for me.
RAM is still RAM, the switch from crusty HDDs to fast NVMe SSDs may have helped to smooth things over when you spill into swap but it's not going to do miracles.
RAM isn't just RAM though. Unified memory on Apple Silicon provides significantly better memory management and efficiency compared to trad RAM
I know RAM is scarce and everything, but doubling down on LLM local acceleration with all of that dedicated silicon while at the same time sticking with Apple's traditional lack of RAM availability makes for a very weird product proposition to me.
> M5 Pro supports up to 64GB of unified memory with up to 307GB/s of memory bandwidth, while M5 Max supports up to 128GB of unified memory with up to 614GB/s of memory bandwidth
Isn't this it?
Ah yeah youāre right, thanks. I tried to at least make my post useful and pull up prices for the different tiers. Overall, those prices are surprisingly competitive now compared to the rest of the laptop market!
On the M5 Pro tier (not the base M5 tier that was released last November), the base memory is 24GB.
My M3 Pro from a few years ago for the same price had 18GB.
Apple doesn't tend to use "RAM" in their marketing materials, they usually use "memory", which appears 9 times in the press release.
Preorders open tomorrow according to the store page. You canāt order the base RAM model today, either.
>Anyway, it starts with 16GB of RAM. $400 to go from 16GB to 32GB
Interesting that this hasn't budged since the memory shortages appeared.
They sell you 1gb LPDDR5X for $25 while buying it at $5, don't worry for their margins...
Fair chance that Apple has price/purchase agreements already in place. Consumers are left to fight over the excess capacity after megabuyers get their orders filled.
> Interesting that this hasn't budged since the memory shortages appeared.
Apple has had enough war chests with the ability of buying the entirety of TSMC's new capacity years in advance in the past.
If I were to guess, Apple locked in their entire BOM and production capacity two years ago. That's something even the large players cannot replicate because they run cash-lean and have too many different SKUs, and the small players (Framework, System76, even Steam) are entirely left to the forces of the markets.
The price hasn't changed between the M4 and M5. I honestly don't know how they did it. But I had a standing order for a maxed-out M4 (128 GB RAM, 2 TB drive) and the price is the same as the M5 so I cancelled my M4 order and will pre-order the M5 MAX instead.
Well, guess I was wrong about that.
No, that's not how it works at all. They still source all their RAM from Samsung, Hynix, Micron, etc.
that is ... not at all how that works. RAM is a separate chip, that is placed on top of the substrate that holds the main dies. It is bought from normal ram manufacturers like micron. it is not "embedded in the chip" by any possible meanings of those words.
It starts at 16GB for the base M5 and 24GB for the Pro/Max. It's been like this.
on Silicon Mac's it's never called RAM, it "unified memory"
I'm honestly just glad they don't brand this as "1016 MB of unified memory". Swap and ramdisks are a thing, after all...
Insane for the "Pro" to have only 16GB of memory. My 11 year old Intel i3 laptop has 16GB of memory.
Don't these integrated ARM-based SoCs make much better use of RAM as opposed to old Intel-based boards? That's my understanding, anyway.
My wifeās 8GB MacBook Air crashed yesterday with Firefox and Find My open and nothing else because of running out of RAM, so, sort of, but theyāre not magic. (Find My was using 3GB of memory!)
If you mean it showed the out of memory dialog, that wouldn't be caused by an app using 3GB. The dialog shows up at ~48GB swap space used on an 8GB Mac, or when you're out of disk space and can't write a swap file.
So Firefox was using 5gb? There's your problem.
What page? Azure portal is notorious for leaking memory in both chrome and firefox, thatās the only tab Iāve seen using 5+ gb ram.
Itās a losing battle me trying to tell my wife to close her Firefox tabs, haha, but yes, Firefox does use a lot of ram when you have 500 tabs. Maybe Iāll get her a 64GB MacBook Pro for the premium web browsing experience she so desires!
Tabs as bookmarks, people keep falling into this trap, my wife included
I do it myself and I'm sure a lot of people on HN do too. But I've tried to embrace the "zen" of closing all tabs lately and it's been nice. If I really want to find something later I can search my history or, like you said, just bookmark it.
She shouldn't have to do anything. That's the browser's job.
The benefits are in speed not capacity.
More to do with the faster storage allowing you to swap without noticing it as much. There was this whole trend when m1 first came out of people saying it didn't matter if you got the lowest spec because the ssd was so fast it made up for the lack of ram... totally ignoring that swapping like that was destroying their drives really fast.
Apple's RAM price bumps were already insane, now they'll get worse.
Theyāre literally not changing
If they can just absorb the current ram price hike, you know they having insane margins.
It did change. They bumped $200 on the entire line. So even the 16GB version is more expensive.
I'd love to have customers like Apple. Bumps $200: "it didn't change!!!"
And no power adapter included.
You mean bumped $100. M4 MacBook Pro and M5 MacBook Pro started at $1599 with 512GB SSD.
Now it starts at $1699, a $100 bump but comes with a 1TB SSD. Previously it would have cost $1799 for the 1T SSD, so it's a $100 bump on base price but you are also getting 1TB SSD for $100 less than before.
To me, this is kind of like Telecom providers giving you bandwidth headroom that realistically should have been there for a long time, but removing the option to get a cheaper plan whether you'd otherwise pay for the upgrade or not.
Like for my last upgrade, I bit the bullet and upgraded to 1TB for the first time ever instead of base storage at Apple's absurd prices, so it's good, but if I'd not have been willing to spend money on that at all, they lifted the floor.
My cell phone plan has been increasing every year by small amounts, but my usage pattern hasn't changed, and meanwhile they've restricted HD streaming using Deep Packet Inspection or whatever, so I theoretically have a 100GB full speed cap but can't practically use more than 20gb anyway, so they're pricing the bandwidth into the contract but I can't save money by getting a lower ceiling
> I'd love to have customers like Apple. Bumps $200: "it didn't change!!!"
Try making a good product that people love?
The base storage increased as well, and the upgrade prices for RAM are the same, which is where the real issue was.
> And no power adapter included.
To be fair, ever since the advent of high power USB-C PD that really, really is not needed any more, way too many power bricks are effectively e-waste.
People already have USB-C power bricks and docks everywhere and unlike pre-USB-C generations, you can use them not just across different generations of hardware, but across vendors as well.
I doubt if that many have USB-C high power bricks unless they are upgrading from another USB-C laptop.
> unless they are upgrading from another USB-C laptop.
Which MacBooks have been for almost a decade - the 2016 MBP with Touch Bar was the first that went fully USB-C PD. Anyone who has had a MacBook in that time frame will have had at least one high power USB-C PD wall wart.
The Windows world, as usual, has been different, but even there, I'm not aware of any mainstream model being sold in the last two years without even a single PD capable port.
> It did change. They bumped $200 on the entire line.
I wonder if that would happen regardless of RAM, e.g. for tariffs etc.
The EU forbids them from including power adapters. They're still included everywhere else.
EU doesn't forbid including. The new law requires there to be an option without the adapter. If the manufacturer chooses so they can have an option with and without the adapter.
I can buy a laptop right now close to home and it comes with power adapter.
Except that it's literally not true and people are repeating it for some stupid reason, I assume you just never actually looked it up - laptops are specifically excluded from that regulation, and in fact Apple does bundle a power adapter with their laptops, just not on the cheapest models.
> in fact Apple does bundle a power adapter with their laptops, just not on the cheapest models.
Here in the UK, they no longer include the power adapter even with the top models. I just specced out a fully-loaded M5 Max Macbook Pro, 128GB RAM, 8TB storage on the Apple Store, and it doesn't include a power adapter by default.
The 140W power adapter can be added as an option to the MacBook Pro for an additional Ā£99 + VAT, or purchased separately. If you purchase separately you can of course choose a lower-power adapter for a lower price.
