15 ms·

Nvidia RTX Spark

• smcleod 5mo ago
  Pretty low bandwidth and given how terrible nvidias software has been with the DXG et el, I would not put much faith into this.
• SilverElfin 5mo ago
  It all sounds good on paper. But I have trouble believing Windows can be a good platform for this. Microsoft has lost all trust after inserting ads into windows, slowly removing power user features, and exploiting every dark pattern they can. And for years, the ARM based Windows laptops have been useless due to app compatibility issues. Why would this change now? Is it priced to be a lot cheaper than Apple’s laptops? Or is this a niche product for AI developers basically?
  • try-working 5mo ago
    Hopefully MSFT would look at this as a do or die system, and go all in on improving the user and ownership experience. Will they? Not so sure.
    • jfim 5mo ago
      That's what they're working on, in theory, with Windows K2.
      • fhn 5mo ago
        I would never trust Microsoft. Their next drama is revoking Office 2019 perpetual licenses https://www.youtube.com/watch?v=KRnno9VIZx0 https://www.youtube.com/watch?v=KRnno9VIZx0. It never ends with them because they know they have you by the balls.
        • twilo 5mo ago
          I trust them on a daily basis. No issues thus far..
    • Gigachad 5mo ago
      Microsoft sees windows purely as a platform to sell AI products these days.
  • sorry_outta_gas 5mo ago
    [dead]
  • __atx__ 5mo ago
    The "gaming" take is a strange one indeed for an ARM platform. Hopefully they (Microsoft or Nvidia?) put some real effort into the translation layer. They claim modern AAA games, but it is possible they strongarmed the developers to make them an ARM build for a few select titles...
    • SilverElfin 5mo ago
      Yep. I noticed the press releases talk about all the partners they have. It seems like a desperate attempt to manufacture a consensus to invest in this new hardware instead of leaving it sort of abandoned like the other Windows ARM stuff. But the problem is that these attempts end up having a few very visible apps working on the architecture and others not actually doing anything substantial. Sure the graphics capabilities are probably very good. But if you’re a game developer who has traditionally built on Windows on x86 chips, would you want to invest in this new chip or invest in making games for the Apple ecosystem? Aren’t there more new customers to reach in the Apple world than this new Nvidia world?
      • andsoitis 5mo ago
        > But if you’re a game developer who has traditionally built on Windows on x86 chips, would you want to invest in this new chip or invest in making games for the Apple ecosystem? Windows and the new chip. Higher developer productivity and higher chances of a substantial audience.
    • satvikpendem 5mo ago
      It's clear gaming was not a major concern, it's just "good enough" for someone running AI models and occasionally wants to play some games, not made to primarily play games.
  • bentcorner 5mo ago
    Anecdotally Windows ARM works fine for me, although to be honest most of my work is command line + browser anyway. WSL works like a treat. Steam installs and most lower end games also play fine on my ARM laptop too. Games that require kernel anticheat don't work. I think they make a great "second device" where you have something meatier to fall back to if something doesn't quite work right. I'm not sure if it's ready to take on the "main device" role just yet. But it's a far far better experience than the Surface RT days.
  • satvikpendem 5mo ago
    Who cares about Windows, the goal is to run local AI models similar to AMD Strix Halo and Apple Silicon machines. The OS is honestly a distant last concern as long as the models work well, as you could put Linux on these too, but not sure how well wake lock works.
  • TreeInBuxton 5mo ago
    A lot of the app compatibility issues on current machines are down to Qualcomm's poor drivers - the actual core bits are mostly okay.
• jqbd 5mo ago
  They made their own x86 CPU? Or was that part outsourced? Ok ARM MediaTek.
  • try-working 5mo ago
    ARM cpu made by MediaTek.
    • zamadatix 5mo ago
      But probably worth clarifying it's not a typical "MediaTek CPU" some might assume by that. It has Nvidia's customized ARM CPU implementation + their GPU.
      • TiredOfLife 5mo ago
        This has off-the-shelf Arm cores.
    • Bulat_Ziganshin 5mo ago
      I think that Nvidia made GPU and CPU, and Mediatek made other parts of SoC necessary for a notebook. Grace is Nvidia's own CPU ARM core
      • SomeHacker44 5mo ago
        I believe Grace is an ARM designed core. Vera is the nVidia designed core.
• boredatoms 5mo ago
  Is this just dgx spark, but a laptop?
  • pella 5mo ago
    yes, same chip + Windows + Screen - ConnectX-7 Smart NIC
    • zer0zzz 5mo ago
      What about the desktop version? It seemed like it is not a dgx since it has the CPUs cores done by mediatek
      • pipyakas 5mo ago
        desktop is GB300, not GB10 like Spark
        • KeplerBoy 5mo ago
          they also announced a GB10/N1X windows desktop mini PC.
        • wtallis 5mo ago
          GB300 is nominally "available" in desktop form factor workstations priced around $100k. That's a few orders of magnitude away from the ordinary desktop PC market that consumers participate in.
          • zer0zzz 5mo ago
            Yeah this is why it’s important to get something with similar programmability for less money. I don’t need the power of a gb300 just to do experiments with tma or “tcgen05” instructions
      • Bulat_Ziganshin 5mo ago
        They didn't say that Mediatek made the cpu sores. Grace is NVidia's own cpu arm cores. I bet that Mediatek made other parts of SoC necessary for a notebook
• cyanydeez 5mo ago
  competitor is already on the market and is x86: AMD AI 395+ bechmarks with DGX arnt spectacular for NVIDIAs software and CUDA lead. wouldnt count on this being a price/compute challenger. especially with overpriced VRAM.
  • xyzzy123 5mo ago
    Or like a m4 max? This thing has <300GB/s vs the max with 550GB/s All those CUDA cores in the sparks but they're starved for memory bandwidth. I am still waiting for NVidia to release a system that legit beats 3090 maxxing for the home gamer...
    • moondev 5mo ago
      Spark: OS: Windows/Ubuntu Mbw: 300GB/s Cuda cores: 6000 GPU accelerated containers: yes M5 max: OS: macOS Mbw: 600GB/s Cuda cores: 0 GPU accelerated containers: no
      • xyzzy123 5mo ago
        I feel like the shape of the market right now for "home lab" inference is: The sparks are good if your ultimate plan is to spend even more on NVidia hardware in future to run your dev setups at usable speeds. Or, you're developing for a work cluster. If you mainly want to run local models at acceptable speeds portably, buy a mac with lots of RAM. If you’re happy with non-portable / racked, buy 3090s (dense) or mac studios (MoEs). Buy newer cards if you are restricted on power or slots. If you are rich, buy a6000 blackwells.
  • SilverElfin 5mo ago
    Is CUDA really a lead for long? Aren’t all the latest competitive approaches avoiding all the standard software stacks and writing deeply customized software that is very directly tied to whatever hardware they use? And is it really a way to lock in people? With AI coding tools, isn’t it trivial to write software on top of CUDA and rewrite it to target some other hardware?
• renoir 5mo ago
  So basically Cerebras style?
  • trvz 5mo ago
    No.
  • KeplerBoy 5mo ago
    Not at all. This is a more like what Apple has been doing the past few years. A bunch of decent arm cores paired with a beefy integrated GPU.
