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I bet there’s gonna be a banger of a Mac Studio announced in June. Apple really stumbled into making the perfect hardware for home inference machines. Does any
by chatmasta 7mo ago
I bet there’s gonna be a banger of a Mac Studio announced in June.
Apple really stumbled into making the perfect hardware for home inference machines. Does any hardware company come close to Apple in terms of unified memory and single machines for high throughput inference workloads? Or even any DIY build?
When it comes to the previous “pro workloads,” like video rendering or software compilation, you’ve always been able to build a PC that outperforms any Apple machine at the same price point. But inference is unique because its performance scales with high memory throughput, and you can’t assemble that by wiring together off the shelf parts in a consumer form factor.
It’s simply not possible to DIY a homelab inference server better than the M3+ for inference workloads, at anywhere close to its price point.
They are perfectly positioned to capitalize on the next few years of model architecture developments. No wonder they haven’t bothered working on their own foundation models… they can let the rest of the industry do their work for them, and by the time their Gemini licensing deal expires, they’ll have their pick of the best models to embed with their hardware.
- HerbManic 7mo agoJeff Geerling doing that 1.5TB cluster using 4 Mac Studios was pretty much all the proof needed to demo how the Mac Pro is struggling to find any place any more. https://www.jeffgeerling.com/blog/2025/15-tb-vram-on-mac-studio-rdma-over-thunderbolt-5/ https://www.jeffgeerling.com/blog/2025/15-tb-vram-on-mac-stu...
- zozbot234 7mo agoBut those Thunderbolt links are slower than modern PCIe. If there's actually a M5-based Mac Studio with the same Thunderbolt support, you'll be better off e.g. for LLM inference, streaming read-only model weights from storage as we've seen with recent experiments than pushing the same amount of data via Thunderbolt. It's only if you want to go beyond local memory constraints (e.g. larger contexts) that the Thunderbolt link becomes useful.
- wpm 7mo agoWhy everyone wants to live in dongle/external cabling/dock hell is beyond me. PCIe cards are powered internally with no extra cables. They are secure. They do not move or fall off of shit. They do not require cable management or external power supplies. They do not have to talk to the CPU through a stupid USB hub or a Thunderbolt dock. Crappy USB HDMI capture on my Mac led me to running a fucking PC with slots to capture video off of a 50 foot HDMI cable, that then streamed the feed to my Mac from NDI, because it was more reliable than the elgarbo capture dongle I was using. This shit is bad. It sucks. It's twice the price and half the quality of a Blackmagic Design capture card. But, no slots, so I guess I can go get fucked.
- wtallis 7mo agoFor anything that's even somewhat in the consumer space rather than pure workstation/professional, the main reason is that dongles can be used with a laptop but add-in cards can't. When ordinary consumer PCs (or even office PCs) are in the picture, laptops are a huge chunk of the target audience. The market segments that can afford to ignore laptops and only target permanently-installed desktops are mostly those niches where the desktop is installed alongside some other piece of equipment that is much more expensive.
- GeekyBear 7mo agoWasn't streaming models from storage into limited memory a case where it was impressive that you could make the elephant dance at all? If you want to get usable speeds from very large models that haven't been quantitized to death on local machines, RDMA over Thunderbolt enables that use case. Consumer PC GPUs don't have enough RAM, enterprise GPUs that can handle the load very well are obscenely expensive, Strix Halo tops out at 128 Gigs of RAM and is limited on Thunderbolt ports.
- zozbot234 7mo agoThe bad performance you saw was with very limited memory and very large models, so streaming weights from storage was a huge bottleneck. If you gradually increase RAM, more and more of the weights are cached and the speed improves quite a bit, at least until you're running huge contexts and most of the RAM ends up being devoted to that. Is the overall speed "usable"? That's highly subjective, but with local inference it's convenient to run 24x7 and rely on non-interactive use. Of course scaling out via RDMA on Thunderbolt is still there as an option, it's just not the first approach you'd try.
- pjmlp 7mo agoThat is the proof what is left is a workaround, just like pilling minis on racks because Apple left the server space. Also why Swift nowadays has to have good Linux support, if app developers want to share code with the server.
- coldtea 7mo agoA workaround that works is better than an official solution that's barely adequate. Which is often the case.
- pjmlp 7mo agoOr just maybe, to use a Steve Jobs quote, one is holding it wrong and should look elsewhere.