Now that a power adapter isn't included and you have to pay for it separately, it might make more sense to get one of the good brands of GaN power adapters instead, because they are smaller than the Apple ones for the same power, and have more ports.
>>Here in the UK, they no longer include the power adapter even with the top models
That's incredibly stupid(of apple), I'm in the UK and literally got my M4 Max MacBook Pro delivered on Friday, it came with a power adapter.
I feel like Apple pulled an Instant Pot with the M1 MacBook Pro. I still haven't had a single situation where I felt like spending more money would improve my experience. The battery is wearing out a bit, but it started out life with so much runtime that losing a few hours doesn't seem to matter.
> The battery is wearing out a bit, but it started out life with so much runtime that losing a few hours doesn't seem to matter.
this is my exact opposite experience. my M3 Max from 2 years ago now has <2hrs battery life at best. wondering if any experts here can help me figure out what is going on? what should i be expecting?
As others have said, keep the battery in the 80%-30% range. Use the `batt` CLI tool to hard limit your max charge to 80%. Sadly, if you're already down to <2hrs, this might not make sense for you. Also prevent it being exposed to very hot or cold temps (even when not in use)
I type this from an M3 Max 2023 MBP that still has 98% battery health. But admittedly it's only gone through 102 charge cycles in ~2 years.
(use `pmset -g rawbatt` to get cycle count or `system_profiler SPPowerDataType | grep -A3 'Health'` to get health and cycles)
Either your battery was defective or something is using all your battery. Even my 2018 Intel MacBook still lasts 3+ hours on a charge.
Apple will replace the battery for $249 if you choose to. https://support.apple.com/mac-laptops/repair?services=servic...
What is your maximum capacity in Settings > Battery Health? What processes are running with significant CPU? What's the typical temperature of the laptop according to a stats app? (Temperature is a good proxy for general energy use.)
I'm typing this on an M3 Max; its max battery capacity is 88%. I've got some things running (laptop average temp is 50-55C, fans off), screen is half brightness, and it's projected to go from 90% to 0% in five hours. I don't usually baby it enough to test this, but 8-10 hours should be achievable.
My M3 Max can burn through battery much faster than my M1 Max ever could.
And some apps are really inefficient. New Codex app drains my battery. If you are using Codex I recommend minimizing it, since itās the UI that uses most power.
A couple weeks ago I was working remote and didn't bring a power adapter, and I realized a couple hours in that my battery was getting kind of low. I clicked on the battery icon and got a list of what was using a lot of power: 1 was an hour long video chat using Google Meet, the other was Claude desktop (which I hadn't used at all that morning).
What in the world is an idle Claude Desktop doing that uses so much power?
Charge habits with batteries make a huge difference. If your use pattern is that once per day, you take the device from 100% to 10%, you put a lot more wear on the battery than if it kind of hovers in the 30%-80% range for example, or if it just hangs out nearish top-of-charge all day when you're at your desk.
Hot take: people should get used to, and expect to, replace device batteries 1 or 2 times during the device lifetime. They're the main limiting factor on portable device longevity, and engineers make all kinds of design tradeoffs just to make that 1 battery that the device ships with last long enough to not annoy users. If we could get people used to taking their device in for a battery once every couple of years, we could dramatically reduce device waste, and also unlock functionality that's hidden behind battery-preserving mechanisms.
BatFi is a macOS application which will prevent your battery from charging to over 80% by default. macOS does have a version of this built-in but itās āintelligent chargingā I donāt really trust, and Iād rather just have a hard 80% limit except when I override that.
Also check which apps use the energy.
I set Claude loose on my computer and said āwhy is my battery life so bad?ā and it found an always-running audio subsystem kernel extension (Parrot) which didnāt need to be there and was preventing the CPU from going into low-power states. My battery life got noticeably better when I deleted it.
Iām not even sure how it got installed, possibly when I installed Zoom for an interview once but I donāt know. Point is, at least in one case, AI can help track down battery hogs.
M1 pro MacBook pro here as well. Just today I was thinking I have no need to upgrade until M7 and by then maybe even MacBook Air would do. Especially since I will have my home server (dgx spark) available for anything serious anyway. So excited for the Mac studio configs though. M5 ultra 1TB would be a huge leap for serious home server builders.
I use an M1 for personal development an an M4 for work. I'm a typical dev. I don't feel any difference.
I just bought this model in the past year for $600 and it still feels like a great bargain.
Same. It looks like battery replacement from ifixit is not too difficult, so I plan to do that when the time comes.
Incidentally, I just switched to Asahi Linux, but that was for software quality and openness reasons, rather than anything to do with performance.
How's Asahi treating you? If I upgrade from my m1max, I was going to try it out
I wish this sort of thing was encouraged in the modern capitalist technology space.
Unfortunately, number always must go up (and the rate at which the number goes up, also must go up).
You can very easily replace the battery yourself for less than $100 USD too if it ever becomes enough of an issue that you feel you actually need to do something about it. My M1 Max is at about 88% battery health, but it still gets 4X-6X longer on battery (At full performance too boot) compared to my old PoS Razer laptop, so I likely won't be replacing my battery any time soon.
The hardware looks amazing! Too bad they will ship with Tahoe installed. Iām not upgrading until I see in which direction the next Mac OS release goes
This. I have been a big (and loud) fan of M-series hardware from the beginning, but if Apple is going to keep making their software worse, I will find myself lingering on older generations that run Asahi Linux or going back to a traditional x86_64 laptop instead of buying into new generations.
I've upgraded to Tahoe at 26.2, zero complaints from my side. Haven't had any runaway memory leaks or similar that were reported.
Same here. I know some people are unhappy with some of the UX tweaks but honestly I don't notice much of it. The whole liquid glass thing is a bit gimmicky. Other than that, I don't see much difference. The rounded corners on windows are a bit silly. But I don't spend a lot of time fiddling with windows. Most of my windows are maximized (not full screen). I'm sure there are other issues people dislike that I just haven't noticed.
I use my laptop for development. I don't actually use most of the built in applications. My browser is Firefox, I use codex, vs code, intellij, iterm2, etc. Most of that works just fine just as it did on previous versions of the OS. I actually on purpose keep my tool chains portable as I like to have the option to switch back to Linux when I want to. I've done that a few times. I come back for the hardware, not the OS.
In my experience, if you don't like Apple's OS changes that is unfortunate but they don't seem to generally respond to a lot of the criticism. Your choices are to get further and further out of date, switch to something else, or just swallow your pride. Been there done that. Windows is a "Hell No" for me at this point. I'll take the UX, with all the pastel colors that came and went and all the other crap that got unleashed on macs over the last ten years. Definitely a case of the grass not being greener on Windows. Even with the tele tubby default desktop in XP back in the day.
I can deal with Linux (and use that on and off on one of my laptops). However, that just doesn't run that well on mac hardware. And any other hardware seems like a big downgrade to me. Both Windows and Linux are arguably a lot worse in terms of UX (or lack thereof). Linux you can tweak. And you kind of have to. But it just never adds up to consistent and delightful. Windows, well, at this point liking that is probably a form of Stockholm Syndrome. If that doesn't bother you, good for you.
So, Mac OS it is for me as everything else is worse. I've in the past deferred updates to new versions of Mac OS as well. Generally you can do that for a while but eventually it becomes annoying when things like homebrew and other development toys start assuming you run something more recent. And of course for security reasons you might just not drag your feet too long. Just my personal, pragmatic take.
Closing Tabs in Safari till takes more than a second though. And if you hold Cmd-W to close all of them it just completely locks up and crashes. Still not fixed since the release of Safari 26.