• zmk5 5mo ago
  I really like this, but I think the reason Apple Silicon took off was that Apple sort of forced devs to support ARM. Not sure if Microsoft can do the same for Windows…
  • trvz 5mo ago
    They didn’t though. Rosetta 2.
    • ptole_my 5mo ago
      rosetta is a relatively short term solution. will be supported up to macOS 28
  • supersing 5mo ago
    Developers weren’t really “forced” to support ARM. They simply recognized that all future Macs would be ARM, whereas most new PCs would continue to run on x86. So the incentive to adopt ARM was much weaker on the PC side.
    • ryukoposting 5mo ago
      > Developers weren’t really “forced” to support ARM. They simply recognized that all future Macs would be ARM One might call this "forcing"
  • aa-jv 5mo ago
    Microsoft can do the same for windows - they need to address the fat bundle solution that Apple came up with, but for Windows, though ..
• SilverElfin 5mo ago
  Some other relevant discussions and sources … NVIDIA and Microsoft Reinvent Windows PCs for the Age of Personal AI https://news.ycombinator.com/item?id=48352705 https://news.ycombinator.com/item?id=48352705 NVIDIA DGX Station for Windows Puts a Trillion-Parameter AI Supercomputer on Every Enterprise Desk https://news.ycombinator.com/item?id=48352691 https://news.ycombinator.com/item?id=48352691 Introducing Surface Laptop Ultra: Made for world makers https://news.ycombinator.com/item?id=48352627 https://news.ycombinator.com/item?id=48352627 Introducing a powerful new chapter for Windows PCs, accelerated by NVIDIA RTX Spark https://news.ycombinator.com/item?id=48352693 https://news.ycombinator.com/item?id=48352693
  • EugeneOZ 5mo ago
    2 comments in total there
• mastermage 5mo ago
  Is this finally Macbook Chip Efficiency coming to Windows or will it just be shittier compatibility for slightly better battery life?
  • zer0zzz 5mo ago
    I heard leaked geekbench putting it behind the m3, which is couple years old now. All I care about is if I can get one of these for significantly less than a dgx and get Linux on it for some cuda Blackwell kerneling.
  • deleted 5mo ago
    [deleted]
• timpera 5mo ago
  We'll need to wait for the benchmarks, but this looks great! Windows 11 ARM64 is already amazing, and if these really are an upgrade from the Qualcomm chips we're going to have even better laptops on the market.
• throwa356262 5mo ago
  I have no idea how powerful or power efficient these guys are, but this seems to be the first step in a bigger push towards Windows on ARM (without loosing gaming). I think more announcements will follow soon from other companies.
  • jauntywundrkind 5mo ago
    It's worth noting that Nvidia power management on Linux has been absymal. There also aren't any of the usual power management options to see how much power things are using, which is quite atypical for a modern system. Nvidia really threw stuff over the wall with the DGX Spark release. They don't seem to really care. I sort of think they'll spend a little more time on Windows, where there's no pesky upstreaming to do and they can just do whatever, but man, it's such typical hubris from Nvidia to build such an expensive box with good chips but make it basically unsupportable and roasty hot all the time. You also generally have to run an ever more stale two year old Ubuntu derived DGX OS to get anywhere, with bespoke kernel and drivers all. None of it is well supported, none of it just works like a comparable PC or even well behaved arm system would. As for other ARM, there were rumors AMD Sound Wave is/was going to be a ~10W arm APU, but there hasn't been much said about it lately. Honestly given the ram crunch, it's maybe just not worth trying to build a system with a cheap core, if the rest of your costs are going to stay so stratospheric. https://www.techpowerup.com/341848/amd-sound-wave-arm-powered-apu-appears-in-shipping-manifests https://www.techpowerup.com/341848/amd-sound-wave-arm-powere...
  • fmajid 5mo ago
    My DGX Sparks are the first and only devices I have with 200W USB-C PD. Low power by AI workstation standards, but intolerable in a laptop.
    • MoonWalk 5mo ago
      Intolerable? Why?
      • ternaryoperator 5mo ago
• ma2kx 5mo ago
  Unified RAM means its soldered to the mainboard, right? I'm not sure if I like this. Sure for a laptop this might be not a big problem but if this ARM ecosystem is a success it will spread to desktop computers and I fear we could lose the existing modularity.
  • Skinney 5mo ago
    "Unified" means that it's shared between CPU and GPU, I believe. But yes, it tends to be soldered on.
  • Rekindle8090 5mo ago
    [dead]
  • Bulat_Ziganshin 5mo ago
    No, but LPDDR means soldered, there are no LPDDR dimms
    • debugnik 5mo ago
      There's LPCAMM2, but it's very recent. The Framework Pro laptop supports it, for example, although only on the Intel variant.
  • phcreery 5mo ago
    I think unified RAM means soldered to the SoC, which is in turn soldered to the mainboard
• hgoel 5mo ago
  Looks like the MSI one might be a 2-in-1, if it has good stylus support I might have a good candidate for an upgrade, thought my ~3-4 year old Galaxy Book is holding up alright for now.
• donkeylazy456 5mo ago
  hope nvidia support driver better than qualcomm. also hope they support linux soon.
• officerk 5mo ago
  This will crush the M5 Max going by the numbers. I'm curious to see how much they end up costing
  • Rekindle8090 5mo ago
    M5 max is 3x stronger and 50% more power efficient. nice try though.
    • spwa4 5mo ago
      ... but you'll be rewriting inference for any model that isn't a well-known LLM. Yourself.
      • wbolt 5mo ago
        AI coding agents can do that pretty nicely already and it will only (slowly) improve over time.
  • Tiberium 5mo ago
    It won't, the top tier RTX Spark has the same exact CPU and GPU as DGX Spark, so you can check DGX Spark CPU benchmarks to see how it fares. Spoiler: it's about M3 Max level. And they're only coming this fall.
  • aenis 5mo ago
    Nah, still ~300GB/s memory bandwidth. That will be slower than the M5 max, by a wide margin for LLM inference.
• pseudosavant 5mo ago
  This may finally be the chip family ARM on Windows has always needed. Qualcomm's chips have always been dogs with slow off-the-shelf ARM CPU cores that have pathetic single-threaded performance compared to x86 AMD/Intel or ARM Apple Silicon designs.
  • TiredOfLife 5mo ago
    Qualcomm Snapdragon x1 and upcoming x2 use their Oryon core and have much faster single-thread performance than Intel/Amd and this nvidia soc that uses off-the-shelf arm cores
    • pseudosavant 5mo ago
      That wasn't true of the X1, but apparently the X2 (which is only in a single device so far) does appear to finally be fast. The first Windows ARM CPU to be faster than any of its x86 rivals. Competitive with Apple Silicon single-thread performance even. I was disappointed to see that the RTX Spark has the ARM cores from the DGX Spark. I was hoping it had their new in-house developed cores that Nvidia is starting to use on their latest gen server parts. They look really fast. That said, if RTX Spark has CPU performance like the DGX Spark, it will be almost as fast as the top AMD/Intel parts.
  • BoggleOhYeah 5mo ago
    These chips also appear to be using off-the-shelf ARM cores.
  • kcb 5mo ago
    This will likely have worse single threaded performance than recent Qualcomm CPUs.
