Or maybe just not at all - shell out for OAI tokens and send us all your data - your privacy is very valuable to us and we will make sure to be the only ones to monetize it.
You could say, Nvidia is selling pickaxes and has no business gatekeeping what rocks you hit with it, but I guess it depends on their relationships with major mining companies, and ultimately what pays more.
Those are very different things as far as I understand, and the whole "doesn't work well with linux" really only makes sense on the RTX Spark laptop I think? Isn't the DGX spark linux by default?
Man it really is exhausting to read a title that sparks my interest, just to be greeted with the most basic Claude-isms in the subheading.
I see what you did there. ;)
I just heard a quick J. Talarico speech at some country concert. In the 10 or so sentences he spoke, he had 3 or 4 instances of doing this "Claudism" enumeration. Are you saying Texas just elected Claude for Senate?
Maybe we should stop with such superficial judgements. It's the modern equivalent of not liking the speaker's tie. (Doesn't mean the speaker's speech is good, but it doesn't mean it's bad either.)
Edit re "equivalent to not liking the speaker's tie": This is not equivalent at all, this is a written blog post and I'm put off by the way it is written, not by say the URL or their chosen font. It's more akin to a speaker dropping an inappropriate joke at the start of their talk and leaving because of that
But, on the other hand, having my DGX Spark stack at hand, I know the solution:
/btw reverse engineer the Nvidia Platform Controllers and Framework component and build a Linux version
EDIT: I don't know why you changed your comment, but yes, it was obvious from reading the article that it was not actually about the DGX Spark.
Sovereign AI has never been more important.
But yeah, we do need to make sure the REA cat stays out of the bag.
I, for one, welcome our reverse-engineer-anything overlords.
TIL. Nice word.
If you really want to do DIY inference, plug it in at home and set up tailscale so you can access it on the go.
No huge battery drain or toasty hot laptop required. Lower cost laptop. Lighter laptop. Longer battery life laptop. Win win win win.
Maybe you need a therapy. FOMO can be treated, too. Or you're just upset about Trump falling into irrelevance.
The market for someone who wants local AI in a laptop for $10k has to be tiny.
GGP's point is just: keep the bulk of your compute at home, where airflow and energy is cheaper (in an opportunity-cost sense). Keep the laptop portable, cool, and light, with long battery life by offloading your own computing tasks to your own hardware.
I am not saying don't use a laptop.
I am not saying you have to use cloud inference.
I am saying using a laptop for inference is dumb. If you want private inference:
- use a dgx spark or similar plugged in at home
- set up tailscale so you can connect from anywhere
- use your phone as a hotspot on the go
- work on your laptop, using tailscale to connect to your home inference server if you're on the go
This gets you everything except for the few hours you might be on an airplane.
The simple point I'm always trying to make is that area vs volume is a fundamental physical difference regarding cooling, which is critical for high performance applications (that's why they're considering an RTX Spark in the first place, right?).
There's so much more I could say about my Strix Halo machine, which fits in the palm of my hand and I have a wonderful portable screen and keyboard+touchpad (and only cost me 2k with 128 GB fast memory, idles at 4w, amazing 32 thread Zen 5 CPU with AVX-512, ...), but it's either preaching to the choir or pissing against the wind.
unique local data and know how not shared with cloud.
I meanwhile, run my ridiculously OP workstation class hardware as a server - 9995wx, 768GiB, rtx pro 6000 w/ 96GiB vram - at home, and my Asus ZenBook is light, cool, and long-lived.
Runs GLM 5.3 flash at 35 tok/sec while consuming only 15 GiB VRAM, and I can run a lot more stuff on there alongside.
To me the simple answer to why is control. If I run a model locally I get to control the model params, the system prompt, all of it. And of course there is no quota. But probably most importantly I am not tied to paying some company a monthly subscription forever.
Sovereign AI has never been more important.
Controlling AI is so much more powerful and impactful than controlling search or social algorithms.