Literally unusable
Never had this problem, been on Tahoe since it released. My safari tabs are buttery, silken smooth.
Works fine for me. I wonder if you have some extension or script on one of the sites you use slowing down the tab closure.
This sounds like swap needing to be swapped in and then released. Check your memory usage.
Iāve been running the macOS 26.4 beta and have none of these issues.
I will say that 26.4 beta 2 was the first time I've regretting using betas since Sonoma beta 2. The Sonoma beta ruined the firmware on my machine and Apple had to replace the logic board; the latest Tahoe beta broke all networking on my machine and I had to erase the installation to fix everything. I've since dropped off the beta train for the time being.
I already left the beta train on my iPhone because I had too many issues getting my grocery apps to allow me to place orders without going to my laptop and doing it in a web browser.
I'm on an M4 Pro MacBook-- basically the fastest computer you could buy from Apple before today-- and opening/closing the tab sidebar in Safari on Tahoe takes multiple seconds, even if I have only 4-6 tabs open, and seems to drop to 5 FPS. It's comically bad.
It's so bad I switched back to Chrome. I had thought Chrome had a major battery life penalty compared to Safari on Macs, but I checked more up-to-date info and apparently that's outdated.
The next macOS will be touch screen centric with elements getting bigger when you're close to touching them, rumors say. That being said, I run Tahoe and it works perfectly fine to me, I am not sure what issues people have with it. Sure, some corner radii aren't exactly the same but I honestly couldn't give less of a shit as long as it runs the programs I need.
Safari routinely using 20+ Gb of memory with a handful of tabs open. Safari tabs refusing to close. Unresponsive System Settings window. Random application freezes and crashes, Apple Music not playing music. This is on a 32Gb M1 Max. My M1 Air on Sequoia doesn't experience any of these issues, even if it has half the unified memory.
I never had any of those issues, but then again I don't use Safari or other Apple apps like music.
The fact that avoiding Apple-made software provides an overall better user experience is very telling
Not necessarily, because I never used Apple apps, it's not like I'm avoiding them now because they're ostensibly buggy (as others don't seem to have the same issues in this thread).
I read a rumor about it being ātouch friendly instead of touch 1stā.
I moved away from mac because of the OS and couldn't be happier. The hardware may be great but non-Apple hardware is fine too, and Linux is significantly better experience than MacOS these days.
Same. Im waiting for the next macOS release. Tahoe is ugly as hell
Yeah this is a real issue with these new Macs. I would wait until macOS 27 to see the direction Apple takes.
Hopefully less `border-radius`.
Just yesterday, my colleague's mac Time Machine couldn't recover backup and they had to reinstall everything.
But I think this predates Tahoe.
Silent corruption has been a feature of Time Machine for the last 19 years. But haven't you seen the new glass effects, isn't it cool?
On M4 Max 128GB we're seeing ~100 tok/s generation on a 30B parameter model in our from scratch inference engine. Very curious what the "4x faster LLM prompt processing" translates to in practice. Smallish, local 30B-70B inference is genuinely usable territory for real dev workflows, not just demos. Will require staying plugged in though.
The memory bandwith on M4 Max is 546 GB/s, M5 Max is 614GB/s, so not a huge jump.
The new tensor cores, sorry, "Neural Accelerator" only really help with prompt preprocessing aka prefill, and not with token generation. Token generation is memory bound.
Hopefully the Ultra version (if it exists) has a bigger jump in memory bandwidth and maximum RAM.
Do any frameworks manage to use the neural engine cores for that?
Most stuff ends up running Metal -> GPU I thought
It's referring to the neural cores(for matrix mul) in the GPU itself, not the NPU.
https://creativestrategies.com/research/m5-apple-silicon-its...
https://github.com/maderix/ANE
What about real workloads? Because as context gets larger, these local LLMs aproxiate the useless end of the spectrum with regards to t/s.
The thing about context/KV cache is that you can swap it out efficiently, which you can't with the activations because they're rewritten for every token. It will slow down as context grows (decode is often compute-limited when context is large) but it will run.
I strongly agree. People see local "GPT-4 level" responses, and get excited, which I totally get. But how quickly is the fall-off as the context size grows? Because if it cannot hold and reference a single source-code file in its context, the efficiency will absolutely crater.
That's actually the biggest growth area in LLMs, it is no longer about smart, it is about context windows (usable ones, note spec-sheet hypotheticals). Smart enough is mostly solved, combating larger problems is slowly improving with every major release (but there is no ceiling).
That should be covered by the harness rather than the LLM itself, no? Compaction and summarization should be able to allow the LLM to still run smoothly even on large contexts.
Sometimes it really needs a lot of data to work.
4x faster is about token prefill, i.e. the time to first token. It should be on par with DGX Spark there while being slightly faster than M4 for token generation. I.e. when you have long context, you don't need to wait 15 minutes, only 4 minutes.
The marketing subterfugue might be about this exactly, technically prompt processing means the prefill phase of inference. So prompt goes in 4x as fast but generates tokens slower.
This seems even likely as the memory bandwidth hasn't increased enough for those kinds of speedups, and I guess prefill is more likely to be compute-bound (vs mem bw bound).
So prompt goes in 4x as fast but generates tokens slower.
I'd take that tradeoff. On my M3 Ultra, the inference is surprisingly fast, but the prompt processing speed makes it painful except as a fallback or experimentation, especially with agentic coding tools.
I find time to first token more important then tok/s generally as these models wait an ungodly amount of time before streaming results. It looks like the claims are true based on M5: https://www.macstories.net/stories/ipad-pro-m5-neural-benchm... so this might work great.
100 tok/s sounds pretty good. What do you get with 70B? With 128GB, you need quantization to fit 70B model, right?
Wondering if local LLM (for coding) is a realistic option, otherwise I wouldn't have to max out the RAM.
I run gpt-oss 120b model on ollama (the model is about 65 GB on disk) with 128k context size (the model is super optimized and only uses 4.8 GB of additional RAM for KV cache at this context size) on M4 Max 128 GB RAM Mac Studio and I get 65 tokens/s.
Have you tried the dense(27B,9B) Qwen3.5 models? Or any diffusion models (Flux Klein, Zimage)? I'm trying to gauge how much of a perf boost I'd get upgrading from an m3 pro.
For reference:
Whoah, both the Pro and Max CPUs feature 18 cores. This hasn't happened since M1 Pro/Max. This is a surprise.
Also, the mix of cores have changed drastically.
- 6 "Super cores"
- 12 "Performance cores"
I'm guessing these are just renamed performance and efficiency cores from previous generations.
This is a massive change from the M4 Max:
- 12 performance cores
- 4 efficiency cores
This seems like a downgrade (in core config but may not be in actual MT) assuming super = performance and performance = efficiency cores.
I don't think the "new" Performance cores are just "renamed" "E" / "Efficiency" cores; Apple has retroactively renamed the baseline M5 nomenclature to say it has "10-core CPU with 4 super cores and 6 efficiency cores"; so they're clearly keeping the "efficiency cores" nomenclature around.
I think this is a new design, with Apple having three tiers of cores now, similar to what Qualcomm has been doing for a while.
I think how it breaks down is:
- "Super" are the old "P" cores, and the top tier cores now
- "Performance" cores are a new tier and seen for the first time here, slotting between "old" P and E in performance
- "Efficiency" / "E" are still going to be around; but maybe not in desktop/Pro/Max anymore.
Interesting. This is clearly a big CPU change if so. I wonder why no E cores. Iām sure E cores would be more efficient at OS tasks than the new performance cores.
For example, 6 super, 8 performance, and 4 efficiency.
Another commenter stated the P cores can be scaled down to be E cores dynamically, so why not?
I wonder if they'll get to good enough scaling from E to Super where they don't really need to distinguish anymore?
P cores would take up more die space.