  • deleted 5mo ago
    [deleted]
  • pseudosavant 5mo ago
    For reference, this is just a single benchmark, but as an idea of each vendor's top mobile CPU single-threaded performance: Geekbench Single Thread Score: - DGX Spark (same CPU as RTX Spark): 3125 - Snapdragon X1 Elite: 2950 - Snapdragon X2 Elite Extreme: 4050 - AMD Ryzen 9 9955HX: 3225 - Intel Core Ultra 9 290HX Plus: 3175 - Apple M5 Max: 4350 I'm happy to be wrong about Qualcomm's latest X2 chip performance, even if it is shipping in only a single product so far. Their previous best was the lowest in this list.
• minraws 5mo ago
  Awesome, won't be buying it all at current prices but once they calm down, I will very much like to get one. Around 2-3K USD something with a good GPU + CPU + 128GB of integrated RAM is just going to be an awesome experience. Considering Mac options are north of 5K+ even on a regular day.
  • Tiberium 5mo ago
    DGX Spark is $4700, so I kind of doubt that RTX Spark's top configs will be cheaper than that.
    • KeplerBoy 5mo ago
      The DGX also contains the 200 GbE networking and linux support.
      • Tiberium 5mo ago
        Laptops will also have to contain a much tighter configuration, display, keyboard, camera, etc ;)
        • minraws 5mo ago
          there is desktop variant as well
      • fmajid 5mo ago
        The ConnectX 7 2x200 Gbps networking card in the DGX Spark alone is worth $700
        • KeplerBoy 5mo ago
          To be fair the connectx-7 in the spark can't even push 2x200 Gbps since it is connected via 4 pcie lanes.
          • 5mo ago
• Tiberium 5mo ago
  For anyone curious to know how this will fare against Macbooks, at least in CPU perf: DGX Spark has the exact same GPU and CPU as the top RTX Spark laptops will, so you can just directly compare from that. Of course, DGX Spark is a miniPC, so laptops will likely be slower due to power limits/throttling.
  • FuriouslyAdrift 5mo ago
    DGX Spark is also $4700
  • exabrial 5mo ago
    UEFI, display panels, wifi, storage controllers, etc would be what I'm worried about. I doubt Microsoft is going to make it easy.
  • siquick 5mo ago
    DGX Spark is really poor at inference due to the memory bandwidth so hopefully they’ve fixed that before touting this as a way to run local models.
    • wtallis 5mo ago
      I think DGX Spark has poor memory bandwidth because these laptops were the plan all along. NVIDIA didn't want to commit to the extra costs of a 512-bit memory bus for their first laptop SoC, so they went with the more modest 256-bit bus, same as AMD did for Strix Halo.
• t_mahmood 5mo ago
  After nvidia's many years of neglecting Linux, paired with direct Microsoft's involvement? Are we going to trust them, to allow installing Linux in these easily? I don't think so. This most likely be a winmodem situation, again
  • TiredOfLife 5mo ago
    DGX Spark has the same soc and ships with Ubuntu
    • t_mahmood 5mo ago
      Okay, but still it's highly skeptical trusting MS, and NVIDIA.
    • lern_too_spel 5mo ago
      It ships with DGX OS 7, which includes Ubuntu's 24.04 repos. It is not using mainline Ubuntu, and if you want to run Ubuntu 26.04, you'll have to do some work.
  • bigyabai 5mo ago
    [dead]
• rsolva 5mo ago
  Will NVIDIA get a monopoly on providing laptops and desktops with a lot of RAM going forward?
  • nycdatasci 5mo ago
    No. You can get a PowerBook today with 128 GB ram. https://www.bhphotovideo.com/c/product/1957120-REG/apple_mbp_m5p_175_16_macbook_pro_m5.html https://www.bhphotovideo.com/c/product/1957120-REG/apple_mbp...
    • edtechdev 5mo ago
      Or get an AMD 395 laptop or mini PC for half the price of an equivalent mac device
      • berbec 5mo ago
        https://onexplayerstore.com/products/onexplayer-super-x?variant=51917402538278 https://onexplayerstore.com/products/onexplayer-super-x?vari... $3649 with 128GB of ram
      • igravious 5mo ago
        https://www.bosgamepc.com/products/bosgame-m5-ai-mini-desktop-ryzen-ai-max-395?sku=18073504178329773749154095 https://www.bosgamepc.com/products/bosgame-m5-ai-mini-deskto... Bosgame M5 AI Mini Desktop Ryzen AI Max+ 395 96GB variant €1.800,95 (sold out) 128GB+2TB variant €2.401,95 (in stock) I have the latter, it's fantastic
        • artificialLimbs 5mo ago
          $600 for 32GB ram seems bananas
          • riknos314 5mo ago
            Unfortunately in the current market 32GB of ddr5 seems to run about $400 as 2x16gb DIMMS, and even more for 1x32GB DIMM (higher density chips are more expensive). So $600 really isn't much over market price, especially considering strix halo uses 8000MHz ram instead of the typical 6000 found in consumer dimms.
• nokeya 5mo ago
  It was wintel (windows + intel) before. This will be what? Windia? Wintek?
  • grassfedgeek 5mo ago
    Nvindows
  • igravious 5mo ago
    Nvidiows
  • Geee 5mo ago
    Winvidia
  • MoonWalk 5mo ago
    Nvideous
• PeterStuer 5mo ago
  It's been almost 30 years, and a single letter changed. When will we get the Sparkstation, the UltraSpark and the SuperSpark?
  • a1o 5mo ago
    SuperSpark and then UltraSpark. And then we can get SparkCube, Sparkii, and SparkiiU.
    • pantulis 5mo ago
      I'm personally waiting for the OpenSpark.
      • rudros 5mo ago
        https://en.wikipedia.org/wiki/OpenSPARC https://en.wikipedia.org/wiki/OpenSPARC
      • KingFelix 5mo ago
        And the top tier QuantumSpark?
      • phcreery 5mo ago
        I'm waiting for the AllSpark
    • anakaine 5mo ago
      With competition from the MegaSpark and SparkGenesis.
    • m463 5mo ago
      you forgot Xerox sPARC with guis, ethernet, laser printers, ...
  • happosai 5mo ago
    Will we get enterprise ready open firmware too instead of this "we missed DOS so we invented UEFI" for boot firnware?
• hs86 5mo ago
  I am wary of those ARM-based Windows machines because I am unsure how good the ongoing driver support for those SoCs will be. Will they even outlive the Windows version they currently ship with? Looking at devices like the NVIDIA Shield gives me some hope that NVIDIA will be better than Qualcomm here. I just hope this is not a case where the OEM has to purchase X years of driver support from the chip vendor beforehand, and that NVIDIA will provide support directly itself.
  • jwlake 5mo ago
    I would love a RTX Spark Shield. ;p
• toksum 5mo ago
  [flagged]
• sylware 5mo ago
  [flagged]
  • twobitshifter 5mo ago
    Right, the export controls are only forcing Chinese AI to innovate, build their own fabs, and make training and inference more efficient. The end game of this will be NVIDIA chips won’t be wanted because you can get a $50 chinese chip running a ternary model that is competitive with claude in English and is much better in Mandarin.
    • pitched 5mo ago
      I would order that in a heartbeat. Even if it required proprietary Chinese-government drivers. I would try to segregate in a VM without internet or something. Please make this happen! Tokens cost too much in the current system.