Centralized AI a 10x on social control over everything we have seen before, and there is no way that a free and open society survives contact with centralised, high capability AI if the system is manipulated towards guiding outcomes. It’s essentially mind control, as people will offload an even greater share of their cognition to AI than they do with search and social.
Build and maintain sovereign AI while you still can.
Pay up for license to unlock full capacity, pay up for license to use encrypted models from AI moguls, paid per billion tokens processed or just operations in GPU
I wonder if this space is explored fully enough at the moment.
Aside from some implementation details, it's conceptually much easier than doing it for a SQL database.
Note, these models generally run 60/120/240 FPS depending on the camera range, and can command the connected lenses at ~100FPS (because physics).
The consumer has access to free and open models for local use.
The supplier has better control and wider market to serve running the models in data centers.
Only way I can see encrypted models being widespread is if they are bundled as part of a software package (OS/Browser/etc) and not sold as the product.
And, the same GPUs are run in datacenter, where there's a big insider risk that vendors want to mitigate with encrypted models (if you're Anthropic and you want AWS to host your models, you don't want 5000 or even 500 or even 50 AWS employees with access to your highly valuable/desirable model weights).
Remember, the kernel module is open source, but rest of the driver is closed source, and any kernel level code which can't be open sourced but had to be is moved to card firmware. Only the kernel module is open source. Not the libraries, not the driver, nothing else.
NVIDIA is holding to its pearls like a sloth holding to its branch, because their all business model and livelihood is dependent on that control. I still commend AMD's decision to allow full card enablement with any driver which talks the correct language.
There will be ways for them to segment the market and make their money. Maybe not 100x stock in 5 years but money all the same.
So it is something that has been done for a long time now. Still feels like unethical rent-seeking that should not be tolerated by the customer.
See Also: car companies that charge additional fees for hardware already on the car. Additional services, I sort of understand(remote start via cell network), but stuff like heated seats, that is just wrong.
Yep, "Batterygate"
https://www.npr.org/2020/11/18/936268845/apple-agrees-to-pay...
It saves the car manufacturer on logistics cost. The per-unit cost of a seat heater is (much) smaller than the cost related to keeping two variants of seat in stock and to provide spare parts. Say the heating mat costs 100€ per seat including materials and installation, and can be sold to the customer for 400€ permanent, that means as long as 1 in 4 customers buys the seat heating option, the books are balanced, and all money you save on logistics is pure profit.
Adding subscription on top of that is financially even better, if there is one thing companies LOVE thanks to stonk market incentives it is monthly recurring revenue.
I think more than that, it is probably a lie they tell us that you are not paying for the hardware/equipment.
Yeah, Nothing morally wrong there.
A license has zero marginal cost in the first place. Software distribution over networks have a negligible marginal cost. An ebook as zero margin cost. We are constantly paying lots of things with zero or negligible marginal cost.
AI is a software just like operating systems and executables where open source absolutely dominates the industry. Remember when the compiler engineers optimized the shit out of llama.cpp.
Right now the bottleneck for AI software is compute and data. Moore's law is give us compute, StackOverflow, arXiv (and it's children like bioRxiv), gutenberg and others (3lib, anna, internet.org) will give us data.
It's a waiting game. Open source always wins.
Tons of stuff happenning behind closed doors today though. No more stackoverflow for the next decade, that could create a problem if all new context only exists in chatgpt conversations only openAI has access to (or whoever).
Based on... what? Thoughts and prayers? Feelings? Vibes?
I don't know if you looked around but open source is basically unusable for the largest platform in the world, mobile.
The next platform, whatever that is, will also be closed source (maybe VR, once it finally matures...).
LLMs are closed source, is there even 1 (ONE) LLM which is both open source and open weights and publishes its training data and methodology and is also remotely competitive with the frontier lab LLMs?
Consoles are closed source. Appliances are closed source. Embedded devices are closed source.
Even the web is basically closed source. Blobs of encrypted, obfuscated JS used to serve news pages (!).
Maybe I'm looking in the wrong places, but closed source has won.
And regarding servers, who cares? The platforms users interact with are their clients and the actual server software on top of the Linux OS is closed source 99% of the time.
