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Apple M3 Ultra
- mythz 2y agoUltra disappointing, they waited 2 years just to push out a single gen bump, even my last year's iPad Pro runs M4.
- heeton 2y agoFor AI workflows that's quite a lot cheaper than the alternative in GPUs.
- mythz 2y agoYeah VRAM option is good (if it performs well), just sad we'd have to drop 10K to access it tied to a prev gen M3 when they'll likely have M5 by the end of the year. Hard to drop that much cash on an outdated chip.
- chvid 2y agoNow make a data center version.
- pier25 2y agoSo weird they released the Mac Studio with an M4 Max and M3 Ultra. Why? They have too many M3 chips on stock?
- bigfishrunning 2y agoThe M4 Max is faster, the M3 Ultra supports more unified memory -- So pick whichever meets your requirements
- nottorp 2y ago> support for more than half a terabyte of unified memory Soldered?
- simlevesque 2y agoAs are all Apple M devices.
- universenz 2y agoIs there a single Apple SoC where they’ve provided removable ram? Not that I can recall.
- danpalmer 2y agoIs there even an existing replaceable memory standard that would meet the current needs of Apple's "Unified Memory" architecture? I'm not an expert but I'd suspect probably not. The bus probably looks a lot more like VRAM on GPUs, and I've never seen a GPU with replaceable RAM.
- jsheard 2y agoCAMM2 could kinda work, but each module is only 128-bit so I think the furthest you could possibly push it is a 512-bit M Max equivalent with CAMM2 modules north, east, west and south of the SOC. There just isn't room to put eight modules right next to the SOC for a 1024-bit bus like the M Ultra.
- eigenspace 2y agoFramework said that when they built a Strix Halo machine, AMD assigned an engineer to work with them on seeing if there's a way to get CAMM2 memory working with it, and after a bunch of back and forth it was decided that CAMM2 still made the traces too long to maintain proper signal integrity due to the 256 bit interface. These machines have a 512 bit interface, so presumably even worse.
- 2y ago
- universenz 2y ago96gb on baseline model m3 ultra with a max of 512gb! Looks like they’re leaning in hard with the AI crowd.
- datadrivenangel 2y agoUnclear what devices this will be in outside of the mac studio. Also most of the comparisons were with M1 and M2 chips, not M4.
- reaperducer 2y agomost of the comparisons were with M1 and M2 chips, not M4. Is anyone other than a vanishingly small number of hard core hobbiests going to upgrade from an M4 to an M4 Ultra?
- nordsieck 2y ago> Is anyone other than a vanishingly small number of hard core hobbiests going to upgrade from an M4 to an M4 Ultra? I expect that the 2 biggest buyers of M4 Ultra will be people who want to run LLMs locally, and people who want the highest performance machine they can get (professionals), but are wedded to mac-only software.
- bredren 2y agoAnecdotal, and reasonable criticisms of the release aside, OpenAI's gpt-4.5 introduction video was done from a hard-to-miss Apple laptop. It is reasonable to say many folks in the field prefer to work on mac hardware.
- _mlbt 2y agoIt is a bit misleading to do that, but in fairness to Apple, almost nobody is upgrading to this from an M4 Mac, so those are probably more useful comparisons.
- TheTxT 2y ago512GB unified memory is absolutely wild for AI stuff! Compared to how many NVIDIA GPUs you would need, the pricing looks almost reasonable.
- InTheArena 2y agoA server with 512GB of high-bandwidth GPU addressable RAM in a server is probably a six figure expenditure. If memory is your constrain, this is absolutely the server for you. (sorry, should have specified that the NPU and GPU cores need to access that ram and have reasonable performance). I specified it above, but people didn't read that :-)
- Numerlor 2y agoA basic brand new server can easily do 512gb. Not as fast as soldered memory but it should be maybe mid to high 5 figures
- la_oveja 2y ago5 figures? can be done in 6k https://x.com/carrigmat/status/1884244369907278106 https://x.com/carrigmat/status/1884244369907278106
- InTheArena 2y agoThat's CPU only memory, not high bandwidth, and not addressable by the GPU.
- jeffbee 2y agoThere isn't anything particularly high-bandwidth about Apple's DDR5 implementation, either. They just have a lot of channels, which is why I compared it to a 24-channel EPYC system. I agree that their integrated GPU architecture hits a unique design point that you don't get from nvidia, who prefer to ship smaller amounts of very different kinds of memory. Apple's architecture may be more suited to some workloads but it hasn't exactly grabbed the machine learning market.
- varjag 2y agoCall me a unit fundamentalist but calling 512Gb "over half a terabyte memory" irks me to no end.
- klausa 2y agoIt's over half a _tera_byte; exactly half of _tebi_byte if you wanna be a fundamentalist.
- varjag 2y agoIt is exactly the opposite. Every computer architecture in production addresses memory in the powers of two. SI has no business in memory size nomenclature as it is not derived from fundamental physical units. The whole klownbyte change was pushed through by hard drive marketers in 1990s.
- esafak 2y agoDo SSD companies do the same thing? We ought to go back to referring to storage capacity in powers of two.
- jl6 2y agoSSDs have added weirdness like 3-bit TLC cells and overprovisioning. Usable storage size of an SSD is typically not an exact power of 10 or 2.
- School-Cotton 2y ago> Every computer architecture in production addresses memory in the powers of two. What does it mean to "address memory in powers of two" ? There are certainly machines with non-power-of-two memory quantities; 96 GiB is common for example. > The whole klownbyte change was pushed through by hard drive marketers in 1990s. The metric prefixes based on powers of 10 have been around since the 1790s.
- 2y ago
- okamiueru 2y agoDon't know what the prior extreme apple is alluding to here. But, apple marketing is what it is.
- _mlbt 2y agoInteresting that they’re releasing M3 Ultra after the M4 Macs have already shipped. I wonder if the plan is to only release Ultras for odd number generations.
- _alex_ 2y agom2 ultra tho
- pier25 2y agoThey released the M2 Ultra
- _mlbt 2y agoGood point, I forgot about that. Maybe it just got really delayed in production.
- ryao 2y agoReportedly Apple is using its own silicon in data centers to run “Apple Intelligence” and other things like machine translation in safari. I suspect that the initial supply was sent to Apple’s datacenters.
- jmull 2y agoI'm guessing it's more because "Ultra" versions, which "fuse" multiple chips take significant additional engineering work. So we might expect an ultra M4 next year, possibly after non-ultra M5s are released.
- iambateman 2y agoPeople who know more than me: they’re talking a lot about RAM and not much about GPU. Do you expect this will be able to handle AI workloads well? All I’ve heard for the past two years is how important a beefy GPU is. Curious if that holds true here too.
- lynndotpy 2y agoVRAM is what takes a model from "can not run at all" to "can run" (even if slowly), hence the emphasis.