    • adrian_b 5mo ago
      The US government has failed to learn from its own history. 60 years ago the US government had forbidden the export of fast computers to France, with the hope that this sanction will prevent the French from developing thermonuclear bombs. The result was that the French state (which at that time was lead by de Gaulle, not much less autocratically than China) subsidized some of their computer manufacturers, which previously could not compete with the American companies like IBM and CDC, and also their semiconductor manufacturing industry, which had to provide the components for the locally-made computers. Eventually, the French produced TTL circuits and mainframe computers made with them, and finally they also made thermonuclear bombs. So the American "sanctions" against France have been a complete failure and have been great for the French industry of semiconductors and computers. Many years later, when USA no longer had export restrictions towards France and the French state no longer protected their industry, the French industries of integrated circuits and computers have been greatly reduced, their companies either becoming bankrupt or being bought or merged into multinational companies.
      • sylware 5mo ago
• LatencyKills 5mo ago
  First: > "Our goal is to deliver unmetered intelligence to every home and every desk with Windows," said Satya Nadella, chairman and head of Microsoft. Then: > However, Ian Fogg, Research Director at industry analyst firm FDM CCS Insight said the change was "likely to come with a significant price tag" and Nvidia would be targeting "those looking for workstation-class performance". So... not every desk with Windows.
  • pitched 5mo ago
    First, make it possible. Then, expand the market. The early adopters help pay R&D for later efforts. Every desk is a good goal, even if not hit by the first doodad. It just feels too much like what they said about Apple II and early Windows. A play at nostalgia instead putting real thought into it.
    • LatencyKills 5mo ago
      I was an engineer at both MS and Apple, and wholeheartedly agree with you. My question is, what happens to the people who use RTX cards for gaming? This new solution isn't meant for that. Do they need an "AI accelerator" and a gaming-centric GPU?
  • netdevphoenix 5mo ago
    The constant deliberate conflagration of LLMs with general intelligence is so grating.
  • cryo32 5mo ago
    I don’t know anyone other than a very small but vocal minority who will give a shit about this. Even in the analytics side most of the stuff is some shonky ass numpy or excel gank. I don’t know what the market is. I just can’t see it.
• comandillos 5mo ago
  So they have basically reused the same hardware as in the DGX Spark (GB10)... That chip isn't great for LLM inference actually. https://www.techpowerup.com/gpu-specs/gb10.c4342 https://www.techpowerup.com/gpu-specs/gb10.c4342 https://www.nvidia.com/en-us/products/rtx-spark/ https://www.nvidia.com/en-us/products/rtx-spark/
  • joe_mamba 5mo ago
    >That chip isn't great for LLM inference actually. Why do I have the feeling it's been intentionally made to be bad in order to get you on to their most pensive datacenter gear.
    • ekidd 5mo ago
      It's probably more that LLM inference speed comes from having a large amount of fast RAM. And fast RAM is brutally expensive right now. At this point, your cost-efficient options include used 3090s, "frankenrigs" using recycled data center cards, and a handful of "workstation" class cards, where the originally high margins and the long enterprise purchasing cycles have kept prices from going up too fast. In contrast, a lot of these "personal" AI systems are basically a GPU-like core wired to larger amounts of slow RAM. Which is still semi-affordable. Generally speaking, they make for OK chatbots but extremely slow coding agents. Whereas you can run a modestly useful coding agent at reasonable speed on a 3090. So yeah, a lot of these systems are bit scammy. But not because it's a secret conspiracy to protect data center cards. Rather, there simply isn't enough fast RAM in the entire world. So they'll flog you disappointly slow RAM instead. TL;dr: Might be useful for some use cases, but benchmark very carefully.
  • ewklwekl 5mo ago
    It is great for inference for single user/single session. it is not replacement for graphical accelerator, that run several concurrent inference sessions in parallel. Basically the same tradeoff as macmini with unified memory.
  • general_reveal 5mo ago
    The RTX GPU laptops run very hot. Even though they are pound for pound better, it’s just runs too hot for local llm usage for me at least. Prefer Macs for this. A lot of AMD cards also run cooler. I wonder if undervting would help with smaller models and heat.
• PunchyHamster 5mo ago
  The fact they advertise it as some step forward in PCs is outright bizzare. It's just worse Strix Halo, as you are landing square in middle of Windows ARM problems
  • Iolaum 5mo ago
    Strix Halo chips have around 210+ GB/sec gpu memory bandwidth and announcements put the new nvidia chip at around 300GB/sec gpu memory bandwidth. I 'd say that is an improvement if you want to run local llm inference. Still well below with what you can achieve with Apple chips though.
• agnosticmantis 5mo ago
  How would these compare to a MacBook Pro M5 in terms of performance and price?
• eigenspace 5mo ago
  I'm surprised they released this thing. Brand perception is probably a lot more important to Nvidia than whatever sales they could get from this thing, and if it's basically just DGX Spark, it's likely to underwhelm. I've heard there's still a large backlog of both software problems, and hardware problems with the platform. The software problems could be fixed with time, but they'll still give a shitty first impression. I'd have thought Nvidia would just bury this and try again with a successor run of silicon with a new design. This thing seems practically destined to just be a repeat of the Snapdragon laptop debacle.
  • fg137 5mo ago
    I cannot think why someone would run those workflows on a Windows laptop, unless someone has way too much money to spend.
    • bigfishrunning 5mo ago
      > someone has way too much money to spend. that's what nvidia is hoping for
    • thinkingtoilet 5mo ago
      If the workload is offloaded to the chip, why would the host platform matter?
      • fg137 5mo ago
        Lots of machine learning workflows support Linux better than Windows, if they run on Windows at all. (e.g. https://docs.vllm.ai/en/latest/getting_started/quickstart/ https://docs.vllm.ai/en/latest/getting_started/quickstart/ ) DGX Spark runs Linux, and nobody is going to install Windows on that machine. This laptop got it backwards. If someone decides to run Ollama for local inference with this laptop, they fit perfectly into the "has too much money to waste" bracket, which is addressed by a few other comments in the discussion.
        • 5mo ago
• chris_money202 5mo ago
  It’s a step in the right direction, but there’s still a long ways to go in terms of smaller LLMs ability and hardware costs
• asimovDev 5mo ago
  >Lenovo, HP, Dell and Apple accounted for almost 75% of the world's PC market in the first three months of this year, according to research firm Gartner. https://www.gartner.com/en/newsroom/press-releases/2026-4-10-gartner-says-worldwide-pc-shipments-increased-4-percent-in-first-quarter-of-2026 https://www.gartner.com/en/newsroom/press-releases/2026-4-10...
• dom96 5mo ago
  I’m getting more and more convinced that we will end up running LLMs in our personal computers. Which makes me wonder where Anthropic/OpenAIs moats will come from.
  • eigenspace 5mo ago
    If we do, it won't be on this chip.
  • itake 5mo ago
    My biggest concern with local LLMs is there just isn't enough RAM or HD space to run multiple models, and the generic LLMs are too generic...
  • VMG 5mo ago
    Convince me 1. in order to run LLMs, especially the best ones, you need complicated devices which are expensive 2. if you buy one for your personal use, you are probably not going to utilize it all the time and it will be idle a lot It seems to me that it will always be more economical that the LLM-running devices are in a datacenter where it is easier to make sure they are always utilized
    • nerbert 5mo ago
      Just like cloud vs private server. It'll be based on use case.