Don't post lazy comments.
Nothing stops you from giving Nvidia half a million for their latest and greatest AI GPUs, unless you are in China I guess, but China does very well despite the export control.
It is just classic market segmentation, the thing Nvidia and just about every company that can benefit from it has done for decades. Cloud providers are ready to pay a lot of money, consumers wanting local AI have a lower budget, and gamers even lower. But a low budget is greater than zero, and there is still money to be made on these markets. But they also don't want to compete against themselves, so they are going to find ways of crippling enterprise-class workloads on consumer hardware.
It used to be that they crippled high precision arithmetic on consumer hardware, because it was a differentiating factor, but AI doesn't care about high precision, so now, it is something else.
These are multi-million dollar datacenter systems, not consumer. If you mean the consumer market, it's coming but it's going to be 2028-29 most likely (if the bubbled hasn't popped by then).
Strix Point is quite good but not the same thing as a DGX, though. Same idea, different methodology.
I miss the old days when they released enthusiast products like the R9 295X2. Though that’s just the gaming enthusiast market in general declining (not that this happened organically though, it feels like a deliberate choice).
I have many pleasant memories of keeping myself warm just by opening Witcher 3 on my R9 390.
AMDs revenue this quarter just passed Intels for the first time in history and they still are dominating in the HPC market which is fairly immune to the AI bubble (while also selling everything they can build at a high premium to AI datacenters).
AMDs margins on their Instinct datacenter GPUs is nearly as good as nVidia's. They just can't get contract volume at TSMC to make more because nVidia buys all of it.
https://d1.awsstatic.com/onedam/marketing-channels/website/a...
They're still getting plenty of Nvidia GPUs. Someone in Jensen Huang's inner circle apparently runs a number of companies in Singapore that have been found to source GPUs at scale. The catch is that she has close ties to Beijing and is suspected of working closely with their government, potentially even spying for them.
This was reported just a week or two ago and is just one example of how China is still getting their hands on resources they're supposedly unable to get.
I stopped using my laptop for dev and switched to talking to claude code on my phone and as you can imagine I am faster at producing code.
100% cloud with a single entry point device to manage dedicated servers + agents
[Hanlon's Razor] This is such a contrived performance drop scenario that I find it hard to believe it was done with the purpose you're inferring.
I'd interpret this as Nvidia not caring that much about Linux desktops/laptops once again (as opposed to Windows desktops/laptops), rather than anything to do with local vs cloud.
Even that argument is weak - the DGX Spark is Linux, and the RTX Spark is practically the same exact chip.
Sorry to remind people of HN, but most of the consumer market still runs Windows. This was a joint project to have a consumer-level Windows-on-ARM machine, likely requiring lots of development efforts from both NVIDIA and Microsoft.
So, for these specific laptops, they put 100% of their attention for it to be on Windows for launch to capture as much market mindshare as they can. Local AI, Graphics and creative work, and some gaming.
I doubt Microsoft would have been happy about NVIDIA having Linux on their laptop right at launch.
Market Share by OS for consumer laptops & desktops:
• Windows: 76.65%
• OS X / macOS (Combined): ~15.67% (OS X at 9.86% + macOS at 5.81% due to user-agent reporting quirks)
• Linux: 5.63%
• Chrome OS: 2.04%
As in, make your own inference and training hardware?
Sovereign AI is less about being able to build it from first principles and more about being able to tinker and modify what already exists. I can’t train a 30B model, but I can modify the weights of one. I can’t fab my own chips, but I can putter with the software that interfaces with them.
Sovereignty is lost when encryption hides your toys and attestation tells you “you may not”.
Estonian only has sovereign AI as long as they’re allowed to buy from Nvidia. Oh wait, they’re already restricted in what they can get.
Who exactly?
Beyond him, I would bet most of his bilderberg group friends agree. E.g. Peter Thiel, the owner of JD Vance.
This is a linux driver problem. On laptops designed for windows.
Read the article and stop sensationalizing.