- coldtea 7mo agoPeople sneer at this Steve Jobs quote, but almost anybody working in tech had at some point quoted another, stronger, quote like "We tried to make the program idiot proof, but they keep making better idiots". There's also: "Programming today is a race between software engineers striving to build bigger and better idiot-proof programs, and the Universe trying to produce bigger and better idiots. So far, the Universe is winning." https://en.wikiquote.org/wiki/Rick_Cook https://en.wikiquote.org/wiki/Rick_Cook
- mixdup 7mo agoThe proposition of a Mac Pro in the Apple Silicon world wasn't necessarily about performance, it was about the existence of the PCIe slots. I don't think AI becoming a workload for pro Macs means the Mac Pro doesn't have a place, people who were using Mac Pros for audio or video capture didn't stop doing that media work and switched to AI as a profession. That market just wasn't big enough to sustain the Mac Pro in the first place and Apple has finally acknowledged that fact
- grahamlee 7mo agoso many peripherals now come in external boxes that communicate _incredibly quickly_ over Thunderbolt 4/5 that the need for PCIe is marginal, while the cost to support it is significant.
- alsetmusic 7mo agoI had a U-Audio PCI card in a Mac Pro during the Intel era of Macs. It was a chip to run their software plugins and the plugins are top of the line. I have a U-Audio box that runs over Thunderbolt now. I know there are people who need device slots, but it's vanishingly few. I'm disappointed that this category of machine is going away, but it stopped being for me in the Apple Silicon era.
- ActorNightly 7mo agoWow spend 40k to get the same tokens/second in QWEN as you would on a 3090 I have a feeling that Mac fans obsess more about being able to run large models at unusably slow speeds instead of actually using said models for anything.
- rubyn00bie 7mo agoI don't think Apple just stumbled into it, and while I totally agree that Apple is killing it with their unified memory, I think we're going to see a pivot from NVidia and AMD. The biggest reason, I think, is: OpenAI has committed to enormous amount capex it simply cannot afford. It does not have the lead it once did, and most end-users simply do not care. There are no network effects. Anthropic at this point has completely consumed, as far as I can tell, the developer market. The one market that is actually passionate about AI. That's largely due to huge advantage of the developer space being, end users cannot tell if an "AI" coded it or a human did. That's not true for almost every other application of AI at this point. If the OpenAI domino falls, and I'd be happy to admit if I'm wrong, we're going to see a near catastrophic drop in prices for RAM and demand by the hyperscalers to well... scale. That massive drop will be completely and utterly OpenAI's fault for attempting to bite off more than it can chew. In order to shore up demand, we'll see NVidia and AMD start selling directly to consumers. We, developers, are consumers and drive demand at the enterprises we work for based on what keeps us both engaged and productive... the end result being: the ol' profit flywheel spinning. Both NVidia and AMD are capable of building GPUs that absolutely wreck Apple's best. A huge reason for this is Apple needs unified memory to keep their money maker (laptops) profitable and performant; and while, it helps their profitability it also forces them into less performant solutions. If NVidia dropped a 128GB GPU with GDDR7 at $4k-- absolutely no one would be looking for a Mac for inference. My 5090 is unbelievably fast at inference even if it can't load gigantic models, and quite frankly the 6-bit quantized versions of Qwen 3.5 are fantastic, but if it could load larger open weight models I wouldn't even bother checking Apple's pricing page. tldr; competition is as stiff as it is vicious-- Apple's "lead" in inference is only because NVidia and AMD are raking in cash selling to hyperscalers. If that cash cow goes tits up, there's no reason to assume NVidia and AMD won't definitively pull the the rug out from Apple.
- pjmlp 7mo agoNo one cares about Metal in that space, plus CUDA already has unified memory for a while. https://docs.nvidia.com/cuda/cuda-programming-guide/04-special-topics/unified-memory.html https://docs.nvidia.com/cuda/cuda-programming-guide/04-speci... Can we also stop giving Apple some prize for unified memory? It was the way of doing graphics programming on home computers, consoles and arcades, before dedicated 3D cards became a thing on PC and UNIX workstations.
- tannhaeuser 7mo agoFor LLMs and other pure memory-bound workloads, but for eg. diffusion models their FPU SIMD performance is lacking.
- robotswantdata 7mo agoDGX workstations, expensive but allow PCI cards as well. https://marketplace.nvidia.com/en-us/enterprise/personal-ai-supercomputers/?superchip=GB300&page=1&limit=15 https://marketplace.nvidia.com/en-us/enterprise/personal-ai-...