    • KeplerBoy 5mo ago
      It's inevitable. What might be a prosumer device today priced at 4000$ will be a regular consumer device in 10 years and models only get better. Local models today are fine for a lot of mundane tasks and will continue to be so. The use cases where paying for frontier models is worth it, will continue to shrink for folks not doing frontier work.
      • parineum 5mo ago
        > models only get better. Or stall. Acceleration has been slowing significantly and gains seem to be tied to huge memory footprints.
• xeyownt 5mo ago
  Great! More pressure on fabs, price of standard GPU will again rise. Guess I need to postpone my gamer PC renewal to end 2030.
• lucamark 5mo ago
  [flagged]
• aseipp 5mo ago
  The GB10 itself is pretty good and I love using mine for broad Linux development. But it's too expensive for consumer level pricing, and even for the "prosumer" the price is pretty stiff. Even if they dropped the CX-7 and halfed the RAM and shipped a smaller hard drive, would it be below, say, $2500 USD? I guess we'll see, but this variant is coming out pretty late so maybe it's just best to wait for the 2nd generation.
  • h14h 5mo ago
    This feels like getting a foot in the door to ensure Apple doesn't entirely eat Nvidia's lunch if AI inference workloads start to shift from cloud to local. With MLX, Apple is building an answer to CUDA, and if people start switching from ChatGPT & Claude to some app that runs on their M5, suddenly Apple starts to look like Nvidia's biggest competitor. If Nvidia doesn't have a pathway towards getting hardware into the hands of consumers, it could be a really difficult road ahead for them.
    • selicos 5mo ago
      Apple seems to still own the creative space. If those tools are able to run local models for any AI workflows suddenly anthropic/etc could lose a massive segment. Or at least demonstrate to others wanting a slice of the cloud AI profits it can be done. I'm here for it. Local models can do a lot of what I need at almost no cost, plus the fun of making them work better or building a new system to handle that aspect of my home lab. A Strix Halo system may not be amazingly fast but at 128gb of RAM it can keep up with most open models worth exploring. Based on June 1 Copilot Pro plan premium token burn and cost, unless you REALLY know how to use cloud AI efficiently and are tooled up to do so a local LLM on hardware you may already own is very appetizing. I converted a lot of work today to a 6.5gb local LLM on a 12gb GPU and no, it's not as good. But it is 'free' or at least feels that way, especially when I need to redo something and my copilot premium request % doesn't change.
• ocdtrekkie 5mo ago
  The thing I think is really funny is that if this takes off, frontier model companies and datacenters will end up holding the bag, and as per usual after the last few tech hype cycles, NVIDIA will still be selling. Eventually a lot of inference will get right-sized into something you affordably run yourself.
• lanycrost 5mo ago
  I'm waiting for powerful on device LLM models, since that not worth it
  • Hugsun 5mo ago
    Have you tried Qwen 3.6 or Gemma 4? They're not frontier level but certainly have their uses.
    • lanycrost 5mo ago
      Yes, they work great for small tasks, but not smart and powerful enough to beat with frontier models. Hope they will become better.
• orthoxerox 5mo ago
  Well, it was only a matter of time, since both AMD and now Intel are now switching to APUs. Nvidia could either cede the desktop GPU market to them, going all-in into AI datacenter chips, or it could challenge them. Maybe the Nth time's the charm and Microsoft+Nvidia will manage to make Windows on ARM a viable platform.
• ChrisArchitect 5mo ago
  Related: A powerful new chapter for Windows PCs, accelerated by Nvidia RTX Spark https://news.ycombinator.com/item?id=48352693 https://news.ycombinator.com/item?id=48352693 Surface Laptop Ultra: Made for World Makers https://news.ycombinator.com/item?id=48352627 https://news.ycombinator.com/item?id=48352627
• koolkao 5mo ago
  Very exciting! sounds like we're finally leaving x86 behind
• tonoto 5mo ago
  What is this product anyway? Is it a general purpose CPU or is it specifically designed for MS Windows? Nvidia stepping back from the open source? "Introducing the NVIDIA RTX Spark™ Superchip. The fusion of NVIDIA AI and RTX graphics in a single chip redefines Windows PCs and delivers amazing creating, AI development, and gaming—on the slimmest, most beautiful RTX laptops ever and small, ultra-efficient desktops."
  • mingus88 5mo ago
    It’s nivdia attempting to compete with Apple’s M-series
    • dawnerd 5mo ago
      All the news articles in my feed mentioned Nvidia reinventing personal computing which is laughable given the specs are worse than the m series. I’m guessing they saw how well Apple devices were selling and rushed to get something similar out so they can ride the hype train and have something to fall back on if ai DC spend slows down.
      • AlotOfReading 5mo ago
        There's a lot of companies trying to support datacenter systems like GH and Rubin that don't have dev hardware remotely resembling it. M-series isn't a good option, speaking from the personal experience of currently using one for this exact purpose.
    • Almondioco 5mo ago
      Its nvidia attempt to gain additional market share and expected as well. If the whole ecosystem is around nvidia and its the easiest way of running stuff, Nvidia offering more enterprise infrastrcuture allows companies to just buy directly nvidia. Nvidia is also very very rich and pushes the boundaries of stuff. They stoped waiting for industry standards. You can see this in there network stuff. All nvidia. Next logical step (at least now, not something i thought about) was there CPU for their GPU racks/clusters/systems. Now they have everything anyway, RTX Spark is just logical. I don't think its specificly targeted at Apple at all. Apple has like 10-15% market share and just because some IT nerds buy themselves a mac mini doesn't mean much. Plenty of them actually just run openclaw without local models. Something which surprised me quite a lot. But i have two 4090 at home. They consume a lot of power and i had to research the proper Mainboardmodel and had to mod one 4090 to use water cooling because they run too hot. There Spark setup was at 3k, way to expensive for normal people. If they can get this down and sell more, great for their ecosystem (strengthening it) and getting more money from people. It does surprise me though that they have enough capacity for this chip and not just putting everyting in Rubin but perhaps the build out has slowed down a little or they start to diverse already for economic savety
• 2001zhaozhao 5mo ago
  I think this is the first time an ARM windows device gets marketed for gaming. Would be interesting to see what kind of performance hit games have on the x86 to ARM translation layer.
  • lowbloodsugar 5mo ago
    Apple Silicon has a special mode that modified how the ARM chip handles memory transactions to be like x86. Does this nvidia ARM have the same? What would be interesting to me would be how quickly developers start targeting ARM64 directly.
    • odkurzacz 5mo ago
      For Apple use of Rosetta 2 was only temporary as they moved whole lineup to ARM. MS would not abandon x64 anytime soon. So I'm guessing they will try hard to convince developers to release for both architectures.
    • tedd4u 5mo ago
      This seems to imply it doesn't. https://docs.nvidia.com/dgx/dgx-spark-porting-guide/porting/memorder.html https://docs.nvidia.com/dgx/dgx-spark-porting-guide/porting/...
  • fidotron 5mo ago
    Rosetta on Mac was obviously impressive. There was also impressive Arm->Intel translation in the mobile ecosystem at one time. One reason it works surprisingly well on modern systems is how much is offloaded to the GPU. You aren't going to get great power optimization or anything without it being truly native though. There are games which are CPU limited though, and it will be interesting how those do. Curiously those also tend to be in engines with Arm support already.