Intel is totally gonna steal that. They're catching so much flak for their "efficiency cores" I'm surprised they haven't done a rebrand yet
I think super cores are a new type/tier of core, not a rename of performance.
The base M5 has super/efficiency cores.
The Pro and Max have super/performance cores.
I was looking into this. The M5 performance cores can be scaled down to match efficiency cores in performance and power usage.
I believe they lower the clock speed, limit how much work is done in parallel on each core, and limit how aggressive the speculative execution is so less work is wasted.
So they renamed performance to mean efficiency and are now using super in place of performance?
Super is old "performance" core:
> The industry-leading super core was first introduced as performance cores in M5, which also adopts the super core name for all M5-based products
But new "performance" is claimed to be new design (= not just overclocked efficiency core from M5?):
> M5 Pro and M5 Max also introduce an all-new performance core that is optimized to deliver greater power-efficient, multithreaded performance for pro workloads.
quotes from https://www.apple.com/newsroom/2026/03/apple-debuts-m5-pro-a...
1.35x speed up in single core versus M3 Max. Insane. Everyone else has failed to bump single core performance in years. Where are these single core gains coming from?
The most interesting change for the M5 Pro and Max is Apple moving to a bonded chiplet strategy from a single monolithic die.
> The tech giant says the chips are engineered around its new Fusion Architecture, an advanced design that merges two dies into a single, high-performance system on a chip (SoC), which includes a powerful CPU, scalable GPU, Media Engine, unified memory controller, Neural Engine, and Thunderbolt 5 capabilities.
https://techcrunch.com/2026/03/03/apple-unveils-m5-pro-and-m...
They also replaced the efficiency cores on the CPU chiplet with a new higher performance design.
> The CPU now features six āsuper cores,ā which is Appleās term for its highest-performance cores, alongside 12 all-new performance cores. Collectively, the CPU boosts performance by up to 30% for pro workloads.
I have a fairly maxed out M2 Ultra (24 cores, 192GB RAM), and still cannot get this machine to choke on anything.
I have not once felt the need to upgrade in years, and thatās with doing pretty demanding 3D and LLM work.
If thereās anything this past three years has taught me, itās that modern cpus can performantly do every task except for streaming text over the internet.
I had to upgrade the CPU in a 10-year old machine (from i5 to i7) to have decently -working javascript on websites. Every other piece of software worked fine, though.
I'm pretty sure that's just LLMs tendency to replicate bad React patterns.
I've found current-generation Macs so capable that I've switched to using a Macbook Air. Would strongly recommend - it's still a powerful machine and it's significantly lighter and cheaper.
I have a powerful older Mac that doesnāt really āchokeā on anything, but I could always use more speed.
The high memory Macs have been great for being able to run LLMs, but the prompt processing has always been on the slow side. The new AI acceleration in these should help with that.
There are also workloads like compiling code where Iāll take all the extra speed I can get. Every little bit of reduced cycle time helps me finish earlier in the day.
And then thereās gaming. I donāt game much, but the M1 and M2 era Apple Silicon feels sluggish relative to what I have on the nVidia side.
my m4max runs fan at high speed! just have few electron apps open..
> It definitely chokes with larger models that can fit the 192GB of RAM
M5 Max maxes out at 128GB, so that will have to wait for the eventual M5 Ultra anyways.
AI video generation can fairly easily choke anything that's not NVIDIA's flagship model. Even the latest local image gen models are so large that they can be frustratingly slow with non-optimal hardware even if they fit in the VRAM. IIRC when I had an M2, it was about 4x slower at running the venerable Stable Diffusion (and SDXL) than my meager RTX 3060.
I do not do anything with AI Video, but I imagine running this locally would be a hog on a Mac - especially if not optimised for Metal.
Sounds pretty beefy. What kind of local LLM is that thing capable of running? Does it open up real alternatives to cloud providers like OpenAI and Claude, or are the local models this hardware is capable of running still pretty far behind?
Yeah I have an M1 Max, and I really want to upgrade, but thereās no reason to.
You might have confused Hacker News with your e-mail inbox again. This is an Apple press release, directed to everybody in the world who might be interested in a new computer or their first computer.
Whatās with the attitude? My machine is aging like a fine wine, Iām acknowledging how resilient their custom silicon is despite the world demanding more and more compute.
It was a joke, should have put a smiley face. But every thread on a new Apple product here on HN have the same "why should I upgrade" comment, forgetting that there are people who might have very old devices they want to upgrade, or they might want to switch from Windows/Android to Apple.
Even if a new device is a small upgrade from last year's model, it can be a giant upgrade for other people.
Are you one of the folks thinking of upgrading? If so, from what generation? What makes you excited? Isn't this a more interesting way to have the conversation?
Got it. I guess it feels unfair to gaslight people who are celebrating not needing upgrades, anecdotally sharing their experiences - because some people just need a new computer for xyz reason in time.
Honest question. Is it possible to install an earlier version of macOS on these machines? Liquid glass looks so.. unprofessional to my eyes. And I hear it's also unstable.
That's a big part of what's keeping me from upgrading. Every time I look at my wife's iPhone I'm dumbfounded by just how bad the liquid glass looks.
It's the first time I've ever been so repulsed by a design that I actively avoid it just... out of sheer preference.
I have a base M5 since last year. You cannot, no. It is literally impossible. Do with that what you will.
You barely see any liquid glass on Tahoe. I keep my dock hidden and it's just the icons mostly which aren't that different than before.
Same here. Not really understanding the complaints for macOS. I think the addition of icons in the context and menus is worse than glass.
accessibility settings can turn off some (but not all) of the garish animations, transparencies, etc.
It does look terrible, but I haven't found it to be unstable, personally
Yes. This page has several ways to get older macOS versions: https://support.apple.com/en-us/102662, but the earliest macOS version you can use on Apple Silicon is macOS 11.
If you move your home directory to a different disk partition, you can even share it between two different macOS versions!
these Macs can't go below Tahoe. People on Mac Rumours were complaining about M5 MacBooks unable to install Sequoia, so it's safe to assume Pro/Max chips will be the same.
This. You canāt downgrade below the version the device ships with (a forked build of the current version at time of mass production)
"The new MacBook Pro gets up to 24 hours of battery life, giving Intel-based upgraders up to 13 additional hours"
I have a Intel-based 2019 Macbook Pro still and I have NEVER in its lifetime gotten even half of what they are claiming here. These days if I run it from battery I might get 90 mins.
That said I had a maxed out Macbook Pro M4 Max on order but just cancelled it right now and will get this new M5 Max one for basically the same price. Once I saw that they didn't up the price of memory (I don't know how it doesn't affect them) I canceled my order.
I had intel MacBook Pro. It is a NIGHT and DAY difference. I wish I didnāt get the 16gb of memory though. It is ok, but running 5-10 cursor ai agents at the same time does start to choke the memory. Battery is absolutely amazing! And the best part - it stays cold!! No more irritated from heat fingers when using touchpad.
They are at least nice for comparing it with the max of the Intel. That should really say gives them up to 22 additional hours given the wear on their batteries lol
One thing I haven't seen mentioned in this thread is M5 Pro now supporting 64GB ram . I believe prior gens you had to go Max to get 64. m5 Pro 64GB is $3000 meanwhile to upgrade ram on the max you need the 40 gpu core variant with 64GB is $4300. $1300 dollar mark up for twice the gpu compute and 50% higher mem bandwidth isn't great value imo.
Anyone who cares about value isnāt getting a non-base model Mac. They are buying the silver shiny thing or their company is paying.
For example, grab yourself an Omen Transcend 14, spec it to 64GB RAM and the RTX 5070. Youāre under $2000 and getting better graphics performance for anything that isnāt AI, and youāve got an upgradable 1TB SSD and removable WiFi card.