- dartos 2y agoYou can say the same about GPU clock speed as well…
- vlovich123 2y agoNo, with limited VRAM you could offload the model partially or split across CPU and GPU. And since CPU has swap, you could run the absolute largest model. It’s just really really slow.
- jeffhuys 2y agoReally, really, really, really, really, REALLY REALLY slow.
- Espressosaurus 2y agoThe difference between Deepseek-r1:70b (edit: actually 32b) running on an M4 Pro (48 GB unified RAM, 14 CPU cores, 20 GPU cores) and on an AMD box (64 GB DDR4, 16 core 5950X, RTX 3080 with 10 GB of RAM) is more than a factor of 2. The M4 pro was able to answer the test prompt twice--once on battery and once on mains power--before the AMD box was able to finish processing. The M4's prompt parsing took significantly longer, but token generation was significantly faster. Having the memory to the cores that matter makes a big difference.
- 2y ago
- ksec 2y agoPrevious model of M2 Ultra had max memory of 192GB. Or 128GB for Pro and some other M3 model, which I think is plenty for even 99.9% of professional task. They now bump it to 512GB. Along with insane price tag of $9499 for 512GB Mac Studio. I am pretty sure this is some AI Gold rush.
- dwighttk 2y agoMaybe .1% of tasks need this RAM, why are they charging so much?
- regularfry 2y agoThe narrower the niche, the more you can charge.
- rewtraw 2y agobecause that's how much its worth
- internetter 2y agoIts not though. For consumer computers somewhere 1k-4k there's nothing better. But for the price of 512gb of RAM you could buy that + a crazy CPU + 2x 5090s by building your own. The market fit is "needs power; needs/wants macOS; has no budget" which is so incredibly niche. But in terms of raw compute output there's absolutely no chance this is providing bang for buck
- jeffhuys 2y agoDo you understand that it's UNIFIED RAM, so it doubles as vRAM? I would love to know what computer you can build for <10k with 0.5TB of VRAM.
- kjreact 2y ago2x 5090s would only give you 64GB of memory to work with re:LLM workloads, which is what people are talking about in this thread. The 512GB of system RAM you’re referring to would not be useful in this context. Apple’s unified memory architecture is the part you’re missing.
- desertmonad 2y agoTime to upgrade m1 ultra I guess! M1 ultra has been pretty good with deepseek locally.
- _alex_ 2y agowhat flavor of deepseek are you running? what kind of performance are you seeing?
- InTheArena 2y agoWhoa. M3 instead of M4. I wonder if this was basically binning, but I thought that I had read somewhere that the interposer that enabled this for the M1 chips where not available. That Said, 512GB of unified ram with access to the NPU is absolutely a game changer. My guess is that Apple developed this chip for their internal AI efforts, and are now at the point where they are releasing it publicly for others to use. They really need a 2U rack form for this though. This hardware is really being held back by the operating system at this point.
- klausa 2y ago>I had read somewhere that the interposer that enabled this for the M1 chips where not available. With all my love and respect for "Apple rumors" writers; this was always "I read five blogposts about CPU design and now I'm an expert!" territory. The speculation was based on the M3 Maxes die shots not having the interposer visible, which... implies basically nothing whether that _could have_ been supported in an M3 Ultra configuration; as evidenced by the announcement today.
- sroussey 2y agoI’m guessing it’s not really a M3. No M3 has thunderbolt 5. This is a new chip with M3 marketing. I’d expect this from Intel, not Apple.
- klausa 2y agoBaseline M4 doesn't have Thunderbolt 5 either; only the Pro/Max variants do. The press-release even calls TB5 out: >Each Thunderbolt 5 port is supported by its own custom-designed controller directly on the chip. Given that they're doing the same on A-series chips (A18 Pro with 10Gbps USB-C; A18 with USB 2.0); I imagine it's just relatively simple to swap the I/O blocks around and they're doing this for cost and/or product segmentation reasons.
- sroussey 2y agoWhich means this is a whole new chip. It may be M3 based, but with added interposer support and new thunderbolt stuff. Which, at this point, why not just use M4 as a base?
- behnamoh 2y ago819GB/s bandwidth... what's the point of 512GB RAM for LLMs on this Mac Studio if the speed is painfully slow? it's as if Apple doesn't want to compete with Nvidia... this is really disappointing in a Mac Studio. FYI: M2 Ultra already has 800GB/s bandwidth
- gatienboquet 2y agoNVIDIA RTX 4090: ~1,008 GB/s NVIDIA RTX 4080: ~717 GB/s AMD Radeon RX 7900 XTX: ~960 GB/s AMD Radeon RX 7900 XT: ~800 GB/s How's that slow exactly ? You can have 10000000Gb/s and without enough VRAM it's useless.
- ttul 2y agoI have a 4090 and, out of curiosity, I looked up the FLOPS in comparison with Apple chips. Nvidia RTX 4090 (Ada Lovelace) FP32: Approximately 82.6 TFLOPS FP16: When using its 4th‑generation Tensor Cores in FP16 mode with FP32 accumulation, it can deliver roughly 165.2 TFLOPS (in non‑tensor mode, the FP16 rate is similar to FP32). FP8: The Ada architecture introduces support for an FP8 format; using this mode (again with FP32 accumulation), the RTX 4090 can achieve roughly 330.3 TFLOPS (or about 660.6 TOPS, depending on how you count operations). Apple M1 Ultra (The previous‑generation top‑end Apple chip) FP32: Around 15.9 TFLOPS (as reported in various benchmarks) FP16: By similar scaling, FP16 performance would be roughly double that value—approximately 31.8 TFLOPS (again, an estimate based on common patterns in Apple’s GPU designs) FP8: Like the M3 family, the M1 Ultra does not support a dedicated FP8 precision mode. So a $2000 Nvidia 4090 gives you about 5x the FLOPS, but with far less high speed RAM (24GB vs. 512GB from Apple in the new M3 Ultra). The RAM bandwidth on the Nvidia card is over 1TBps, compared with 800GBps for Apple Silicon. Apple is catching up here and I am very keen for them to continue doing so! Anything that knocks Nvidia down a notch is good for humanity.
- bigyabai 2y ago> Anything that knocks Nvidia down a notch is good for humanity. I don't love Nvidia a whole lot but I can't understand where this sentinent comes from. Apple abandoned their partnership with Nvidia, tried to support their own CUDA alternative with blackjack and hookers (OpenCL), abandoned that, and began rolling out a proprietary replacement. CUDA sucks for the average Joe, but Apple abandoned any chance of taking the high road when they cut ties with Khronos. Apple doesn't want better AI infrastructure for humanity; they envy the control Nvidia wields and want it for themselves. Metal versus CUDA is the type of competition where no matter who wins, humanity loses. Bring back OpenCL, then we'll talk about net positives again.
- johntitorjr 2y agoLots of AI HW is focused on RAM (512GB!). I have a cost-sensitive application that needs speed (300+ TOPS), but only 1GB of RAM. Are there any HW companies focused on that space?