    • HerbManic 5mo ago
      There was a presentation from Valve about their Dex compatibility layer. They did something that seems so obvious in retrospect. When you lay out the software stack it is essentially OS > Game code > APIs. Both the OS and APIs are native code, it is only that middle point that needs the real work. This is why x86 to ARM doesn't have such a heavy performance cost. So games can be CPU heavy but if it is heavy at the API end, that isnt a huge issue. Very cool.
• jmyeet 5mo ago
  I didn't see this in the article but elsewhere I've seen the memory bandwidth quoted as 600GB/s [1]. For comparison: - 5090/6000 Pro: 1792GB/s - 5080:: 960GB/s - 5070Ti: 892GB/s - M3 Ultra: 819GB/s - DGX Spark: 273GB/s (less than an M5 Pro at 307GB/s) Memory bandwidth isn't everything but it will cap inference rate pretty heavily. Also, the M3 Ultra is for an almost 2 year old Mac Studio. It's widely expected that it'll be refreshed in Q3 with a likely M5 or M4 Ultra with >1000GB/s. I really hope Apple realizes what a market opportunity Apple has here. The above shows just how good value the 5090 really is. It basically a RTX 6000 Pro with less RAM (and ~12% fewer CUDA units), which is a ~$10k card, for 20-30% of the price. This also demonstrates how NVidia uses VRAM for market segmentation. As an aside, the true data center cards (eg B100, H100) use HBM memory at ~3.2TB/s. [1]: https://wccftech.com/nvidia-enters-pc-space-with-rtx-spark/ https://wccftech.com/nvidia-enters-pc-space-with-rtx-spark/
  • MrBuddyCasino 5mo ago
    Yeah and also the quoted 1 PF is only for sparse models (only half that for dense, if that), and the DGX had serious hardware issues: https://x.com/ID_AA_Carmack/status/1982831774850748825 https://x.com/ID_AA_Carmack/status/1982831774850748825
  • wmf 5mo ago
    Spark memory bandwidth is ~300 GB/s. Internal bandwidth is 600 GB/s but that doesn't matter.
  • dist-epoch 5mo ago
    128 GB at 600 GB/s for this versus 32 GB at 1800 GB/s for 5090. This is much better value than 5090, you can run much bigger models.
    • jmyeet 5mo ago
      Here's a pretty detailed breakdown of this [1]: > tl;dr - For software development, Qwen3.6 27B, 5090 gives you ~3x speed over M5 Max, letting you plow through code, while M5 Max gives you ~4x memory, letting you use higher quantization and bigger context. Which would you choose and why? I've read a number of things from which the consensus seems to be that yes you can run a larger model and/or have more context with a 128GB+ Mac but the performance gap is still massive and with current hardware we're still talking about inference rates that matter. By this I mean there's a big difference between 10tok/s vs 30. Once we get to t apoint where it's 100 vs 300, it won't be as big of a deal, a bit like FPS in games. Oh and there are similar concerns with the DGX Spark [2]. [1]: https://www.reddit.com/r/LocalLLaMA/comments/1t5v2gr/need_advice_on_hardware_purchasing_decision_rtx/ https://www.reddit.com/r/LocalLLaMA/comments/1t5v2gr/need_ad... [2]: https://www.reddit.com/r/LocalLLaMA/comments/1sqk333/dgx_spark_vs_rtx_5090_for_local_ai_workflows_llms/ https://www.reddit.com/r/LocalLLaMA/comments/1sqk333/dgx_spa...
• lowbloodsugar 5mo ago
  ARM64+GPU sure seems like the future. I'm still using my M1 and even that can handle models well, has decent graphics, M5 is a beast, and M6 must surely go even bigger on LLM compute. Now Microsoft has a compelling ARM64+GPU future too. What does AMD or Intel have here?
  • throwa356262 5mo ago
    Don't know about intel, but AMD has Strix Halo with unified memory and really impressive performance. I think the future will be 50/50 x64 vs arm64 for PCs.
• babhishek21 5mo ago
  Question is: "Can it run Doom?"
• seanalltogether 5mo ago
  "Unified Memory" still means divided address space right? You have to pre-allocate system vs gpu and copy from one to the other?
• numron-dev 5mo ago
  Yeaaaah . But at what Cost though.
• giancarlostoro 5mo ago
  Can it work with Linux? That's all I care about.
  • newsclues 5mo ago
    This is strangely absent from the news.
    • wtallis 5mo ago
      There are two new things being announced here: the GB10 chip being put into laptops, and GB10 running Windows. GB10 running Linux is not news, it's a product that's been shipping since last fall.
  • tarruda 5mo ago
    I don't think there's any incentive for Nvidia to make this a Windows-only device, so most likely it will be fully supported on Linux, just like their GPUs are.
    • Matl 5mo ago
      > just like their GPUs are So with proprietary blobs that give you more trouble that they're worth?
      • wmf 5mo ago
        Those blobs are worth $5T; show some respect.
        • cromka 5mo ago
          Kids these days, amirite?
        • Danox 5mo ago
          Bubble incoming....
      • 5mo ago
• throw0101c 5mo ago
  Imagine a Beowulf cluster of these. /slashdot
• nerdjon 5mo ago
  Some competition for Apple in this space and competition for Intel and AMD is great. But I really do question how well Windows on Arm is really going to work out long term. For Apple it worked because they were able to force the issue. If you wanted a new Mac it was going to be Arm and we all knew eventually (this year or is it next year?) Intel support would drop. Over time we have seen M series exclusive features. Developers were forced to update or abandon Mac which gave users a great experience (with some early growing pains). This is something that Windows will never be able too do. They will always be stuck maintaining an emulator and a likely large subset of apps only supporting one over the other. (also does this work the other way around with an Arm only app working on x86?) This seems like a repeat of when it was not uncommon for games to only support Intel or AMD or NVIDIA or AMD. But worse since they are not both x86. Sure at least we have emulation but just like with Rosetta2 it shouldn't ever be the long term solution.
  • crims0n 5mo ago
    I feel like making universal binaries a thing, and pushing for it to be standard is one viable path.
    • pjmlp 5mo ago
      They already kind of are with ARM64EC, however Windows ecosystem isn't macOS, unless there is market pressure, most shops will keep doing x86/x64.
    • MagicMoonlight 5mo ago
      Microslop doesn’t want people to be able to run their binaries elsewhere, it’s the only reason people buy their product.
      • pjmlp 5mo ago
        They also buy it, because to this day most people cannot buy GNU/Linux powered laptops on the stores they usually buy their computers from. They only know Apple, Windows and Chromebooks.
• deleted 5mo ago
  [deleted]
• perarneng 5mo ago
  No thunderbolt is a big no for me. Its one of the greatest feature of MacbookPro that makes it dockable and expandable as a desktop with a good thunderbolt dock.
  • Almondioco 5mo ago
    Thats also possible with usb-c.
    • gillesjacobs 5mo ago
      With some caveats, you wouldn't be able to connect two 4k monitors to a dock without TB5.
      • kllrnohj 5mo ago
        USB 4 v2 has the same display capabilities as TB5. In fact, TB5 gets its display capabilities from USB 4 v2
• airstrike 5mo ago
  This seems to be an attempt to compete with people running local models on Apple hardware—even though those local Mac Mini setups aren't really powerful. I expect we'll get there in a few years, so perhaps this is Nvidia taking an early step in that direction. In that case, this goes against Anthropic and OpenAI's business models. Which is a double whammy after Jensen Huang's recent comment about how agentic coding will only increase demand for software engineers, not reduce it. So it also feels like a part of a budding shift in the competitive tension between the various parts of the AI supply chain.