Youāre also getting an OLED screen which most people would prefer.
This model in particular Iāve chosen because itās just as quiet as the M4 MacBook Pro models within 3dB during high intensity usage and gets very similar battery life, actually better battery life than the M4 Pro/Max models for light tasks.
Interesting that they're showing VFX/CG software (Autodesk MAYA and Foundry Nuke) so prominently - obviously people using "Pro" machines are the target audience for this, but both of those apps (any many others in the industry) use Qt for the interface, rather than being totally platform-native.
Contrary to HN popular belief, there are neither incentives nor benefits to building native ui apps, for neither consumer nor professional apps. The exception is apps that only make sense on a single platform, such as window management and other deep integration. On iOS/macos you have a segment of indie/smaller apps that capture a niche market of powerusers for things like productivity apps. But the point is it makes no sense for anything from Slack, VSCode, Maya, DaVinci Resolve, and so on, to build native UIs. Even if they wanted to build and maintained 3 versions, advanced features arenāt always available in these frameworks. In the case of Windows, even MS has given up on their own tech, and have opted to launch webview based apps. Apple is slightly more principled.
Qt delegates to native UI in a lot of cases. I think a lot of people who rail against native UI fail to delineate between native UI and first party frameworks. Using third party frameworks, even cross platform ones, does not mean you lose out on native UI elements.
I am not an apple framework expert, but some things in apple ecosystem are nice.
CoreImage - GPU accelerated image processing out of the box;
ML/GPU frameworks - you can get built-in, on device's GPU running ML algorithms or do computations on GPU;
Accelerate - CPU vector computations;
Doing such things probably will force you to have platform specific implementations anyway. Though as you said - makes sense only in some niches.
Strong disagree. I think Microsoftās decision to wrap web apps for the desktop is one of the stupidest they have ever made. It provides poor user experience, uses more battery power and needs more memory and CPU to be performant and creates inconsistencies and wierd errors compared to native apps.
The increased adoption of webviews has resulted in a death by a thousand cuts effect on Windows 11 performance. The speed bump that comes from going from an up to date Windows 11 install to a up to date Windows 10 install on the same machine is stunningā¦ W10 is much more snappy in every regard despite being nearly identical functionally speaking.
I wonāt try to claim that Electron and friends have no place is software development but we absolutely should be pushing back harder against stuffing it everywhere it possibly can be.
> but we absolutely should be pushing back
Every modern desktop uses webviews in some capacity. macOS renders many apps with webviews, GNOME uses gjs to script half the desktop. The time to push back was 10-20 years ago, it's too late to revert now.
Theyāre still fairly uncommon in macOS, mostly being used in places related to cloud service settings. SwiftUI and Catalyst (iOS bridge) are both much more common than webviews, and AppKit remains ubiquitous.
Meanwhile on Windows major features like the Start menu are written in React.
Worth noting that WebKit webviews also tend to be more lightweight than their Chromium brethren.
Similar thoughts with first image of Capture One, when apple bought Pixelmator/Photomator a year ago.
I think I read somewhere long time ago that Capture One is also using Qt for GUI, though cannot find this anymore, so probably not true.
$200 price bump across the board. The cheapest 16" is now $2699 and 14" Pro $2199. I think it's a fair price considering M2Pro 14" was $1999 (though it was discounted) only had 512GB and 16GB RAM.
It's not $200 across the board. M4 MacBook Pro and M5 MacBook Pro started at $1599 with 512GB SSD.
Now it starts at $1699, a $100 bump but comes with a 1TB SSD. Previously it would have cost $1799 for the 1T SSD, so it's a $100 bump on base price but you are also getting 1TB SDD for $100 less than before.
To clarify, I meant, model with Pro chip, not just Macbook Pro name.
For example, up until MacBookPro M2, MacBookPro M2 came with M2 Pro chip.
However, starting with M3, Apple lowered the MacBookPro MSRP to $1599, but its base configuration was downgraded to M3 chip from M3 Pro. To get the M3 Pro, you had to pay $1999. There's substantial performance between the two.
Same with M4. To get the M4 Pro chip, you had to pay $1999.
Now to get M5 Pro chip, it's $2199. Still a good value, but just saying it's a deviation from the trend.
With how much more expensive SSDs and RAM are recently, Iād say this is a great deal.
I checked the fine print on the product website: by āup to 4x faster LLM prompt processing,ā theyāre specifically referring to time to first token. So itās not about token generation rate (tokens per second).
Yes. This is known. They added neural accelerators, aka Tensor core equivalent, in the GPU. This will make prompt processing competitive vs similar class GPUs.
It would probably be worth finding a more friendly way to market this, but it's a reasonable / accurate way to say it.
The prompt processing sped up.
Not the output generation.
M4 was notoriously slow at this compared to DGX etc.
Nano-texture is worth the upgrade if you are on a macbookpro whatever M<cpu> and dont have it.
For those of us with astigmatism it's really night and day experience.
I was considering it but got cold feet when I've been told that you could damage it when cleaning it. When I open/close my laptop I leave a ton of finger prints. I'm not too good with delicate hardware stuff.
Why are you touching the screen when you open/close your laptop??? Do you close your car doors with the window?
My screen gets fingerprints from the keyboard, maybe that's what he meant.
Nice starting storage bump
It's not exactly a bump if they raise prices at the same time, though with the RAM situation I'm not mad.
Well 1TB MacBook Pro used to cost $1799, now 1TB is the base model and costs $1699, so it's actually a $100 price drop for 1TB storage.
Not if you compare Macbook Pro with Pro CPUs.
> M5 Pro supports up to 64GB of unified memory with up to 307GB/s of memory bandwidth, while M5 Max supports up to 128GB of unified memory with up to 614GB/s of memory bandwidth.
This is the important statement. 614GB/s is quite decent, however a NVIDIA RTX 5090 already offers 1,792 GB/s (roughly 3x) of memory bandwidth, for comparison.
You're right a $3600 graphics card is worse than a $2600 laptop; but from my perspectives they're very different products. Not least of all because even at $3600 for a RTX 5090 you still have the whole rest of the computer left to purchase.
Max version with the 614GB/s is a $3599 laptop
The RTX 5090 only has 32gb of VRAM. So the tradeoff is NVIDIA is for blazing speed in a tiny memory pool, but Apple Silicon has a larger memory pool at moderate speed.
Or, there's the DGX Spark, which effectively neutralizes both of these trade-offs, and is the same price as the RTX 5090.
For reference, DGX Spark is at 273 GB/s
It's not 5090 performance though.
Nothing stops you from plugging in a 5090. Nvidia ships ARM64 GPU drivers.
So, what were we talking about even then in the thread?
> NVIDIA RTX 5090 already offers 1,792 GB/s
You can buy two m5 pro base model for the same price as a single 5090...
That's a fun comparison, but can you run those 2 m5 pros in parallel to accomplish 2x the work? Otherwise, you just told me you can buy 2 toyota corollas for the price of 1 F-150 while trying to convince me you can haul your boat behind both corollas at the same time.
You can also buy a 64gb mini, save $1k and do more work than what you could do with a single 5090.
In Europe I can get a 128gb mac studio m4 max for 300 euros more than a 5090 (for which you still need to buy a power supply, motherboard, cpu , &c.)
But the inference on the mac studio m4 max will be slower than on the 5090, even though you can load larger models.
All I'm saying is that the comparison doesn't make sense. The 5090 is faster on a small subset of tasks if attached to a computer which ends up being 3x the price of a m5 machine that fit the same model or the same price as a machine that fits models 5x bigger
So you're saying that buying 2 Corollas for the cost of 1 Ferrari engine would be better? Even though the Ferrari engine is much more powerful, it's useless without the rest of the car.