- Havoc 2y agoGreyskull cards might be a fit. Think they’re not entirely plug and play though
- xyzsparetimexyz 2y agoIsn't that just any discrete (Nvidia,AMD) GPU?
- NightlyDev 2y agoMost recent GPUs will do. An older RTX 4070 is over 400 TOPS, the new RTX 5070 is around 1000 TOPS, and the RTX 5090 is around 3600 TOPS.
- johntitorjr 2y agoYeah, that's basically where I'm at with options. Not ideal for a cost sensitive application.
- stefan_ 2y agoJust buy any gaming card? Even something like the Jetson AGX Orin boasts 275 TOPS (but they add in all kind of different subsystems to reach that number).
- johntitorjr 2y agoThe Jetson is interesting! Can you elaborate on how the TOPS value is inflated? What GPU would be the equivalent of the Jetson AGX Orin?
- stefan_ 2y agoThe problem with the TOPS is that they add in ~100 TOPS from the "Deep Learning Accelerator" coprocessors, but they have a lot of awkward limitations on what they can do (and software support is terrible). The GPU is an Ampere generation, but there is no strict consumer GPU equivalent.
- crest 2y agoToo bad it lacks even the streaming mode SVE2 found in M4 cores. If only Apple would provide a full SVE2 implementation to put pressure on ARM to make it non-optional so AArch64 isn't effectively restricted to NEON for SIMD.
- vlovich123 2y agoThis is for AI which is going to benefit more from use of metal / NPU than SIMD.
- bigyabai 2y agoSure, but larger models that fit in that 512gb memory are going to take a long time to tokenize/detokenize without hardware-accelerated BLAS.
- microtonal 2y agoWhy would you need BLAS for tokenization/detokenization? Pretty much everyone still uses BBPE which amounts to iteratively applying merges. (Maybe I'm missing something here.)
- ryao 2y agoTokenization/detokenization does not use BLAS.
- stouset 2y agoHell I’m just sitting here hoping the future M5 adopts SVE. Not even SVE2.
- lauritz 2y agoThey update the Studio to M3 Ultra now, so M4 Ultra can presumably go directly into the Mac Pro at WWDC? Interesting timing. Maybe they'll change the form factor of the Mac Pro, too? Additionally, I would assume this is a very low-volume product, so it being on N3B isn't a dealbreaker. At the same time, these chips must be very expensive to make, so tying them with luxury-priced RAM makes some kind of sense.
- jsheard 2y ago> Maybe they'll change the form factor of the Mac Pro, too? Either that or kill the Mac Pro altogether, the current iteration is such a half-assed design and blatantly terrible value compared to the Studio that it feels like an end-of-the-road product just meant to tide PCIe users over until they can migrate everything to Thunderbolt. They recycled a design meant to accommodate multiple beefy GPUs even though GPUs are no longer supported, so most of the cooling and power delivery is vestigial. Plus the PCIe expansion was quietly downgraded, Apple Silicon doesn't have a ton of PCIe lanes so the slots are heavily oversubscribed with PCIe switches.
- pier25 2y agoI've always maintained that the M2 Mac Pro was really a dev kit for manufacturers of PCI parts. It's such a meaningless product otherwise.
- toasterlovin 2y agoIMO they had plans for a Mac Pro chip that didn’t work out, so they released the M2 version to let their Mac Pro customers know that they’re still committed to the product in the Apple Silicon era.
- pier25 2y agoCould be. I'm not sure if this current incarnation of the Mac Pro signals a commitment to the product though. Same performance as the Mac Studio but 2-3x the price just to get PCI slots.
- mrtksn 2y agoLet's say you want to have the absolute max memory(512GB) to run AI models and let's say that you are O.K. with plugging a drive to archive your model weights then you can get this for a little bit shy of $10K. What a dream machine. Compared to Nvidia's Project DIGITS which is supposed to cost $3K and be available "soon", you can get a specs matching 128GB & 4TB version of this Mac for about $4700 and the difference would be that you can actually get it in a week and will run macOS(no idea how much performance difference to expect). I can't wait to see someone testing the full DeepSeek model on this, maybe this would be the first little companion AI device that you can fully own and can do whatever you like with it, hassle-free.
- bloomingkales 2y agoThere’s an argument that replaceable pc parts is what you want at that price point, but Apple usually provides multi year durability on their pcs. An Apple ai brick should last awhile.
- behnamoh 2y ago> I can't wait to see someone testing the full DeepSeek model on this at 819 GB per second bandwidth, the experience would be terrible
- mrtksn 2y agoHow many t/s would you expect? I think I feel perfectly fine when its over 50. Also, people figured a way to run these things in parallel easily. The device is pretty small, I think for someone who wouldn't mind the price tag stacking 2-3 of those wouldn't be that bad.
- giancarlostoro 2y agoAt 9 grand I would certainly hope that they support the device software wise longer than they supported my 2017 Macbook Air. I see no reason to be forced to cough up 10 grand essentially every 7 years to Apple, that's ridiculous.
- moondev 2y ago> support for more than half a terabyte of unified memory — the most ever in a personal computer AMD Ryzen Threadripper PRO 3995WX released over four years ago and supports 2TB (64c/128t) > Take your workstation's performance to the next level with the AMD Ryzen Threadripper PRO 3995WX 2.7 GHz 64-Core sWRX8 Processor. Built using the 7nm Zen Core architecture with the sWRX8 socket, this processor is designed to deliver exceptional performance for professionals such as artists, architects, engineers, and data scientists. Featuring 64 cores and 128 threads with a 2.7 GHz base clock frequency, a 4.2 GHz boost frequency, and 256MB of L3 cache, this processor significantly reduces rendering times for 8K videos, high-resolution photos, and 3D models. The Ryzen Threadripper PRO supports up to 128 PCI Express 4.0 lanes for high-speed throughput to compatible devices. It also supports up to 2TB of eight-channel ECC DDR4 memory at 3200 MHz to help efficiently run and multitask demanding applications.
- Shank 2y ago> unified memory So unified memory means that the memory is accessible to the GPU and the CPU in a shared pool. AMD does not have that.
- mythz 2y agoAMD Ryzen AI Max SoC chips have that [1], but it maxes out at 128GB RAM. [1] https://www.amd.com/en/products/processors/laptop/ryzen/ai-300-series/amd-ryzen-ai-max-plus-395.html https://www.amd.com/en/products/processors/laptop/ryzen/ai-3...
- curt15 2y agoWhat about AMD Instinct accelerators like the MI300A[1]? Doesn't that use a single memory pool for both CPU and GPU cores? [1] https://www.amd.com/en/products/accelerators/instinct/mi300/mi300a.html https://www.amd.com/en/products/accelerators/instinct/mi300/...
- ryao 2y agoI suspect that they do not consider workstations to be personal computers.
- gatienboquet 2y agoNo benchmarks yet for the LLMs :(
- xyst 2y agoI might like Apple again if the SoC could be sold separately and opened up. It would be interesting to see a PC with Asahi or Windows running on Apple’s chips.