- QuantumNomad_ 7mo agoHow much do those workstations cost? All of the different manufacturers links on that page lack pricing info and you have to contact them for pricing.
- fooker 7mo agoIt's hilarious that not a single one of these has pricing listed anywhere public. I don't think they expect anyone to actually buy these. Most companies looking to buy these for developers would ideally have multiple people share one machine and that sort of an arrangement works much more naturally with a managed cloud machine instead of the tower format presented here. Confirming my hypothesis, this category of devices more or less absent in the used market. The only DGX workstation on ebay has a GPU from 2017, several generations ago.
- numpad0 7mo agoI don't think it's so odd, very few products above ~$50k have final prices listed for anyone to buy 1-click.
- DeathArrow 7mo agoStill, running 2 to 4 5090 will beat anything Apple has to offer for both inference and training.
- Tsiklon 7mo agoThat won’t work for the home hobbyist 2.4KW of GPU alone plus a 350W threadripper pro with enough PCIe lanes to feed them. You’re looking at close to twice the average US household electricity circuit’s capacity just to run the machine under load. A cluster of 4 Apple’s M3 ultra Mac studios by comparisons will consume near 1100W under load.
- bluedino 7mo agoI mean if a hobbyist can run a welder or cnc machine in their home workshop...
- mitjam 7mo agoI would say 1-2 RTX 6000 Pro maxQ are more practical.
- port11 7mo agoAs to better or cheaper homelab: depends on the build. AMD AI Max builds do exist, and they also use unified memory. I could argue the competition was, for a long time, selling much more affordable RAM, so you could get a better build outside Apple Silicon.
- spacedcowboy 7mo agoAgreed. I’m planning on selling my 512GB M3 Ultra Studio in the next week or so (I just wrenched my back so I’m on bed-rest for the next few days) with an eye to funding the M5 Ultra Studio when it’s announced at WWDC. I can live without the RAM for a couple of months to get a good price for it, especially since Apple don’t sell that model (with the RAM) any more.
- wolfhumble 7mo agoJust out of curiosity, where do you think is the best place to sell a machine like that with the lowest risk of being scammed, while still getting the best possible price? Wish you a speedy recovery for your back!
- asimovDev 7mo agolowest is probably an apple trade in if available, but i can't imagine how bad of a price hit it will be.
- spacedcowboy 7mo agoI checked, it's terrible. They don't take into account the size of the RAM in the machine, so you get the base-model trade-in value (£1280). Yeah, no.
- polshaw 7mo agosounds like 100% risk of getting scammed
- spacedcowboy 7mo ago> Just out of curiosity, where do you think is the best place to sell a machine like that with the lowest risk of being scammed, while still getting the best possible price? There are none currently on eBay.co.uk, so I'm going to try there. I'll also try some of the reddit UK-specific groups. As far as not being scammed - it's a really high value one-off sale, so it'll either be local pickup (and cash / bank-transfer at the time, which happens in seconds in the UK) or escrow.com (for non-eBay) with the buyer paying all the fees etc. I'd prefer local pickup because then I have the money, the buyer can see it working, verify everything to their satisfaction etc. etc. > Wish you a speedy recovery for your back! Thank you :) It is a little better today. Sitting down is now tolerable for short periods... :)
- hermanzegerman 7mo agoFramework offers the AI Ryzen Max with ̶1̶9̶6̶G̶B̶ 128GB of unified RAM for 2,699$ That's a pretty good deal I would think https://frame.work/de/de/products/desktop-diy-amd-aimax300/configuration/new https://frame.work/de/de/products/desktop-diy-amd-aimax300/c...
- rl3 7mo ago128GB*
- hermanzegerman 7mo agoThanks for spotting the mistake. No Idea how I got to 192
- rl3 7mo agoFor what it's worth, I really wish that was the actual number.
- eigenspace 7mo agoThe framework desktop is quite cool, but those Ryzen Max CPUs are still a pretty poor competitor to Apple's chips if what you care about it running an LLM. Ryzen Max tops out at 256 GB/s of memory bandwidth, whereas an M4 Max can hit 560 GB/s of bandwidth. So even if the model fits in the memory buffer on the Ryzen Max, you're still going to hit something like half the tokens/second just because the GPU will be sitting around waiting for data. Personally, I'd rather have the Framework machine, but if running local LLMs is your main goal, the offerings from Apple are very compelling, even when you adjust for the higher price on the Apple machine.