I imagine the upcoming M5 Ultra will be competitive in this regard. The M3 Ultra already has 819GB/s and it's two generations behind.
Was hoping to see Apple break the 128GB barrier in a laptop that they previously set, though 128GB is still pretty sweet for local LLM inference on consumer hardware. My 128GB M3 Max is still shredding tokens pretty well (with that annoying slow initial prompt processing), so no major complaints there. I guess the question is, given access to the same amount of RAM, does the M5 really do an order-of-magnitude better than 128GB on a M3 or M4?
I don't see it mentioned much, but the most exciting thing to me is that they're shipping their own WiFi chip in it, which leads me to be hopeful that they'll eventually get around to shipping a cell modem so I don't have to tether to my phone constantly. Still no new colours unfortunately. I think those are the two things that would/will be exciting in the future. Give me a green 5g+ capable MBP and I'll be happy. I'm so deeply bored of the drab grey and darker grey versions; we can have tattoos at work now, give me a different colour laptop for christ's sake
I donāt know if theyāll ever do that. Colors add another dimension, so you either need to have more stock on hand or do more custom models. Right now, the profit margins on all upgrades is huge.
Phones have less configurability, they sell more, and colors seem more important.
Why doesn't this excite me anymore?
Because the M1 was too good, a qualitative leap over previous Macs and really every other laptop and even some desktops back in 2020. Now, Apple Silicon is just iterative.
Me either. I guess it's just fatigue, at least for me. I also don't really get that excited by new LLM releases either. Not to say the tech isn't impressive, but I guess all the hype has me inured.
For me going way back, it was exciting when I had to save a bit (but not too much!) for a new 512 DIMM, and when I opened the box and smelled the chip smell, put it in always worried I was going to fuck it up, and then computer literally felt faster that next boot...that was pretty fun!! Now it's like oh great $5k for a slab of stone that can do pretty much anything, neat. I still think computers are cool, just not particularly exciting.
Because it's the same shit every year for the past 5 years with the M line. 2010 to 2015 was a major improvement, 2015 to 2020 was a major improvement, now they pretty much solved the computer/laptop problem for 99% of people. I'm on a 16gb m1 air, I see absolutely no reason to update.
Watch this video if you have time: https://youtu.be/6AtTk3XoQVs
TL;DW: 2010s intel mac era laptops have seen at very best 35% single core CPU performance over in 5 years time! This happens almost every year now with M line macs.
Rant:
Retina macs were great and had great form factor over unibody macs. Touch-bar macs in the mid 2010s was IMHO a disaster. Terrible keyboard, poorer thermal capacity, missing essential ports, adapters galore.
But when it comes to performance - early 2010s macbooks with dedicated gpus had serious overheating issues.
Retina macbooks were decent, both form factor and performance.
Touch-bar macs were totally abysmal, all performance gains over previous generations was all through pumping more heat. CPUs constantly pegged at 90C+, cannot have laptop on your lap, Apple planning and delaying release schedules around intel fumbling their tik/tok cycles (as far as i remember some macs did not get any improvements for 2 years+ if not way more). Upgrades sometimes were total jokes, because of thermal throttling there was no point to put more hardware than it could work with. From reviews buying higher level cpu sometimes didnāt give noticeable real life gains because, again, thermal throttling kicking in instantly. 2020 intel macbook pro has fans spinning almost all the time. Having a remote call - your battery is dead in 2h max (essentially 1% per 1min).
M1 mac gave insane perceived performance boost - no noticeable throttling. Macbook airs are fully passively cooled, never heard M Macbook pro with fans screeching.
Also real full work day battery doing real work without power adapter at full performance. Cool to touch most of the time.
I made homework for a job in 2020 on a 2013 personal macbook. Apart from memory footprint - I could not feel noticeable difference on development experience. Editing images was frustrating on both. With M macs - its silent, smooth fast.
Number of parallel cores matching best intel cpus on base models, GPU blowing any mobile gpu in price range out of the water with thermal capacity to peg it 100% no problem. Unified memory for those GPUs to do what you could only imagined doing on GPUs that cost 3 times more than the macbook.
Itās a such excellent architecture that yeah - itās āboringā you can nitpick about M69 Ultra Pro Max performance, but take a base MBP of any M line and it blows almost any laptop out of the water, even to this day.
Because it was always a vapid distraction from life.
Because a Macbook M1 is fast enough to do anything and most people aren't running local LLMs
It excites me, since I am finally going to replace my 2019 Intel MacBook Pro!
Hot take - Local LLM computing will move to stationary, always on devices (Mac mini & studio). Developers and users will move to lighter, portable devices to interface with their long running agent workers (MacBook Airs & iPads).
So is this a minimal upgrade before the M6 Macbook Pros w/ OLED & a redesign later this year?
It doesn't even look like they added cellular as an option with their own C1X chip (getting around the licensing / cost issues since it's their own chip now).
I wouldn't assume those are coming this year.
Everybody says they are, with the main point being they can get the M6 Pros onto TSMC's 2nm node and save 3nm capacity for iPhones.
Yea, I think it is worth waiting for M6 just for OLED alone.
OLED sounds great, but I am worried about burn in. MacBook screens are a bit more static and on longer than iPads and iPhones.
Ugh, more "AI" hype. How useful are the cited hardware features for NON-"AI" processing?
Note: no power adapter included.
Not true everywhere. Only where required by law, so complain to your government.
For those who don't already know, you can get a lot of PC gaming performance out of these machines using Sikarugir. You can install all of Steam via winetricks and go from there, or launch DRM-free games directly.
https://github.com/Sikarugir-App/Sikarugir
Can someone comment on the new dual die thing theyāre promoting for how they make the M5 Pro and M5 Max chips?
How is that different from the silicon interposer they were using before?
The big change is the two dies donāt have to fabbed next to each other in a single wafer, which is fantastic for costs and yields. But would this affect the interconnect speed somehow?
How would the two be wired together?
Could this mean the Ultra comes back in M6 since it would be easier to fab?
the new dual die thing theyāre promoting for how they make the M5 Pro and M5 Max chips?
It's chiplets just like GB10, Strix Halo, etc. One die has the CPU and the other die has the GPU.
How is that different from the silicon [bridge] they were using before?
It's probably similar.
the two dies donāt have to fabbed next to each other
They never were; this is a widespread misunderstanding.
But would this affect the interconnect speed somehow?
Apple never documented the internal interconnect for the M4 Pro/Max and now they don't document it for the M5 Pro/Max so we don't know. It's probably better to read reviews and avoid theorycrafting and backseat driving.
Curious about that as well.
They seem to market it as a technological advancement, which it is, but rather than being excited im actually worried about hidden latencies that could come with that approach. Have you found any interesting info on that yet?
The question is when Apple Laptops are going to be able to run LLMs with a performance comparable to what the AI companies are offering?
Never - data centers will always offer more power if you only care about raw inference speed. HOWEVER I think that we'll reach the 'good enough' bar super soon. In 2-3 years I expect apple macs to be able to run a model as 'good' as Claude 4.6 sonnet at 90% of the inference speed we're used to from a cloud API.
Yes, I'm sure by then there will be better models on offer via cloud providers, but idk if I'll even care. I'm not doing science / research or complex mathematical proofs, I just want a model good enough to vibe code personal projects for fun. So I think at that point I'll stop being a OpenAI / Anthropic customer.
I bought an M4 and don't think I can justify upgrading so soon. Certainly has some great improvements.