- deleted 2y ago[deleted]
- c0deR3D 2y agoWhen would Apple silicons made natively support for OSes such as Linux? Apple seemlingly reluctant to release detailed technical reference manual for M-series SoCs, which makes running Linux natively on Apple silicon challenging.
- bigyabai 2y agoProbably never. We don't have official Linux support for the iPhone or iPad, I would't hold out hope for Apple to change their tune.
- dylan604 2y agoThat makes sense to me though. If you don’t run iOS, you don’t have App Store and that means a loss of revenue.
- bigyabai 2y agoRight. Same goes for MacOS and all of it's convenient software services. Apple might stand to sell more units with a more friendlier stance towards Linux, but unless it sells more Apple One subscriptions or increases hardware margins on the Mac, I doubt Cook would consider it. If you sit around expecting selflessness from Apple you will waste an enormous amount of time, trust me.
- AndroTux 2y agoIf you don't run macOS, you don't have Apple iCloud Drive, Music, Fitness, Arcade, TV+ and News and that means a loss of revenue.
- dylan604 2y agoAs I replied in else where here, I do not run any Apple Services on my Mac hardware. I do on my iDevices though, but that's a different topic. Again, I could be the edge case
- 2y ago
- catlover76 2y ago[dead]
- NorwegianDude 2y agoThe memory amount is fantastic, memory bandwidth is half decent(~800 GB/s), and the compute capabilities are terrible(36 TOPS). For comparison, a single consumer card like the RTX 5090 is only 32 GB of memory, has 1792 GB/s memory and 3593 TOPS of compute. The use cases will be limited. While you can't run a 600B model directly like Apple says(cause you need more memory for that), you can run a quantized version, but it will be very slow unless its a MoE architecture.
- Havoc 2y ago>36 Tops Thats going to be the NPU specifically. Pretty much nothing on llm front seems to use NPUs at this stage (copilot snapdragon laptops aside) so not sure the low number is a problem
- BonoboIO 2y agoA factor of 100 faster in compute … wow. It will be interesting when somebody will upgrade the ram ram of the 5090 like they did with 4090s
- bilbo0s 2y agoThey’re a bit confused and not comparing the same compute. Pretty sure they’re comparing Nvidia’s gpu to Apple’s npu.
- NorwegianDude 2y agoI'm not confused at all. It's the real numbers. Feel free to provide anything that suggests that the TOPS of the GPU in M chips are faster than the dedicated hardware for it. But you can't, cause it's not true. If you think Apple added the neural engine just for fun then I don't know what to tell you. You have a fundamental flaw in your understanding of how both chips work. Not using the tensor cores would be slower, and the same goes for apples neural engine. The numbers are both for the hardware both have implemented for maximum performance for this task.
- llm_nerd 2y ago
- tempodox 2y agoI could salivate over the hardware no end, if only Apple software (including the OS) weren't that shoddy.
- bredren 2y agoApart from enabling an 120h update to the XDR Pro, does TB5 offer a viable pathway for eGPUs on Apple Silicon macbooks? This is a cool computer, but not something I'd want to lug around.
- mohsen1 2y agoFor AI stuff, 120GB/s is not really useful really...
- submeta 2y agoI am confused. I got an M4 with 64 GB Ram. Did I buy something from the future? :) Now why M3 now? Not M4 Ultra.
- seanmcdirmid 2y agoIt took them awhile to developed their ultra chip and this is what they had ready? I’m sure they are working on the M4 ultra, but they are just slow at it. I bought a refubished M3 max to run LLMs (can only go up to 70b with 4 bit quant), and it is only slightly slower than the more expensive M4 max.
- opan 2y agoHaven't the Max/Ultra type chips always come much later, close to when the next number of standard chips came out? M2 Max was not available when M2 launched, for example.
- SirMaster 2y agoAn Ultra has never come out after the next gen base model, let alone the next gen Pro/Max model before. M1: November 10, 2020 M1 Pro: October 18, 2021 M1 Max: October 18, 2021 M1 Ultra: March 8, 2022 ------------------------- M2: June 6, 2022 M2 Pro: January 17, 2023 M2 Max: January 17, 2023 M2 Ultra: June 5, 2023 ------------------------- M3: October 30, 2023 M3 Pro: October 30, 2023 M3 Max: October 30, 2023 ------------------------- M4: May 7, 2024 M4 Pro: October 30, 2024 M4 Max: October 30, 2024 ------------------------- M3 Ultra: March 5, 2025
- kridsdale1 2y agoSo about a year and a half delay for Ultra, but the M2 was an anomaly.
- ellisv 2y agoI'd also point out that there was a rather awkward situation with M1/M2 chips where lower end devices were getting newer chips before the higher end devices. For example, the 14 and 16-inch MacBooks Pro didn't get a M2 series chip until about 6 months after the 13 and 15-inch MacBooks Air. This left some professionals and power users frustrated. The M3 Ultra might perform as well as the M4 Max - I haven't seen benchmarks yet - but the newer series is in the higher end devices which is what most people expect.
- JacksCracked 2y ago[dead]
- ferguess_k 2y agoAh, if we can have the hardware and the freedom of installing a good Linux repo on top of it. How is Asahi? Is it good enough? I assume, that since Asahi is focused on Apple hardware, it should have an easier time figuring out drivers and etc?
- bigyabai 2y ago> How is Asahi? For M3 and M4 machines, hardware support is pretty derilict: https://asahilinux.org/docs/M3-Series-Feature-Support/ https://asahilinux.org/docs/M3-Series-Feature-Support/
- ferguess_k 2y agoThanks, looks like even M1 support has some gaps: https://asahilinux.org/docs/M1-Series-Feature-Support/#table-of-contents https://asahilinux.org/docs/M1-Series-Feature-Support/#table... I assume anything that doesn't have "linux-asahi" is not supported -- or any WIP is not supported. Wish I had the skills to help them. Targeting just one set of architecture, I think Asahi has more chances of success.
- bigyabai 2y agoIt's just not an easy task. I can't help but compare it to the Nouveau project spending years of effort to reverse-engineer just a few GPU designs. Then Nvidia changed their software and hardware architecture, and things went from "relatively hopeful" to "there is no chance" overnight.
- ferguess_k 2y agoI agree, it's a lot of work, plus Apple definitely is not not going to help with the project. Maybe an alternative is something like Framework -- find some good enough hardware and support it.
- _alex_ 2y agoapple keeps talking about the Neural Engine. Does anything actually use it? Seems like all the current LLM and Stable Diffusion packages (including MLX) use the GPU.
- gield 2y agoFace ID, taking pictures, Siri, ARKit, voice-to-text transcription, face recognition and OCR in photos, noise filtering, ...
- cubefox 2y agoThese have been possible in much smaller smartphone chips for years.
- stouset 2y agoPossible != energy efficient, which is important for mobile devices.