  • deleted 5mo ago
    [deleted]
  • thewebguyd 5mo ago
    Local AI was/is bound to happen, eventually. It'd be smart of Nvidia to get ahead of it. Non-techy consumers may never do it, but at some point businesses are going to start asking when do they stop paying per token and start running models themselves. Right now the hardware is cost prohibitive, but I doubt that'll always be the case. Eventually the hardware will get cheaper and more available, and Nvidia seems to be betting on that. They don't care where inference happens, so long as it happens on Nvidia hardware.
    • CuriouslyC 5mo ago
      I think non-techy users will get subsidized hardware with compute workloads running in the background on idle to recover the cost (and lots of ads).
    • h14h 5mo ago
      IMO it's only a matter of time before "self-hosting local AI" is as complicated as installing an app and clicking a download button. And when that happens, the pitch to non-techy users is "Free ChatGPT you can use offline with zero privacy risk". Once hardware accessibility and LLM efficiency advance to the point that this becomes feasible, I suspect it'll result in a much bigger hit to the cloud AI market than many expect.
• analogpixel 5mo ago
  Oh, btw, we are only making 10 of these, the rest of our capacity has been sold off to the large AI firms.
• KetoManx64 5mo ago
  I really hope these take off and succeed and they support Linux. Qualcomm is seriously holding back the Linux ARM adoption with their continuous missteps.
• thot_experiment 5mo ago
  Love seeing AMD forcing Novideo to catch up for once rather than the other way around.
• cultofmetatron 5mo ago
  can these do training or only inference? currently working on learning machine learning and I'd love to have a physical machine I could aim to build real workloads on in a few years.
  • the_real_cher 5mo ago
    I believe training is way more processor intensive than inference.
  • LogicFailsMe 5mo ago
    They're Turing complete. What else do you need?
    • porphyra 5mo ago
      technically in order for something to be turing complete it needs infinite memory
      • LogicFailsMe 5mo ago
        The more (memory) you buy, the more you save!
    • Our_Benefactors 5mo ago
      It’s possible (likely, even) to have a chip fast enough for inference, but not fast enough or with enough memory to do meaningful training runs. Like the current DGX spark.
    • Npovview 5mo ago
      There is a reason why Google has tpu8i and tpu8t
  • airjason 5mo ago
    not for llm full training, but can do some finetuning for sure.
• BoggleOhYeah 5mo ago
  Kinda underwhelming. I was hoping to see that they improved their memory bandwidth to move toward competing with the M5 Max. But this is more akin to the Strix Halo.
  • raggles 5mo ago
    128 GB memory is also lame. I'm hankering for a windows equivalent of the mac studio that came with 512 GB.
    • FireBeyond 5mo ago
      The one that Apple discontinued not because of demand but memory pricing?
      • Danox 5mo ago
        Isn't there a possibility they were killed because the M5 Ultra is coming why waste memory on a M3 series Ultra or any other high memory Mac Studio computer when the next generation is coming within six months?
        • FireBeyond 5mo ago
          Possible, to be sure. But given that you could still buy the cheesegrater Mac Pro (with RAM and disk at 2019 prices, and a 2019 CPU at 2019 prices) right up to the week that the the M2 Ultra Mac Pro was announced, that would be something new. Not exactly an apples-to-apples comparison, to be sure, but still.
  • kristianp 5mo ago
    From what I'm reading it's probably the same chip that's used in the DGX Spark, the memory bandwidth at 300MB/s is equivalent to an M5 Pro, however you can't get an M5 Pro with 128GB of RAM. Apple pushes you to the biggest M5 Max chip, which at the 14 inch form factor, costs you $5099. You can get an ASUS GB10 machine with 2TB storage for $4000, so I guess the RTX Spark laptops will be more than that due to battery and screen, etc. Perhaps the next generation of the spark will improve on the bandwidth and RAM size numbers. Yes it's a lot like a Strix Halo, but this has CUDA, which will be of interest to developers who want that. I was looking for AMD AI Max+ 395 laptops recently, and the only ones I've found were 13 inch models, which seems odd from a heat dumping standpoint. I'm looking for 16 inches, I guess the 13 inch form factor would make it easy for commutes where you're taking it to dock to a large monitor at work or home, but no 14 inch screens?
• exabrial 5mo ago
  Yeah, there is zero chance I'm ever running Windows ROFL. However, I'd jump from Mac in a Heartbeat if this supported Linux.
• rnxrx 5mo ago
  There are still a *lot* of sharp edges with the Spark: compatibility, overstated performance, power consumption/heat generation, etc. It's one thing to have that situation on a box explicitly aimed at developers and quite another with an actual consumer-focused laptop.
• amelius 5mo ago
  "Notify me" -> i.e. when we finally have the DRAM to build this SoC.
• atilimcetin 5mo ago
  With 128GB ram, the price tag would be pretty high. And lots of application does not work Windows on Arm. Even Microsoft provides something like Rosetta 2 for windows, still x86 architecture would be the most popular one for Windows for a looong time. Saying that I think this is product is kinda dead on arrival.
• porphyra 5mo ago
  Lots of comments are expressing skepticism about compatibility but it's pretty cool how Nvidia has the clout to convince a bunch of game publishers and creative apps to release Arm versions. Popular games like League of Legends as well as stuff like Adobe Photoshop and Premiere are getting native Arm ports. > Over 100 Windows software providers such as Adobe, Blackmagic Design, Blender, CapCut, ComfyUI and OTOY, and game developers such as KRAFTON, NetEase, Remedy Entertainment, Riot Games and XBOX are embracing the new RTX Spark platform. [...] NVIDIA is partnering with Adobe to rearchitect Adobe Premiere and Photoshop for RTX Spark. [0] > Gaming on Arm is finally coming of age thanks to the NVIDIA partnership. Native anti-cheat solutions from Epic and BattlEye are fully supported on the RTX Spark platform. Major developers are jumping on board, with Riot Games bringing League of Legends and Valorant natively to the architecture, alongside KRAFTON bringing PUBG Battlegrounds. [1] Also, Nintento Switch is an Nvidia/Arm gaming device so many game publishers already have some experience with the combo. [0] https://nvidianews.nvidia.com/news/nvidia-microsoft-windows-pcs-agents-rtx-spark https://nvidianews.nvidia.com/news/nvidia-microsoft-windows-... [1] https://www.windowslatest.com/2026/06/01/microsoft-builds-its-ultimate-macbook-pro-rival-with-the-nvidia-powered-surface-laptop-ultra/ https://www.windowslatest.com/2026/06/01/microsoft-builds-it...
  • Shitty-kitty 5mo ago
    Press releases are easy. Delivering on promises, not so much.
    • stingraycharles 5mo ago
      This thread is almost 1:1 identical to when Apple released their own silicon. This has the potential to be a worthy competitor for the Windows ecosystem, precisely because of NVidia’s moat as the grandparent pointed out. Microsoft pulls in their weight as well, so this seems like it has a decent chance of getting industry support.
      • wslh 5mo ago
        That said, Apple still deserves a lot of credit. They had a 5+ year edge, especially around the vision of tightly integrating the NPU and unified memory.
• synergy20 5mo ago
  can it run linux as I am not a windows nor a macos user
• atlgator 5mo ago
  Anything they can do to avoid producing more 5090 FEs.