I bought an M1 Max with 64G RAM a long time ago, and am perfectly happy with it. I thought about getting a refurbed M4 Max when the M5 Max comes out, and decided my next computer will be a Dell Rugged, just because I want a Rugged laptop for auto diag stuff, and I thought I could kill two birds with one stone and get something with an NVIDIA card for learning CUDA. I've been using the Rugged basically nonstop while the M1 Max gathers dust. I think I may be done with Apple laptops now, a rugged laptop running linux is so nice. I love the keyboard, I love the upgradability, the OS is snappy, and I can use so much nice software. I added a 4TB SSD and now have 7 auto diag virtual machines with volvo, VAG, BMW software, and keep the host linux to myself. I have not had so much fun with a computer in a very long time. Both battery bays are full and my mac mini takes care of blue bubbles and is a home server for inventory management and backups. If for some reason I miss the Apple Experience, I can always RDP into the mini. Keeping a mini under the desk at home and a rugged laptop outside the home is my new sweet spot.
Still rocking M1 air, still a great machine and Im still happy. :-)
M1 Pro Max has held up surprisingly well, and Iām finding justifying the M5 Max over the M5 Pro quite hard to do.
This is what I upgraded from. Adored it - but wanted the 128gb.
Does it still come with a measly 1 year warranty?
Is the notch gone?
Literally the only thing that will get me to upgrade. My M1 MacBook Pro is a beast and I've felt no need to replace it.
Shout out to LM Studio being featured in one of the product shots!
I just bought a M5 Macbook Pro 2 weeks ago. Thinking of returning it and getting a M5 Pro with the same configuration but only $200 more. How should I compare M5 vs M5 Pro?
You'll get slightly more performance and ever so slightly less battery life. I'd do it
Thanks for the advice! Gonna do it.
It doesn't feel like much has changed from the previous gen? Just a new chip + memory?
What did you expect?
I thought a Studio would be my local LLM machine 2026, but this is $2000+ for the 126gb option - not for me. I assume $6000 for that Studio machine but it looks now more like $8000.
I wonder how this compares to my M4 air with 10 GPU cores and 32 MB of RAM. My system can only run ~14B sized models at any reasonable speed. The accuracy of these sized models can be underwhelming. I am looking forward to a time when it would be nice to run models locally at a reasonable price, at a reasonable speed and with reasonable accuracy. I don't think we are there just yet.
I have an m4 pro MBP, 1tb storage and 24gb RAM. Not seeing any reason to consider an upgrade whatsoever.
Is that supposed to be a surprise?
I thought that new models were typically released in October. Have I misremembered or is this an unusual timing vs previous years? If so, I wonder why the earlier release?
They didn't update them last October is why.
I think at this point Apple will just release new versions of laptops whenever new CPU revisions and yields allow. M5 Pro wasn't ready for October so delayed until now.
You remember well, they didnāt update these last fall.
And another rumor said these are going to be updated again this fall but Iām not sure about that. With OLED screens and M6 (supposedly).
Increasing component prices perhaps? Get some sales in before you have to jack up the sale price.
Prices arenāt likely to change. Even when the tariffs were on, Appleās prices didnāt change; they gave up some margin.
They also probably had RAM contracts in place far enough in advance to avoid the worst of the price spikes.
Maybe they want people to have more money available for the new phones later this year, since that market is in decline.
M6 is rumored to be released in Q4.
My M3 Pro with 18gb of ram still feels like a beast. The only thing I can make it suffer with so far is generating meshes from 3D scanning, and even then I'm just patient. Apple is suffering from success with these older laptops, it's a tough sell to upgrade, even from the M1 Max folks.
I mean, they had to make them good because of the new cpu architecture, but since the emulation worked so well and overall adoption was really fast it now is a problem for them as a company. A really good problem to have though
But is it powerful enough to run Liquid glass?
/s I assume but itās crazy to me that LG runs on the watch
Apple TV 4K canāt run the Liquid Glass interface without stuttering, turning off transparency restores fluid (heh!) animations.
Unlikely.
An āunrivaled experienceā with MacOS Tahoeā¦
Still only 8TB max storage. Ugh!
wth are you doing w/ wordpress that requires more than 8tb of storage!?
What's a good value for a used MacBook pro these days? Any of the older models worth buying today?
It's hard to find any fault with the M1 models released 5 years ago. According to second-hand listings on Swappa, US$1200 would get you a capable M1 Max; the equivalent M5 Max is US$3600.
I have absolutely no need and yet I want ittttt
The screenshot of running LM Studio alongside Maya is a massive hardware flex.
Wish it was Blender though ;)
Considering these max out at 128GB of unified ram my guess is the hope of an M5 Ultra with 1TB of unified ram is unlikely to come true... Super disappointing.
Is the M5 Max the first laptop with significantly more memory bandwidth than the M1 Max? Looks like about a 20% jumpā¦ might finally be time to re-benchmark CFD workloads.
Still why especially for Pro there is still version with 24 GB of RAM? It is scary....
I'm done buying Macs until they prove they can ship an OS
will it run GLM-4.7 locally at any speed?
I would probably upgrade my MacBook Pro at once, if it wasn't for the Tahoe disaster. Now, not so much, I'm inclined to wait until next year.
Kinda funny that the top image is capture one when Apple literally owns Photomator and gives you the option of bundling it when you buy.
There only run that low contrast Mac OS version tho.
128gb of memory, it's a nice change for Apple not to lag in that department for once, wonder what such a machine will cost though.
Checking Apple's store, I can't find a cheaper configuration than $5100 for the M5 + 128GiB version.
Here in Europe, including 21% VAT, that's ā¬6.124,00 ($7.094,35 equivalent).
Because of pricing strategies and such, the 128GiB version comes with a 2TiB SSD at minimum, and also requires the M5 Max (not Pro) at its highest configuration.
Not sure if this is new, but it should be noted that these laptops don't come with a charger any more.
In the US, power adapters are included:
Because your countries mandate no power adapter for some stupid ewaste reason.
They didn't: https://9to5mac.com/2025/10/16/no-the-eu-didnt-ban-apple-fro...
Devices should be offered without a charger. There's no law that states that that should be the default configuration. Nor that the charger should cost extra.
I know EU didn't ban chargers, but the common American sentiment somehow molded into that.
It is interesting to see how mass-propaganda is playing out right before our eyes...
In US, going to 128 GB from 32 is $1500 extra. However 32 GB is only offered with the 32 core version and 128 only with the 40 core version.
At today's prices, the memory will probably cost more than the rest of the hardware combined :P
They've offered 128gb of RAM since at least the M3.
128gb was there for a while. I am kind of disappointed they do not have 256gb option.
I was really hoping to see 512gb but I guess they don't want it to cut into the sales of the Studio.
No 256 GB model, so no purchase. What a shame.
Same here. If the had 256GB option I'd pull a trigger. Now I might be looking for alternatives.
> M5 Pro supports up to 64GB of unified memory with up to 307GB/s of memory bandwidth, while M5 Max supports up to 128GB of unified memory with up to 614GB/s of memory bandwidth
Which roughly translates to 30B Q8 size LLM at 10t/s for the M5 Pro and 60B Q8 size LLM at 10t/s for the M5 Max
For reference, RTX 3090 24GB has a memory bandwidth of approx. 936.2 GB/s, DGX Spark 128GB features a unified memory bandwidth of up to 273 GB/s
Yeah, this feels like the annual ānice, but do I actually need it?ā refresh if youāre already on an M4 Pro.
I'm on an M1 Pro and it's still a "nice, but do I actually need it?". They've done too well on the hardware side.
I wonder if it is good to just get one and run Linux on a VM. Would that work better than an x64? Anybody knows?
Why would you want to do that? Do you like the hardware that much, and also that much more than just an M2 (soon M3) running Asahi?
Linux in a VM would work with the usual caveats. Periphery like the built-in webcam most likely won't work. Getting codecs and DRM to run will be pain and you'll be back to use macOS for that quickly (but that's just standard pain of ARM Linux).