This is a problem on the MSI Prestige laptop using the RTX Spark platform and Linux. Lets assume it also applies to the Asus and Dell machines using RTX spark and Linux.
RTX Spark is a new platform and all of these laptops ship with Windows. You cant get Linux on any of these machines from the factory. NVIDIA may even ship drivers for linux later as they did with Dynamic Boost.
Kindly remove this from your list of "Evidence that NVIDIA is Colluding to Centralize Inference" and everyone else take note of this confirmation bias in action.
edit: even more important for mobile computers
That them trying to protect IP around something very profitable isn't crazy. That not being fully supported in Linux, when the product was literally designed around Windows, also isn't crazy or really evidence of anything, including evil (see the whole fucking history of Linux compatibility of made-for-Windows hardware).
Maybe let them cook.
It obviously can't be because of ulterior motives!
No. It's 'the NVidia way or the highway' problem. NVidia is so full of themselves they refuse to work under anyone's rules (i.e. the Linux kernel where they're constantly trying to work around them).
They're egomaniacs who are so full of themselves, riding high on the AI bubble, they think they're above everyone else in the ecosystem, while utilising all kinds of other people's work for their own benefit.
Look at the way they develop their 'open' Linux drivers where it's just a shim that loads a huge binary blob off the GPU rather than a proper driver like amdgpu has.
Meanwhile they wouldn't be a $5T company without Linux and the wider FLOSS ecosystem.
It's kind of like when Secure Boot debuted and the plan was to allow only Windows with it enabled, then no doubt someone would claim the fact that only Windows can boot with it enabled as a 'Linux driver problem'.
Claude, make a driver that runs at full capacity on my laptop. (make no mistakes).
nvidia has always been crap like this. Look at amd and intel, they let u write proper drivers (even if its real difficult to do so). No encrypted blobs or voodoo needed.
the nvidia drivers u need to use a card on Linux are unintelligible binary blobs. thats sad as it is. this is worse. they might give some shitty blobs at some point, after they made enough ppl give up on it and switch to give them and their partners their money, souls and firstborn
Is the problem one that could be easily countered by assuming that laptops are generally better when they're not on fire?
> The laptops also support unified memory configurations up to 128GB, shared between CPU and GPU, which is unusual for a laptop and central to why they’re being marketed at AI developers in the first place.
This isn't rare on laptops, pretty default on AMD with iGPU
Nvidia won because their architecture is better. If you do a significant amount of work that can be CUDA-accelerated, you're kinda wasting your time not owning a CUDA-capable card. It's like being a video editor that software-encodes their projects because they don't want to get an accelerator card. It's your choice, but software-acceleration is a nightmare compared to how quick and efficient hardware-acceleration is. Competitors will all use the accelerator card and ship faster than you can.
Apple, AMD and Intel have all earned their current position by abandoning Khronos and refusing to build their own GPGPU architecture. If the entire industry refuses to invest in complex technology just because it's expensive, then they don't deserve to make money.
Nvidia does something to prevent abuse so that regular people who want the laptops can buy one. Nvidia gets knocked on.
This is all but certainly a bug in their linux driver and nothing else. It sure as hell isn't some "anti abuse" to enable "regular people" to buy one.
The only value proposition of RTX Spark at all is the laptop form factor
> NVIDIA has now confirmed an official starting price of $2,399 for RTX Spark laptops
https://shattered.io/nvidia-rtx-spark-mediatek-oems-price-20...
https://www.servethehome.com/nvidia-dgx-spark-64gb-launched-...
If we look at what you can actually buy the 64GB RTX Spark is $4,500 and the 128GB one is $7,000: https://eshop.asus.com/us/31150-us-cnf-auto.html & https://www.dell.com/en-us/shop/laptop-computers/spd/xps16dx...
Hell there doesn't seem to be an RTX Spark that's sub $3,300 when considering the 32GB models even. $2,399 is pure fiction.
And if there's a market for a DGX Spark configuration with a higher compute-to-RAM ratio, why isn't Nvidia offering it?