- cubefox 2y agoIf the energy efficiency of things like Face ID was indeed so far so bad that you need a more efficient M3 Ultra, how come Face ID was integrated into smartphones years ago, apparently without significant negative impact on battery life?
- 827a 2y agoVery curiously: They upgraded the Mac Studio but not the Mac Pro today.
- FloatArtifact 2y agoSo, what's the question if the M1/M2 Ultra was limited by GPU/NPU or more memory bandwidth at this point? I'm curious what instruction sets may have been included with the M3 chip that the other two lack for AI. So far the candidates seem to be NVIDIA digits, Framework Desktop, M1 64gb M2/M3 128gb studio/ultra. The GPU market isn't competitive enough for the amount of VRAM needed. I was hoping for an Battlemage GPU Model with 24GB that would be reasonably priced and available. The framework desktop and devices I think a second generation will be significantly better than what's currently on offer today. Rationale below... For a max spec processor with ram at $2,000, this seems like a decent deal given today's market. However, this might age very fast for three reasons. Reason 1: LPDDR6 may debut in the next year or two this could bring massive improvements to memory bandwidth and capacity for soldered on memory. LPDDR6 vs LPDDR5 - Data bus width - 24 bits, 16 bits Burst length - 24 bits, 15 bits Memory bandwidth - Up to 38.4 GB/s, Up to 6.7 GB/s - Camm ram may or may not be maintain signal integrity as memory bandwidth increases. Until I see it implemented for a AI use-case in a cost-effective manner, I am skeptical. Reason 2: - It's a laptop chip with limited PCI lanes and reduced power envelope. Theoretically, a desktop chip could have better performance, more lanes, socketable (Although, I don't think I've seen a socketed CPU with soldered RAM) Reason 3: In addition, what does hardware look like being repurposed in the future compared to alternatives? - Unlike desktop or server counterparts which can have a higher cpu core count, PCEe/IO Expansion, this processor with its motherboard is limited on re-purposing later down the line as a server to self-host other software besides AI. I suppose could be turned into a overkill, NAS with ZFS and HBA Single Controller Card in new case. - Buying into the framework desktop is pretty limited based on the form factor. Next generation might be able to include a 16x slot fully populated, a 10G nic. That seems about it if they're going to maintain the backward compatibility philosophy given the case form factor.
- gpapilion 2y agoI think this will eventually morph into apples server fleet. This in conjunction with the ai server factory they are opening makes a lot of sense.
- api 2y agoHalf a terabyte could run 8 bit quantized versions of some of those full size llama and deepseek models. Looking forward to seeing some benchmarks on that.
- zamadatix 2y agoDeepseek would need Q5ish level quantization to fit.
- ntqvm 2y agoDisappointing announcement. M4 brings a significant uplift over M3, and the ST performance of the M3 Ultra will be significantly worse than the M4 Max. Even for its intended AI audience, the ISA additions in M4 brought significant uplift. Are they waiting to put M4 Ultra into the Mac Pro?
- Acelar0 2y ago[dead]
- tuananh 2y agobut is it actually usable for anything if it's too slow. Has anyone has a ballpark number how many tokens per second we can get with this?
- cxie 2y ago512GB of unified memory is truly breaking new ground. I was wondering when Apple would overcome memory constraints, and now we're seeing a half-terabyte level of unified memory. This is incredibly practical for running large AI models locally ("600 billion parameters"), and Apple's approach of integrating this much efficient memory on a single chip is fascinating compared to NVIDIA's solutions. I'm curious about how this design of "fusing" two M3 Max chips performs in terms of heat dissipation and power consumption though
- samstave 2y ago"unified memory" funny that people think this is so new, when CRAY had Global Heap eons ago...
- ddtaylor 2y agoWhy did it take so long for us to get here?
- baby_souffle 2y agoJust a guess, but fabricating this can't be easy. Yield is probably higher if you have less memory per chip.
- astrange 2y agoIt's regular memory on separate chips.
- RachelF 2y agoSome possible groups of reasons: 1. Until recently RAM amount was something the end user liked to configure, so little market demand. 2. Technically, building such a large system on a chip or collection of chiplets was not possible. 3. RAM speed wasn't a bottleneck for most tasks, it was IO or CPU. LLMs changed this.
- 2y ago
- daft_pink 2y agoReally? M4 Max or M3 Ultra instead of M4 Ultra?
- aurareturn 2y agoWith an M3 Ultra going into the Mac Studio, Apple could differentiate from the Mac Pro, which could then get the M4 Ultra. Right now, the Mac Studio and Mac Pro oddly both have the M2 Ultra and same overall performance. https://x.com/markgurman/status/1896972586069942738 https://x.com/markgurman/status/1896972586069942738
- cynicalpeace 2y agoCan someone explain what it would take for Apple to overtake NVIDIA as the preferred solution for AI shops? This is my understanding (probably incorrect in some places) 1. NVIDIA's big advantage is that they design the hardware (chips) and software (CUDA). But Apple also designs the hardware (chips) and software (Metal and MacOS). 2. CUDA has native support by AI libraries like PyTorch and Tensorflow, so works extra well during training and inference. It seems Metal is well supported by PyTorch, but not well supported by Tensorflow. 3. NVIDIA uses Linux rather than MacOS, making it easier in general to rack servers.
- bigyabai 2y agoIt's still boiling down to hardware and software differences. In terms of hardware - Apple designs their GPUs for GPU workloads, whereas Nvidia has a decades-old lead on optimizing for general-purpose compute. They've gotten really good at pipelining and keeping their raster performance competitive while also accelerating AI and ML. Meanwhile, Apple is directing most of their performance to just the raster stuff. They could pivot to an Nvidia-style design, but that would be pretty unprecedented (even if a seemingly correct decision). And then there's CUDA. It's not really appropriate to compare it to Metal, both in feature scope and ease of use. CUDA has expansive support for AI/ML primatives and deeply integrated tensor/SM compute. Metal does boast some compute features, but you're expected to write most of the support yourself in the form of compute shaders. This is a pretty radical departure from the pre-rolled, almost "cargo cult" CUDA mentality. The Linux shtick matters a tiny bit, but it's mostly a matter of convenience. If Apple hardware started getting competitive, there would be people considering the hardware regardless of the OS it runs.
- cynicalpeace 2y ago> keeping their raster performance competitive while also accelerating AI and ML. Meanwhile, Apple is directing most of their performance to just the raster stuff. They could pivot to an Nvidia-style design, but that would be pretty unprecedented (even if a seemingly correct decision). Isn't Apple also focusing on the AI stuff? How has it not already made that decision? What would prevent Apple from making that decision? > Metal does boast some compute features, but you're expected to write most of the support yourself in the form of compute shaders. This is a pretty radical departure from the pre-rolled, almost "cargo cult" CUDA mentality. Can you give an example of where Metal wants you to write something yourself whereas CUDA is pre-rolled?