• yobid20 5mo ago
  how will this compare to having an rtx pro 6000 for inference? (not training)
• ilia-a 5mo ago
  Looks like just rebranded DGX in laptop form, the biggest miss is the weak memory speed, 1/2 of the M5 laptop memory speed, and 1/3 of the M3 ultra that is now years old...
  • mbreese 5mo ago
    I'm not sure that's such a bad thing. It's not going to challenge the Apple M5, but if you're specifically looking for something in the "not-Mac" market, having a laptop-sized version of the DGX is probably going to be pretty successful.
    • deleted 5mo ago
      [deleted]
    • Danox 5mo ago
      Then they better release it within the next two weeks.
      • mbreese 5mo ago
        What's coming out in two weeks?
  • ActorNightly 5mo ago
    The main bus is 300gb/sec, which is on par with MB Pro. MB Max has the 600gb/sec of unified memory (about ~500 or so in practice for token generation) only for the 40 core variant, which is like $7k +, which is ironically more expensive than a dual 3090 card desktop. The 32 core variant which is still wildly expensive is like ~400 gb/sec. The biggest thing where this will crush Apple is the initial prefill phase. 6000+ cores vs 32/40, + active cooling with fans. For local llm models, this matters quite a bit more than tokens/second. In the end, neither are really worth it for llm use compared to just building a desktop and just port forwarding over ssh to ollama.
    • ilia-a 5mo ago
      Because of the memory costs lately, I doubt this will be much cheaper. Also this is quite a bit slower than even 4070 let alone *90 Nvidia variants albeit with much lower memory.
• awesomeusername 5mo ago
  I've been daily driving a dgx spark. Once you start there is no going back. NVIDIA nailed it
  • not_a_bot_4sho 5mo ago
    Mind sharing more details about your use and experience with DGX? I'm just curious
• ThunderSizzle 5mo ago
  I added an R9700 32GB to my 10+ year old desktop that had a 980 4GB card in it, for a grand total of $1350 or so. The payoff compared to what I was using with GHCP was 33 months, but when GHCP announced their price increase, it basically became a 3 month payoff at minimum (so yes, GHCP did a 10x price increase for non-parallel agentic workflows) I can easily run Qwen3.6 35B-A3B with Q5_K_M with a 260k+ context window with some vram to spare. It easily runs probably 80tps. It took me quite a while to find the Compared to GHCP Claude Sonnet 4.5 or 4.6, I have full parity. The wall clock time is faster for agentic workflows, and rule following is about on par. With either, doing something kind of novel or obscure takes more hand holding compared to just generate a GUI or crud app. For example, trying to build an actual program that performs a complicated process correctly requires quite a bit of hand holding to get it to properly help. Sure, it isn't Opus or something, but I think with the right harness, it probably can get close. I think most of the issues these days is the harnesses are lacking.
  • cmxch 5mo ago
    Between that and the Arc Pro B70, they’re the 32gb cards that are actually affordable and worth getting. I’ve got both (single R9700, dual B70) and they do nicely for about anything I throw at them, such that the latter has a visible improvement when the model is well-cached.
  • eVeechu7 5mo ago
    What is GHCP in this context? Glasgow Haskell Compiler Platform? Google Hostage Computer Program?
    • mh- 5mo ago
      Github Copilot, as far as I can tell. Though I like yours.
    • ThunderSizzle 5mo ago
      GitHub Copilot. It was one of the best values around in terms of cheap LLM access since each prompt was basically 4 cents (more or less), no matter how much it would do or how many tokens it used. A simple "Proceed" prompt that was telling the agent to execute a sophisticated plan could burn a lot of time without needing any direct intervention by the user, but as of June 1st, they switched to metered billing, meaning each token in/out has a cost now. It was suspected to come soon enough, but it was a nice cheap road for my small hobby stuff. When they announced the price changes, I started to explore alternatives, and with the news of Qwen3.6 35B being both and having quality, I figured it was worth a try out, and self-hosting made the most sense to me, since that meant I was free from being a forever-renter.
• modeless 5mo ago
  Single-core CPU performance is going to be fully 20% slower than Snapdragon X2 Elite Extreme. People are sleeping on Qualcomm's latest. It's the only chip out there to approach Apple's single core CPU performance and power efficiency.
• dvhh 5mo ago
  I might be in a niche user, but what I a mostly looking forward into an ARM laptop, would be to be silent with preferably passive heat management or as little at possible active heat management (all day battery usage is a given).
• locusm 5mo ago
  Jensen Huang delivers the absolute worst keynotes - I wasnt ready for that level of cringe and stupidity.
• zer0zzz 5mo ago
  What are these things going to cost? I hope not the same as a mac equivalent or as much as a dgx. Geekbench cpu bench leaks indicate they aren’t as good as m3 at single core even. Will they support booting into a Linux installer?
• bch 5mo ago
  "The performance is off the chart!" <basic chart is displayed to illustrate(?) the point> More seriously, obviously a ton of work in an incredibly competitive space, and an incredible machine (without getting into competitive comparisons/minutiae). Was watching a techtechpotato[0] quick post pre-launch about "why is this even being tried?", which was also interesting. What an age we live in. [0] https://youtu.be/JdB722MK380?si=GnLAYqT9ZecMhWCS https://youtu.be/JdB722MK380?si=GnLAYqT9ZecMhWCS
• easygenes 5mo ago
  Looks like RTX Spark desktop is the DGX Spark desktop, minus the expensive 200GbE Connect-X NIC. Only since the DGX Spark released, memory and nand prices have jumped, so it will likely retail for the same amount as the DGX Spark did on release (which has since gone up significantly).
• Schlagbohrer 5mo ago
  They show premium skinny laptops which will have this. I wonder how much the lack of heat dissipation capability will limit it's compute capabilities? In university a friend of mine had a large hardcover book she kept in her dorm freezer. I asked here WTF she had a big book in there. She said it was for minecraft - she'd place her laptop on top of it while playing. The book was cold but also quite dry. I wonder how well it worked.
  • bananadonkey 5mo ago
    I had a high end spec gaming laptop with 0 airflow back in the 2000s, and used to raid dorm LAN party freezers for frozen meat + towel = heatsink. I was lucky that iteration 1 (sans towel) didn't ruin the laptop...
• tommica 5mo ago
  Wow, specs seem amazing. So want one of those once you can run linux on it, especially for the ability to run local models on a laptop.
• big-chungus4 5mo ago
  Running local agents 24/7, I get that it's a powerful CPU or GPU or whatever it is, but still, isn't it going to be constantly loud and 95C hot, that can't be good for the laptop if it's like that 24/7
• Floppyrom 5mo ago
  Nintendo Switch 3 will probably use this.
• rldjbpin 4mo ago
  given how dgx spark was more advertised for finetuning ("tinkering") instead of inference, it is quite interesting to see their approach for the laptops to now be more inference-based. knowing nvidia and their approach to consumer hardware (especially those on notebooks), i'd take a heavy grain of salt on getting a good deal. also, they've been bad to their ecosystem partners, but now they've been able to boss them around into supporting them so far. i suppose getting anticheat vendors to finally support arm might be enough of a nudge for linux support? one can only dream
• AI2070 4mo ago
  128GB unified pool is the headline, but memory bandwidth is the number that decides local LLM speed