- rl3 7mo agoThere's also the DGX Spark. Granted, its price has been going up recently alongside everything else that has memory in it.
- fooker 7mo agoThe typical inference workloads have moved quite a bit in the last six months or so. Your point would have been largely correct in the first half of 2025. Now, you're going to have a much better experience with a couple of Nvidia GPUs. This is because of two reasons - the reasoning models require a pretty high number of tokens per second to do anything useful. And we are seeing small quantized and distilled reasoning models working almost as well as the ones needing terabytes of memory.
- whywhywhywhy 7mo ago> But inference is unique because its performance scales with high memory throughput, and you can’t assemble that by wiring together off the shelf parts in a consumer form factor. Nvidia outperforms Mac significantly on diffusion inference and many other forms. It’s not as simple as the current Mac chips are entirely better for this.
- rafram 7mo agoBut where are you going to find an Nvidia GPU with 128+ GB of memory at an enthusiast-compatible price?
- ricardobayes 7mo agoThat might even be true, but how large is the TAM for such machines?
- edelans 7mo agoand let alone competing on the energy consumption!
- sippeangelo 7mo agoSome Chinese sources sell modded Nvidia GPUs with extra VRAM. They're quite affordable in comparison to even a Mac Pro.
- giwook 7mo agoAnd how much do you trust Chinese hardware?
- x______________ 7mo agoWhen there's no one left to trust, maybe you need to re-evaluate your criteria.
- sgc 7mo ago
- dragonwriter 7mo ago> Apple really stumbled into making the perfect hardware for home inference machines For LLMs. For inference with other kinds of models where the amount of compute needed relative to the amount of data transfer needed is higher, Apple is less ideal and systems worh lower memory bandwidth but more FLOPS shine. And if things like Google’s TurboQuant work out for efficient kv-cache quantization, Apple could lose a lot of that edge for LLM inference, too, since that would reduce the amount of data shuffling relative to compute for LLM inference.
- NetMageSCW 7mo agoOr just mean that you could run a 5x bigger model on Apple than before.
- dragonwriter 7mo agoWell, since its kv-cache that TurboQuant optimizes, it means five times bigger context fits into RAM, all other things being equal, not a five times bigger model. But, sure, with any given context size and the same RAM available, you can instead fit a bigger model—which also takes more compute to get the same performance. Anything that increases the necessary compute to fully utilize RAM bandwidth in optimal LLM serving weakens Apples advantage for that.
- _zoltan_ 7mo agohow about the newly announced GB300 DGX Workstation?
- NetMageSCW 7mo agoComparing a $100K workstation to a $4K desktop PC seems a bit Apples and oranges?
- kranke155 7mo agoThe new M chips beat basically any PC on video editing. Their new ProRes accelerator chiplet is so good they can’t even compete.
- Melatonic 7mo agoGoodluck storing all those 8k videos, plates, and other content on soldered in SSD
- simondotau 7mo ago1. Thunderbolt 4 exists. 2. Even with today's prices, storage is a relatively minor expense for professionals working at this level. 3. When material above 4K is used in a serious workflow, it tends to be at the acquisition phase only. In post production, raw files get transcoded to a proxy format (e.g. ProRes 422 Proxy) for editing. 4. In multi-user workflows, media is commonly accessed directly from shared network storage instead of duplicated onto individual machines. 5. Effects work is normally handled on a shot-by-shot basis. Even if they're working on local copies, we're talking mere minutes of raw material, if not seconds.
- kranke155 7mo agoSSDs can do fine even on USB3 with 4k ProRes 4444 files. At least on my projects. Not sure what OP is doing. I dont know anyone who shoots/finishes in 8k. Most pipelines I know of are 4k.
- SwtCyber 7mo agoThe interesting question is whether they'll lean into it intentionally (better tooling, more ML-focused APIs) or just keep treating it as a side effect of their silicon design
- chatmasta 7mo agoI think we’ll see a much more robust ecosystem develop around MLX now that agentic coding has reduced the barrier of porting and maintaining libraries to it.
- tantalor 7mo ago> home inference machines. The market for this use case is tiny
- chatmasta 7mo agoFor now. In a few years it will be part of every day life, because people will see Apple users enjoying it without thinking about it. You won’t consider it a “home inference machine,” just a laptop with more capabilities than any other vendor offers without a cloud subscription.