- fintechie 2y agoIMO this is a bigger blow to the AI big boys than Deepseek's release. This is massive for local inference. Exciting times ahead for open source AI.
- whimsicalism 2y agoit is absolutely not
- kcb 2y agoThe market for local inference and $10k+ Macs is not nearly significant enough to effect the big boys.
- bigyabai 2y agoI don't think you understand what the "AI big boys" are in the market for.
- rjeli 2y agoWow, incredible. I told myself I’d stop waffling and just buy the next 800gb/s mini or studio to come out, so I guess I’m getting this. Not sure how much storage to get. I was floating the idea of getting less storage, and hooking it up to a TB5 NAS array of 2.5” SSDs, 10-20tb for models + datasets + my media library would be nice. Any recommendations for the best enclosure for that?
- kridsdale1 2y agoIt depends on your bandwidth needs. I also want to build the thing you want. There are no multi SSD M2 TB5 bays. I made one that holds 4 drives (16TB) at TB3 and even there the underlying drives are far faster than the cable. My stuff is in OWC Express 4M2.
- perfmode 2y agoAre you running RAID?
- kridsdale1 2y agoYes RAID 5.
- Sharlin 2y ago> it can be configured up to 512GB, or over half a terabyte. Hah, I see what they did there.
- kridsdale1 2y agoIf they added 1 byte, it counts.
- Sharlin 2y agoThe "what they did here" part is they mean base-10 terabytes, and 512 GiB = 512·1024^3 bytes is indeed strictly more than 0.5 TB = 500·1000^3 bytes.
- aurareturn 2y agoYou can run the full Deepseek 671b q4 model at 40 tokens/s. 37B active params at a time because R1 is MoE.
- KingOfCoders 2y agoIn another of your comments it was "by my calculation". Now it's just fact?
- aurareturn 2y agoEasiest calculation.
- KingOfCoders 2y agoMe pulling numbers out of my hat, easiest calculation too.
- aurareturn 2y agoTroll.
- KingOfCoders 2y agoExactly. Sub-species Apple fanboy.
- aurareturn 2y agoWannabe CTO. Engineering manager at some random Wordpress real estate website and an ex-CTO at an "eBay subsidiary". Looks to be an misinformed AMD fanboy as well. Trolls HN trying to advertise a book that was probably written by ChatGPT.
- KingOfCoders 2y ago[flagged]
- screye 2y agoHow does the 500gb vram compare with 8xA100s ? ($15/hr rentals) If it is equivalent, then the machine pays for itself in 300 hours. That's incredible value.
- awestroke 2y agoA100 has 10x or so higher mem bandwidth
- egorfine 2y agoPer nvidia [1] A100 has memory bandwidth up to 2,039. So not 10x, more like 2x. [1] https://www.nvidia.com/content/dam/en-zz/Solutions/Data-Center/a100/pdf/nvidia-a100-datasheet-us-nvidia-1758950-r4-web.pdf https://www.nvidia.com/content/dam/en-zz/Solutions/Data-Cent...
- kristianp 2y agoThat's for 1, they were asking about 8x A100s, so 16x. H100 is double again.
- ummonk 2y agoIs the Mac Pro dead or are they waiting for M4 Ultra refresh it?
- mrcwinn 2y agoThe Mac Pro died a long, long time ago my friend.
- deleted 2y ago[deleted]
- ozten 2y agoWe've come a long way since beowulf clusters of smart toasters.
- perfmode 2y ago32 core, 512GB RAM, 8TB SSD please take my money now
- raydev 2y agoI know it's basically nitpicking competing luxury sports cars at this point, but I am very bothered that existing benchmarks for the M3 show single core perf that is approximately 70% of M4 single core perf. I feel like I should be able to spend all my money to both get the fastest single core performance AND all the cores and available memory, but Apple has decided that we need to downgrade to "go wide". Annoying.
- xp84 2y ago> both get the fastest single core performance AND all the cores I'm a major Apple skeptic myself, but hasn't there always been a tradeoff between "fastest single core" vs "lots of cores" (and thus best multicore)? For instance, I remember when you could buy an iMac with an i9 or whatever, with a higher clock speed and faster single core, or you could buy an iMac Pro with a Xeon with more cores, but the iMac (non-Pro) would beat it in a single core benchmark. Note: Though I used Macs as the example due to the simple product lines, I thought this was pretty much universal among all modern computers.
- raydev 2y ago> hasn't there always been a tradeoff between "fastest single core" vs "lots of cores" (and thus best multicore)? Not in the Apple Silicon line. The M2 Ultra has the same single core performance as the M2 Max and Pro. No benchmarks for the M3 Ultra yet but I'm guessing the same vs M3 Max and Pro.
- 1attice 2y agoNow with Ultra-class backdoors? https://news.ycombinator.com/item?id=43003230 https://news.ycombinator.com/item?id=43003230
- saagarjha 2y agoIt's unlikely that was a backdoor.
- ein0p 2y agoThat's all nice, but if they are to be considered a serious AI hardware player, they will need to invest in better support of their hardware in deep learning frameworks such as PyTorch and Jax. Currently the support is rather poor, and is not suitable for any serious work.
- divan 2y agoModel with 512GB VRAM costs $9500, if anyone wonders.
- junglistguy 2y ago[dead]
- m3kw9 2y agoInstantly hippa compliant high end models running locally.
- mlboss 2y ago$14K with 512gb memory and 16 Tb storage
- maverwa 2y agoI cannot believe I’m saying that, but: for apple that’s rather cheap. Threadripper boxes with that amount of memory do not come a lot cheaper. Considering what apples pricing when it comes to memory in other devices, 4K for the 96GB to 512GB upgrade is a bargain.
- jltsiren 2y agoIt's not that much cheaper that with earlier comparable models. Apple memory prices have been $25/GB for the base and Pro chips and $12.5/GB for the Max and Ultra chips. With the new Studios, we get $12.5/GB until 128 GB and $9.375/GB beyond that. If you configure a Threadripper workstation at Puget Systems, memory price seems to be ~$6/GB. Except if you use 128 GB modules, which are almost $10/GB. You can get 768 GB for a Threadripper Pro cheaper than 512 GB for a Threadripper, but the base cost of a Pro system is much higher.
- aurareturn 2y agoPudget system Threadripper 32core + 512GB of system RAM + RTX 4060ti is already $12,000.49. Meanwhile, this thing has a faster CPU, GPU, and 512GB of 800GB/s VRAM for $9,500.
- alok-g 2y agoTwo questions for the fellow HNers: 1. What are various average joe (as opposed to researchers, etc.) use cases for running powerful AI models locally vs. just using cloud AI. Privacy of course is a benefit, but it by itself may not justify upgrades for an average user. Or are we expecting that new innovation will lead to much more proliferation of AI and use cases that will make running locally more feasible? 2. With the amount of memory used jumping up, would there be a significant growth for companies making memories? If so, which ones would be the best positioned? Thanks.