My best guess is that the entry-level Sparks are mostly intended for people who would otherwise be in the market for a traditional high-end laptop, who might be enticed to spend a few hundred more for at least the promise of local AI, while the higher-end models are intended for more serious AI development.
With that said, it's not hard to imagine there isn't nearly as large a built-in market for high-end SFF Linux PCs as there is for high-end Windows laptops.
In fact I'm pretty sure it's happening. Why? Because of constantly growing prices of those things.
I was genuinely excited about this device until I heard the specs. Still under 300GB/s memory bandwidth when a gpu like rtx3090 from 6 years ago had 900+
This is really bread crumbing local inference users.
We should be measuring our memory bandwidth in TB by now. The only company that seems to be serious about this is Apple. (the m5 ultra studio etc).
Or RTX Spark and run their workloads under WSL, which as the article notes, has minimal overhead relative to running Linux directly?
This sounds more like a bug than a feature, especially given that Linux on battery runs at full clock speed and downclocks when plugged in, and Windows does the opposite, suggesting they could at least mitigate the problem with no changes to their software stack by inverting a conditional in the firmware and adding a Linux kernel parameter to control memory allocation as apparently already exists for Windows.
https://developer.nvidia.com/blog/nvidia-transitions-fully-t...
Point was about the kernel drivers being open-source enabling hackability - they don't, the card hardware is just as closed as before.
When did "we" have a say in this? I don't get these types of comments from the "open-source as a community."
Nvidia has been doing this for decades, and there are two possible arguments:
1. They are successful despite it.
2. They are successful because of it.
There is no mythical collective "we" representing the open-source community in Nvidia's supply chain of success. It's Nvidia and its consumers.
I don’t think anyone “allowed” them - quite the opposite. They’ve made generational bets that ended up being right, bets that IIRC the industry did not agree with for a long time. Them pursuing CUDA resulted in a draw down of something crazy like 75% of their valuation. They bet the farm multiple times to get to the point they are - and it’s only “obvious” in hindsight.
If you want folks to make generational bets as a matter of course (which I think most folks do), centralizing the downside of those bets and socializing the upside of those bets is not a great strategy. Almost as bad as socializing the downside.
Competition will eventually close that gap. We’re only a few years into this thing.
Have you ever heard of U.S. Steel, IBM, Kodak, and Western Union?
They really got it right on multiple levels - for those who don't know, roller coaster tycoon was infamously written in 99% assembly and meticulously optimized by the developer to run effectively in 16 megabytes of ram.
A laptop can't run the latest big models, because memory is too expensive. This thing probably can't run models larger than Mistral Small 4. But it'd be a completely different thing to have a hardcoded Mistral Large 4, than a choice of tiny models.
I think I misunderstood what the technology could do a little bit, because I imagined these fixed matrix multiplies encoded into hardware as small-ish, as using routing space etc., not just fast.
I think what I really imagined was useful would be more easily achieved by having a big ROM with model weights connected to an ordinary GPU.
But with Nvidia people just expect they nerf all the features.
This is a new thing with the firmware that can be used only by Windows. If this NVIDIA policy continues, then NVIDIA will indeed become a bad choice for Linux, but until now, for graphics and AI applications NVIDIA has been the best choice for Linux, by providing the best performance and reliability.
For pure computational applications, especially for those requiring good FP64 throughput, there are many years since NVIDIA has become a worse choice than AMD and more recently also than Intel, but that is due to poor hardware support, not to bad software support.
Hell, their old closed-source NVIDIA _FreeBSD_ drivers were at parity with Windows. CUDA included (though the CUDA toolkit required Linuxulator syscall emulation to run the Linux bins).
Imagine my surprise when my new Blackwell card didn’t work, and that the newly required open source drivers were Linux-only.
If they were using DirectX through Wine, perhaps the DirectX emulation is not optimized for NVIDIA, but only for AMD.
I do not play games, but I have used professional graphics or computational programs using OpenGL/Vulkan/CUDA/OpenCL natively on Linux with the NVIDIA driver, and those have always been as fast or faster than on Windows.