- valzam 7mo agoThe average person self hosts literally nothing, why would it be different for inference? Which benefits severely from economies of scale and efficient 24/7 utlization
- diabllicseagull 7mo agoI'm not a big fan of reducing computing as a whole to just inference. Apple has done quite a bit besides that and it deserves credit. Mac Pro disappearing from the product line is a testament to it, that their compact solutions can cover all needs, not just local inference, to a degree that an expandable tower is not required at all.
- embedding-shape 7mo ago> Mac Pro disappearing from the product line is a testament to it Apple removing/adding something to their product line matters nothing, for all we know, they have a new version ready to be launched next month, or whatever. Unless you work at Apple and/or have any internal knowledge, this is all just guessing, not a "testament" to anything.
- NetMageSCW 7mo agoDid you read the article? “Apple has also confirmed to 9to5Mac that it has no plans to offer future Mac Pro hardware.”
- embedding-shape 7mo agoI did indeed! Did you read the article? Did you like it? Have you also read the HN guidelines by any chance? None the less, what Apple says or doesn't say doesn't really matter. If their plan for a new Mac Pro is secret, they'll answer exactly that when someone asks them about it. Doesn't mean we won't see new Mac Pro hardware this summer. Plenty of cases in the past where they play coy and then suddenly, "whoops, we just had to keep it a secret, never mind".
- kllrnohj 7mo agoTheir compact solution doesn't cover all needs, they just decided that they didn't care about some of those needs. The Intel Mac Pro was the last Apple offering with high end GPU capabilities. That's now a market segment they just aren't supporting at all. They didn't figure out how to do it compactly, they just abandoned it wholesale. Similarly if your use case depends on a whole lot of fast storage (eg, the 4x NVME to PCI-E x16 bifurcation boards), well that's also now something Apple just doesn't support. They didn't figure out something else. They didn't do super innovative engineering for it. They just walked away from those markets completely, which they're allowed to do of course. It's just not exactly inspiring or "deserves credit" worthy.
- AJRF 7mo ago> Apple really stumbled into making the perfect hardware for home inference machines Apple are winning a small battle for a market that they aren’t very good in. If you compare the performance of a 3090 and above vs any Apple hardware you would be insane to go with the Apple hardware. When I hear someone say this it’s akin to hearing someone say Macs are good for gaming. It’s such a whiplash from what I know to be reality. Or another jarring statement - Sam Altman saying Mario has an amazing story in that interview with Elon Musk. Mario has basically the minimum possible story to get you to move the analogue sticks. Few games have less story than Mario. Yet Sam called it amazing. It’s a statement from someone who just doesn’t even understand the first thing about what they are talking about. Sorry for the mini rant. I just keep hearing this apple thing over and over and it’s nonsense.
- alberth 7mo agoJust a reminder that the old Intel Mac Pro could handle 1.5TB of RAM ... today's Mac Studio can only handle 0.25TB. Seem odd that a computer from a decade ago could have more than a 1TB of incremental RAM vs what we can buy today from Apple.
- NetMageSCW 7mo agoThe M5 Ultra Studio may support more as it becomes a replacement for the Mac Pro.
- utopiah 7mo ago> ...making the perfect hardware for home inference machines. I really don't get why anybody would want that. What's the use case there? If someone doesn't care about privacy, they can use for-profit services because they are basically losing money, trying to corner the market. If they care about privacy, they can rent cloud instances in order to setup, run, close and it will be both cheaper, faster (if they can afford it) but also with no upfront cost per project. This can be done with a lot of scaffolding, e.g. Mistral, HuggingFace, or not, e.g. AWS/Azure/GoogleCloud, etc. The point being that you do NOT purchase the GPU or even dedicated hardware, e.g. Google TPU, but rather rent for what you actually need and when the next gen is up, you're not stuck with "old" gen. So... what use case if left, somebody who is both technical, very privacy conscious AND want to do so offline despite have 5G or satellite connectivity pretty much anywhere? I honestly don't get who that's for (and I did try a dozens of local models, so I'm actually curious). PS: FWIW https://pricepertoken.com https://pricepertoken.com might help but not sure it shows the infrastructure each rely on to compare. If you have a better link please share back.
- pwython 7mo agoGenuine question: If I were to fine-tune a model with 10 years of business data in a competitive space, would you feel safe with cloud training?
- yomismoaqui 7mo agoIf you already have those 10 years of bussiness data on Microsoft or Google services or their respective clouds, are you feeling safe?