- christiangenco 2y agoIMO it's all about privacy. Perhaps also availability if the main LLM providers start pulling shenanigans but it seems like that's not going to be a huge problem with how many big players are in the space. I think a great use case for this would be in a company that doesn't want all of their employees sending LLM queries about what they're working on outside the company. Buy one or two of these and give everybody a client to connect to it and hey presto you've got a secure private LLM everybody in the company can use while keeping data private.
- chamomeal 2y agoI’ll add to this that while I couldn’t care less about open AI seeing my general coding questions, I wouldn’t run actual important data through ChatGPT. With a local model, I could toss anything in there. Database query outputs, private keys, stuff like that. This’ll probably become more relevant as we give LLM’s broader use over certain systems. Like right now I still mostly just type or paste stuff into ChatGPT. But what about when I have a little database copilot that needs to read query results, and maybe even run its own subset of queries like schema checks? Or some open source computer-use type thingy needs to click around in all sorts of places I don’t want openAI going, like my .env or my bash profile? That’s the kinda thing I’d only use a local model for
- user3939382 2y agoHopefully homomorphic encryption can solve this rather than building a new hardware layer everywhere.
- epolanski 2y agoCan anybody ELI5 why aren't there multi gpu builds to run LLMs locally? It feels like one should be able to build a good machine for 3/4k if not less with 6 16GB mid level gaming GPUs.
- snitty 2y agoReddit's LocalLLama has a lot of these. 3090s are pretty popular for these purposes. But they're not trivial to build and run at home. Among other issues are that you're drawing >1kW for just the GPUs if you have four of them at 100% usage.
- coconut08 2y ago6 * 16 is still nowhere near 512gb of vram. On top of that that monster that you create requires hyper specific server grade hardware, will be huge, loud and pull down enough power to trip a circuit breaker. i'm sure most people would rather pay a 30 percent premium to get twice the ram and have a power sipping device that you can hold in the palm of your hand.
- crowcroft 2y agoKinda curious to see how man tok/sec it can crush. Could be a fun way to host AI apps.
- joshhart 2y agoThis is pretty exciting. Now an organization could produce an open weights mixture of experts model that has 8-15b active parameters but could still be 500b+ parameters and it could be run locally with INT4 quantization with very fast performance. DeepSeek R1 is a similar model but over 30b active parameters which makes it a little slow. I do not have a good sense of how well quality scales with narrow MoEs but even if we get something like Llama 3.3 70b in quality at only 8b active parameters people could do a ton locally.
- wewewedxfgdf 2y agoComputers these days - the more appealing, exciting, cooler desirable, the higher the price, into the stratosphere. $9499 What ever happening to competition in computing? Computing hardware competition used to be cut throat, drop dead, knife fight, last man standing brutally competitive. Now it's just a massive gold rush cash grab.
- hu3 2y agoIt doesn't even run Linux properly. Could cost half of that and it would still be uninteresting for my use cases. For AI, on-demand cloud processing is magnitudes better in speed and software compatibility anyway.
- dcchambers 2y agoThere are legitimate use cases for local LLMs. For example, I'll happily feed my entire directory of private notes/diary entries into an LLM running offline on my laptop. I would never do that with someone else's LLM running in the cloud.
- niek_pas 2y agoThe Macintosh plus, released in 1986, cost $2600 at the time, or $7460 adjusted for inflation.
- bigyabai 2y agoIt even came with an official display! Nowadays that's a $1,600-$6,000 accessory, depending on whether you own a VESA mount.
- WXLCKNO 2y agoYou take the top price of the top of the line newest pro chip apple produces and then make this argument?
- bustling-noose 2y agoThe MacBook Air with M4 chip 16gb ram and an amazing display and camera is just 999$. During back to school that will happen soon it’s 899$ with free AirPods. That’s really great value given how good the hardware is.
- martin_a 2y ago> Apple today announced M3 Ultra, the highest-performing chip it has ever created Well, duh, it would be a shame if you made a step backwards, wouldn't it? I hate that stupid phrase...
- wewewedxfgdf 2y agoThe good news is that AMD and Intel are both in good positions to develop similar products.
- dangoodmanUT 2y ago800GB/s and 512 unified ram is going to go stupid for llms
- minton 2y ago+ $4,000 to bump to 512GB from 96GB.
- ldng 2y agoWell, a shame for Apple, a lot of the rest of the world is going to boycott american products after such level of treacherousness.
- tap-snap-or-nap 2y agoAll this hardware but I don't know how to best utilize it because 1) I am not a pro, and 2) The apps are not as helpful which can make complex jobs easier, which is what old apple used to do really well.
- narrator 2y agoNot to rain on the Apple parade, but cloud video editing with the models running on H100s that can edit videos based on prompts is going to be vastly more productive than anything running locally. This will be useful for local development with the big Deepseek models though. Not sure if it's worth the investment unless Deepseek is close to the capability of cloud models, or privacy concerns overwhelm everything.
- gigatexal 2y ago16TB, 512gb ram, m3 ultra 15k+ usd. Wow. Did they say why there’s not an m4 ultra?
- teleforce 2y agoThunderbolt 5 (TB 5) is pretty handy, you can have a very thin and lightweight laptop, then can get access to external GPU or eGPU via TB 5 if needed [1]. Now you can have your cake (lightweight laptop) and eat it too (potent GPU). [1] Asus just announced the world’s first Thunderbolt 5 eGPU: https://www.theverge.com/24336135/asus-thunderbolt-5-external-gpu-graphics-xg-mobile-ces-2025 https://www.theverge.com/24336135/asus-thunderbolt-5-externa...
- ben-schaaf 2y agoExcept that you're stuck with macOS, so there aren't any drivers for NVIDIA, AMD or Intel GPUs.
- iamtheworstdev 2y agoand that no one is developing games for MacOS.
- rafram 2y ago(1) That’s obviously not actually true. (2) “No one” is developing games for Linux either, but the Steam Deck works great. Why? Wine, which you can run on macOS too.
- iamtheworstdev 2y agoAh, yes, you got me. You identified that other market that also no one cares about.
- smilebot 2y agoValve supports games on MacOS
- wpm 2y agoApple Silicon does not work with eGPU.
- emp_ 2y ago
- anArbitraryOne 2y agoCan't wait to run asahi on it
- DidYaWipe 2y agoHow do people feel about the value of the M3 Ultra vs. the M4 Max for general computing, assuming that you max out the RAM on the M4 version of the Studio?
- 827a 2y agoThe kinds of workloads that could truly leverage the M2 Ultra over the M2 Max were vanishingly small. When comparing the M3 Ultra to the M4 Max, that number gets even smaller, because the M4 Max will have ~15% higher single core perf. The insane memory available on M3 Ultra is its only interesting capability, but its still not big enough to run the series of largest open source LLMs. Hot take: You can tie yourself into six knots trying to spin a yarn about why the M3 Ultra spec is super awesome for some AI use-case, meanwhile you could buy a Mac Mini and like 200 million GPT-4o tokens for the cost of this machine that can't even run R1.