Because I don't like MacOS and my understanding is that Asahi has issues with: * USB-C Displays * Thunderbolt / USB4 * Touch ID
Touch ID is the least of the problems, but the other two are more serious.
$5000 laptop you have to pay to add a power adapterā¦ gratuitous penny pinching from Tim Cook's Apple.
It's one of those things, yes if I'm spending that much on a laptop I can afford to spend $80 on the adapter too, but does it feel good as a customer to do that or are you souring the experience of buying from you just to earn a few more dollars.
I'm assuming you're in the EU or UK, Apple is required by law to not include a power adapter:
https://appleinsider.com/articles/25/10/15/eu-gets-what-it-a...
In the US they provide one in the box free of charge.
Nope, they are required to have an option to opt-out from adapter. They choose to charge for one!
https://9to5mac.com/2025/10/16/no-the-eu-didnt-ban-apple-fro...
Does the law say they have to charge for it.
This is one thing I don't really blame Apple for, and I think everyone else will follow suit -- and not just because Apple is doing it.
The EU requires that users must be able to buy a device without a charger. It's a huge supply chain challenge to add two variants of every single SKU, one with a charger and one without. So the obvious solution is to sell the charger separately, since you need that regardless, and always sell the device without a charger. You avoid having two variants of everything that way.
Now, you could maybe argue that Apple should default to bundle a charger with your laptop, so that you'd have to uncheck a "bundle charger" checkbox on their website. But do you really care whether your laptop costs $2200 and you can buy a charger for $60 or your laptop costs $2260 and you can save $60 by removing the charger?
You can make an argument that doing it Apple's way hides a price increase. And yeah, that's probably fair. But it's not like Apple is afraid of non-hidden price increases either.
I have a huge tote box full of power bricks, most of them white Apple ones. I have a stack of 60-90W Apple USB-C ones too that I don't use cause they only have one port and are larger and worse than modern GaN units that can do 140W on one port while also pushing 30 or 60 on the others.
So, if you want one of mine, you can have one. On me. Because I'm fucking drowning in the things and appreciate not having to deal with another one.
If you are thinking about running the next Deepseek model, then you are going to be a bit disappointed with the M5
Might need to wait for the M5 Ultra or M6 Max with 128GB of RAM until the memory bandwidth is greater than a GTX 5090.
So below 128gb is the sweet spot for local LLMs...
Tell me a joke That's a hierarchical
> M5 Max supports up to 128GB of unified memory with up to 614GB/s of memory bandwidth
for reference, the M1 Max has 400GB/s of memory bandwidth, half a decade ago
That's big hockey
I am very excited by this, but I am a bit dampened that the maximum memory available is 128GB. I was really hoping for 256GB, which would allow me to run frontier models locally. I think with 128GB it's still feasible to use this with something like Qwen3-Coder-Next and MiniMax-M2.5, but things like Kimi-K2.5 will require significant quantization to fit and model performance will really suffer.
I'm really wanting to build proper local-first AI workflows at home, and I think Apple has an opportunity to make that possible in a way other companies aren't really focused on, but we need significantly larger memory capabilities to do it, which I know is tough in the current memory market but should be available for a cost.
Tell me about it. I checked the page thinking whether I should go for 256 GB or 512 GB RAM model.
128 GB maximum.
Sigh.
I am only interested in one thing: what's the best local AI model it can run?
I will wait for the new mac mini instead
And your native CLI tools will continue to be from 2011 with 0 attention paid to the dev experience until itās Swift, and weāll continue to lock you out of running programs from other human beings we didnāt approve without a 6 step ritual in the OS. Oh and all apps will continue to constantly phone home i.e. pay for the machine so Google Adobe and Microsoft can run updaters and telemetry on it all day.
Many of the CLI tools have been updated to recent FreeBSD versions.
Good point about the telemetry part. I've been using Little Snitch for the past few years and just block all the telemetry calls.
Or donāt use Google, Adobe or Microsoft software if that bothers you? And how is that Appleās fault?
Right, actually instead of having first class tools and systems that respect us we should all go live in a hut in the forest āif it bothers usā. Apple is right there next to them abusing our machines and makes 0 effort to protect users from this.
Can Apple marketing please reduce the insane quantity of adjectives in its releases, it has been nauseating to read for decades and sickens me when visiting their sites. Early exit from me and ex-OSX dev for over a decade, wont be back until their core culture changes.
The performance numbers are impressive, but I do not get the on-board AI spin. What is it used for?
Private AI assistants will be a big thing. You don't want to send all your private data they have access to to a cloud AI API provider. You shouldn't, anyway.
If youāre working on something sensitive, you may not want to share it with OpenAI or Anthropic.
You can run open source models like Kimi K or Qwen locally. Apple recently updated Xcode 26.3 to support local models.
Local LLMs. Lots of people buy Macs due to their unified memory which obviates the need to buy a much more expensive GPU to get the same amount of VRAM.
Image Playground
marketing.
I barely push my M2 Pro MBPs. Most of my wants aren't hardware-related, they're software-related. How it runs some games from 10-20 years ago very well, but only through hacky compatibility layers that shouldn't be necessary. How some parts of the OS have gotten "out of sync" with each other.
Actually, I can think of one hardware want: have they gotten it to where you can do external GPUs and the like more easily?
Would still buy one over any other laptop on the market today for what I use them for.
Well that's. Just. Great. I bought a 64GB M4 Max MBP last month. I'm past the 14-day return window. I figured the M5 was near, but assumed M5 Max would come a bit later. Not sure where I came up with that.
You can console yourself with the fact that your laptop, unlike one of the new ones if you'd bought that instead, can run macOS Sequoia (without "Liquid Glass") rather than Tahoe.
This is always the gamble with buying a Mac. Either purchase right when the new is released, or be on the fence of your new becoming old a couple of weeks after purchase.
Not sure either since M5 base has been available for months now
Ah yes, that's right. I was looking at the M5 model last month wondering why there was no 64GB option.
M5 has been out since last year, no?
You have to pay separately for the charger now. Ā£99, what a bargain.
Or just don't but an Apple charger? You can get a perfectly fine small 100W GAN USB-C charger for like $30 on Amazon.
Since that is required by law, I suggest moving.
Which part of the law requires it to be Ā£99 (or Ā£1 even?). Can you cite it?
I already have various chargers, don't you?
Theyāre giving us extra storageā¦ but theyāve put the price up by 200, which is as much as they charged for the storage anyway.
Why do you think the price went up by $200?
āAn Unrivaled Experience with macOS Tahoeā
Imagine these with a functioning keyboard, ports, replaceable battery and a good operating system.
In what way are the keyboards and ports non-functional?
Yeah, I'm always envy of the Mac's power together with long battery times. But so tired of their software and dongles.
My current work laptop (Lenovo) is quite a beast as well when plugged in, but I can literally see the battery percentage tick down while unplugged, but colleagues with their Macs can go all day.
Only 128GB. I was hoping they'd do 256GB version. Disappointing.
TL;DR Is this major change, or just incrimental?
Just about to be time for me to get a new laptop. Typically I buy a generation behind, but want to make sure I won't miss anything huge.
> MacBook Pro and the Environment
LOL. is it repairable? probably not.
Only good apple product, most overvallued company ever.
$5k machine for developers to just run claude code while they browse Reddit.
With an additional $200/month subscription from Anthropic, because they noticed that the Kimi K2.5 they were able to run on their M5 comes nowhere close to matching Opus 4.6.
>unified memory
This is just marketing speak. Stop repeating marketing. It isnt a walled garden, its a walled prison.
Unified memory is just regular memory. There is nothing special about integrated GPUs.
Isnāt that is how itās called though? PS4/PS5, Xbox consoles all referred to it like that on the spec sheets.