The AMD and the Intel cards have always had poor drivers for OpenGL, which frequently cheated in order to get better benchmark results, by having various rendering defects in comparison with the NVIDIA cards, so when running a benchmark like SPECviewperf, the advantage of NVIDIA has always been much greater than the already higher speed, because that speed was obtained while rendering everything correctly, while with Intel or AMD many things were rendered only approximately.
I actually have more AMD and Intel GPUs than NVIDIA GPUs, but I continue to use the NVIDIA GPUs for graphics, due to a better driver, while I use Intel and AMD for general-purpose computations. However, I have not tested Intel and AMD with a Vulkan graphics application, to see whether they work better with Vulkan than with the obsolete OpenGL.
Also very curious if the NPU is visible in Linux, too.
https://www.xda-developers.com/nvidia-rtx-spark-laptops-same...
Still miles ahead compared to Apple, where linux does not even boot on newer macs!
If you want to prosper with the current of nature, provide a thing easily for mutual benefit. The more you try to block a thing, the sooner your demise into uselessness.
This has been an issue on Linux since 2014, and the gtx980.
Even if this is an intentional nerf by Nvidia, which I doubt, then then nerf is buggy.
Absolutely hilarious.
This is just incompetence. No reason Nvidia with its TRILLIONS of market cap couldn't of tested and fixed this on Linux before shipping.
Or a day one patch.
I have no doubt that'll it'll work right eventually. Long after RTX Spark laptops flop and can be purchased for half off.
Last night I pulled out my 5070TI laptop and installed CachyOS. I was running various models within about 20 minutes.
That 12GB of VRAM is a hard limitation, Unsloth can't split jobs between vram and system memory.
Could have tested.
Even from the article I'm guessing you could write a script to automatically extract the encryption keys while on Windows and the load those in Linux.
This is only mildly inconvenient for anyone who'd use this in a data center cluster.
They've always played these sorts of games. Now, people are seeing the substandard solutions for what it is, and are angry.
I understand that their "secret sauce" might be exposed with open drivers, so I somewhat respect their right to intellectual property in this respect.
It's lack of linux driver support for firmware designed for windows only laptops.
What is going on here? Commenters here are clearly extremely paranoid about NVIDIA centralizing inference. This is not reflected in the facts nor narrative of the article - it's completely fabricated out of left field her in the comments.
This is a problem on the MSI Prestige laptop using the RTX Spark platform with Linux. Lets assume it also applies to the Asus and Dell machines using RTX spark and Linux.
RTX Spark is a new platform and all of these laptops ship with Windows. You cant get Linux on any of these machines from the factory. NVIDIA may even ship drivers for linux later as they did with Dynamic Boost.
Why the fuck is the power table encrypted?
This is a lack of linux driver support for firmware designed for windows laptops.
This is a problem on the MSI Prestige laptop using the RTX Spark platform. Lets assume it also applies to the Asus and Dell machines using RTX spark.
RTX Spark is a new platform and all of these laptops ship with Windows. You cant get Linux on any of these machines from the factory. There is also precedent for NVIDIA shipping linux support well after Windows (2 years in the case of Dynanmic Boost, a similar power sharing feature).
Then you misunderstand how hardware, software, firmware, drivers, and operating systems have worked for the last few decades.
Good luck with that. A PC is more or less defined by specifications laid out in Microsoft's Windows Hardware Compatibility program and tested by their Windows Hardware Lab Kit. Before that, it was defined by IBM.
I've heard that ARM has had a standard for ARM-based servers, their Server Base System Architecture, but I've never seen any compliant hardware in the wild.
They basically do. ChromeOS runs a Linux kernel, so the userland has everything it needs to run CUDA. FreeBSD is a first-class target for Nvidia drivers, and macOS used to be supported too but stopped signing Nvidia code. Nevertheless, AArch64 is still supported for CUDA et. al..
It is up to Nvidia to support whatever platforms they want users to be on. In their case, it means supporting many OSes.
My point is that's not Nvidia's responsibility. The article itself admits the laptop "ships with Windows on ARM", so support for another OS shouldn't be expected, even if NVIDIA supports other platforms and other product lines differently.