- justinhj 7mo agoPeople store that data in databases in the same data centre so it's really the same level of trust needed that your provider adheres to the no training on your data. Trust and lawyers.
- utopiah 7mo agoI'm not a lawyer but technically most if not all cloud providers, specific to AI ("neo-cloud") or not, to provide Customer-managed encryption keys (CMEK) as someone else pointed out. That being said if I were to be in such a situation, and if somehow the guarantees wouldn't be enough then I'd definitely expect to have the budget to build my own data center with GB300 or TPUs. I can't imagine that running it on a Mac Studio.
- dabockster 7mo agoCUDA 13 on Linux solves the unified memory problem via HMM and llamacpp. It’s an absolute pain to get running without disabling Secure Boot, but that should be remedied literally next month with the release of Ubuntu 26.04 LTS. Canonical is incorporating signed versions of both the new Nvidia open driver and CUDA into its own repo system, so look out for that. Signed Nvidia modules do already exist right now for RHEL and AlmaLinux, but those aren’t exactly the best desktop OSes. But yeah, right now Apple actually has price <-> performance captured a lot of you’re buying a new computer just in general.
- zadikian 7mo agoWhat part of your workflow relies on home LLM inference?
- alerighi 7mo agoTo me there is a fundamental difference. Even if PC hardware costs slightly more (now because of the RAM situation, Apple producing his chips in house can get better deals of course), it's something that is worth more investing in in. Maybe you spend 1000$ more for a PC of comparable performance, well tomorrow you need more power, change or add another GPU, add more RAM, add another SSD. A workstation you can keep upgrade it for years, adding a small cost for an upgrade in performance. An Apple machine is basically throw away: no component inside can be upgraded, you need more RAM? Throw it away and buy a new one. You want a new GPU technology? You have to change the whole thing. And if something inside breaks? You of course throw away the whole computer since everything is soldered on the mainboard. There is then the software issue, with Apple devices you are forced to use macOS that kind of sucks, especially for a server usage. True nowadays you can install Linux on it, but the GPU it's not that well supported, thus you loose all the benefits. You have to stuck with an OS that sucks, while in the PC market you have plenty of OS choices, Windows, a million of Linux distributions, etc. If I need a workstation to train LLM why do I care about a OS with a GUI? It's only a waste of resources, I just need a thing that runs Linux and I can SSH into it. Also I don't get the benefit of using containers, Docker, etc. Mac suck even hardware side form a server point of view, for example it's not possible to rack mount them, it's not possible to have redundant PSU, key don't offer remote KVM capability, etc.
- mjburgess 7mo ago"Upgrades" havent been a thing for nearly a decade. By the time you want to upgrade a machine part (c. 5yr+ for modern machines), you'd want to upgrade every thing, and its cheap to do so. It isnt 2005 any more where RAM/CPU/etc. progress benefits from upgrading every 6mo. It's closer to 6yr to really notice
- bigyabai 7mo agoThat's news to me. I see Mac Minis with external drives plugged-in constantly; I bet those people would appreciate user-servicable storage. I doubt they bought an external drive because they wanted to throw away the whole computer.
- Melatonic 7mo agoApple abandoned the pro market long before ever releasing the current iteration of Mac Pro. I doubt they care about getting it back considering its a smaller niche of consumers and probably significantly more investment on the software side. At best we probably get a chassis to awkwardly daisy chain a bunch of Mac Studios together
- FireBeyond 7mo agoI do love the Mac Studio. I had a 2019 Mac Pro, the Intel cheesegrater, but my home office upstairs became unpleasant with it pushing out 300W+. I replaced it with the M2 Ultra Studio for a fraction of the heat output (though I did had to buy an OWC 4xNVMe bay). > I bet there’s gonna be a banger of a Mac Studio announced in June. Apple really stumbled into making the perfect hardware for home inference machines. This I'm not actually as sure about. The current Studio offerings have done away with the 512GB memory option. I understand the RAM situation, but they didn't change pricing they just discontinued it. So I'm curious to see what the next Studio is like. I'd almost love to see a Studio with even one PCI slot, make it a bit taller, have a slide out cover...
- timtim51251 7mo agoOnce you start adding RAM and storage, the price of the Apple explodes. There is zero expandability and options outside of what Apple provides. So you can easily build a better PC and still at a lower price point for higher end configs. So your argument is a fanboy argument and not based on reality. Is the Mac Studio great? Yeah, for Apple users.