- LeoPanthera 2y agoI suspect most people running LLMs locally are unable to use the big cloud models for either legal or ethical reasons. If you could use gpt4, you would, it's just not that expensive.
- xedrac 2y agoNow let me run Linux on it natively without having to jump through hoops. That would be something...
- datadeft 2y agoApple today announced M3 Ultra, the highest-performing chip it has ever created I thought it was few weeks ago when M4 Max came by.
- apatheticonion 2y agoGod I wish Linux ran on Apple Silicon (with first class hardware support).
- walterbell 2y agoWe need more mainline Linux devs to work on Apple Silicon feature gaps, instead of expecting tiny AsahiLinux to roll support up the mountain alone.
- apatheticonion 2y agoFor sure. The work that Asahi have done is unbelievable, especially given the size of the team and the challenges they've faced. Would be amazing if there was more support from mainline devs (or better still, Apple directly).
- bustling-noose 2y agoI wonder if Apple needs to reconsider Xserve. While Apple probably have some kind of server infrastructure teams, making their own server infrastructure out of their own hardware and software sounds like something they could explore. The app ecosystem coupled with apples servers offered in the cloud or ones you could buy would be a very interesting service business they could get into. Apples App Store needs better apps given how much the hardware is capable of now especially with iPads using M chips. A cloud backed hardware and software service specially designed for the app ecosystem sounds very tempting. The hardware has evolved faster than software at Apple. It’s usually the opposite with most tech companies where hardware is unable to keep up with software.
- ballooney 2y agoI'm from the dark ages and am interested in this for non-AI things like CFD. What is the state of SDK support for these chips? Is there a nice rust or C++ library that abstracts the hardware and lets you just do very big Matrix multiplications?
- GypsyKing716 2y ago[flagged]
- cytocync 2y ago[dead]
- VVilhelmsen 2y agoWho is this made for? Who needs a personal computer this powerful? Not trying to be funny - it's a genuine question. Gamers don't generally use a mac because of the lack of games and I'm guessing those who are really into LLMs use Linux for the flexibility. Video editing can be done on much cheaper hardware. Very rich LLM enthusiasts who wants to try out mac?
- eric-burel 2y agoI don't think people into LLMs necessarily use Linux, most devs I see around use a mac, and I think I'll buy one and move out of Ubuntu if I start using them more seriously. The perfs are the key selling point as many professional use cases benefits from running LLMs locally.
- VVilhelmsen 2y agoI used to run Ubuntu with i3 and recently switched to a macbook air. I thought I would hate it coming from i3, but honestly when using the stage manager + tmux & nvim and betterTouchTool for keybinds it feels just as effective. The fact that fullscreen applications get their own desktop is nice too.
- kalleboo 2y agoModern video editing includes tasks such as AI upscaling and subtitle generation that can use lots of power
- tomovo 2y agoSwift developers.
- perfmode 2y agoI would love 32 cores for audio editing in RX 11.
- rperez333 2y agoContent creation usually, which consists of audio, photo, and video editing mostly. The hardware and software integration makes video editing on a Mac really superior, specially with their ProRes codec. You can get a good experience on a Windows or Linux machine with DaVinci Resolve, but that’s mostly because of the way better GPUs like the 4090/RTX series you’ve got at your disposal.
- jjuliano 2y agoCurrently, Docker does not support Metal GPUs. When running LLMs on Docker with an Apple M3 or M4 chip, they will operate in CPU mode regardless of the chip's class, as Docker only supports Nvidia and Radeon GPUs. If you're developing LLMs on Docker, consider getting a Framework laptop with an Nvidia or Radeon GPU instead. Source: I develop an AI agent framework that runs LLMs inside Docker on an M3 Max (https://kdeps.com https://kdeps.com).
- rtwld 2y agoPodman does support GLU acceleration through libkrun with virtio-gpu (venus) on Mac: https://podman-desktop.io/docs/podman/gpu https://podman-desktop.io/docs/podman/gpu
- asadalt 2y agohow is it in practice (if you have tried). I have some vulkan work and I am too lazy to setup a new ec2 for it.
- casey2 2y agoThey are going to have more memory than storage at this rate.
- maz1b 2y agoSurprised they didn't do an M4 Ultra. I really hope they don't do an M4 Ultra for the Mac Pro and add in this very undesirable kind of product matrix just for the sake of differentiation. I would be ok with an M3 Extreme in the Mac Pro, however.
- lincpa 2y ago[dead]
- enether 2y agoCan anyone with older Mac Studios/Minis comment - do you also notice a "throttling" of the hardware? I'm not sure if this is me not maintaining it properly (e.g fans having dust block them) - but I've always got this sense that Apple throttles their older devices in some indirect ways. I experience it the most with iPhones - my old iPhone is pretty slow doing basic things despite nothing really changing on it (just the OS updating?) So my only concern with this is - how many years until it's slow enough to annoy you into buying a new one?
- BobAliceInATree 2y ago> (just the OS updating?) "Just the OS updating" is not insignificant. Software developers, in general, are not known for making sure latest versions of their software run smoothly on older hardware. Also, performance on iPhones is throttled when your battery is very old. There was a whole class-action lawsuit about it. https://support.apple.com/en-us/106348 https://support.apple.com/en-us/106348
- scarface_74 2y agoYou realize the alternative is the iPhone shutting down completely?
- bigyabai 2y agoNo, I don't. There are multiple alternatives including (though not limited to) opt-in battery protection, removing battery DRM to enable hardware repairs, or declaring a first-party recall on the faulty units to replace components that are damaging to the hardware. Conspicuously, Apple just so happened to pick the one that encouraged people to upgrade the entire phone. You know, an entire phone that is otherwise functional without arbitrary restrictions by the OEM.
- scarface_74 2y agoAt the time, battery replacement from Apple or an authorized dealer was $69. https://support.apple.com/iphone/repair/battery-replacement https://support.apple.com/iphone/repair/battery-replacement There is no “DRM” in their battery. If you had the wherewithal, you could do it yourself https://www.ifixit.com/Guide/iPhone+6s+Battery+Replacement/56607 https://www.ifixit.com/Guide/iPhone+6s+Battery+Replacement/5... The units weren’t “faulty” all batteries degrade over time.
- runeks 2y agoIs the new Mac Studio the only product this chip will go into?
- k_sze 2y agoWhy did Apple call it M3 Ultra when it's supposed to be more performant than the current top of the line M4 Max? Why not just call it M4 Ultra?
- gnabgib 2y agoBecause it's two M3 Max chips fused with a high-speed link? The M4 Ultra will presumably be comprised of two M4 Max processors fused similarly (next year).
- merillecuz56 2y ago[dead]
- teknologist 2y agoSomething nobody mentions is the power draw. This kind of compute horsepower for so little power usage is outstanding.