There are OEMs that refuse this responsibility. If that's the vindication you wanted, there you go. This specific issue is not a catastrophic oversight though.
> There is also precedent for NVIDIA shipping linux support well after Windows
There is also a precedent for NVIDIA nerfing drivers on Linux and pulling anti-competitive shenanigans against competition, so it's only reasonable that people look at the "missing" driver support with suspicion.
How does your conspiracy theory hold up to that?
GB10 and N1X are both Blackwell cousins. So they've had consumer-level Linux machines for a while now.
This was simply a partnership with Microsoft, so of course development of drivers and firmware focused heavily on Windows. Especially since I'm sure Windows required a LOT of updating to run nicely on ARM as well as the N1X unified memory model.
You may as well be right, I am speculating and this theory might be baseless (I don't think it is.) But GP's comment is wrong to ask people to simply read the article at face value. That is bad reading.
Personally, I don't care. If you don't support open drivers, you have to provide first class drivers on Linux on day 1, because NVIDIA's majority of business is running on Linux already.
On top of that, they claim to have the best Linux support, and claim to have best drivers in their class.
So, it's better to act like that and provide support. If any other company has done that, they have been incinerated with the flame of internet's hate thrice already.
NVIDIA and Microsoft tried so hard to make a Mac clone with this and it’s just missing the mark everywhere.
It doesn’t do the dynamic memory split that a Mac does so out of the box it reserves 32GB (half) for the GPU and windows limits CPU processes to that. Getting more memory requires a reboot.
And because I want Unix tools (without Cygwin), WSL2 splits that even further in half.
Performance is way behind a similarly specced Mac. The GPU is thermally throttled near a 5060 laptop. The CPU out of the box came in a lower power state but windows power management makes it stuttery unless you change that, at which point it’s cooling is a hurricane compared to the Mac which outperforms it while being quieter.
The new MagSafe like connector is stupidly designed too. You can’t generically use it in any USB-C port, it’s super chonky and disconnects only on the horizontal axis. Worse, because it’s a right angle connector it can only be used in one orientation without blocking the other ports.
Windows input handling sucks too. There’s a lag before the trackpad responds based on moved distance. Some terrible take on palm rejection I’m sure. But even their display is mediocre because it gets very bright but they messed up local dimming. So if you select a bunch of text in the terminal it blinds you.
Idk I got this specifically to do windows dev with CUDA on arm. So I knew it was niche but anyone else buying this is making a mistake. It’s an unfinished product trying to be a competitor that nobody in Microsoft even understands.
This Linux support issue is just the icing because everyone keeps asking me why I don’t just put Linux on it and workaround my issues, but you can’t.
I’ve spoken to friends at NVIDIA who say it’s rushed out. So maybe software will get better but I urge folks to not buy this unless you’re into the same niche needs as me.
Odd because Tegra/Jetson platforms have been doing this for years.
I suspect it’s a limitation of them focusing on Windows driver and windows being far behind the curve.
We can see with this evil cartel currently driving up the RAM prices how greedy they all are. Our money should go into fairness. The US court system has given up on that. Even on capitalism. Capitalism used to claim that a free market with competition leads to lower prices. Well - we have several de-facto cartels here. And nobody is breaking any of these up.
Vote with Your wallet.
Its that simple.
Every.
Single.
Time.
> laptop ran a full desktop at 4K and 120Hz, with working audio, touchpad, keyboard, and CUDA acceleration
is amazing. It seems that this person's MSI version had some quirks with firmware but Omarchy already supports the Asus and Dell versions of the RTX Spark out of the box. I'm surprised that everyone is focusing on the negative when, prior to RTX Spark's release, it wasn't clear if Linux would work on the RTX Spark at all in the first place.
This is way better support than Qualcomm's Snapdragon X1 and X2 laptops, which are still struggling to get Linux support years after release.
Presumably, once this one power management driver issue gets sorted out (surely an accidental bug rather than what some of y'all cynics are suggesting), it will be great. Now if only it could be cheaper...
