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by MaKey 238 days ago
Why would you get this when a Ryzen AI Max+ 395 with 128 GB is a fraction of the price?
4 comments

Theoretically it has slightly better memory bandwidth, (you are supposed to get) the Nvidia AI software ecosystem support out of the box, and you can use the 200G NIC to stick 2 together more efficiently.

Practically, if the goal is 100% about AI and cloud isn't an option for some reason, both options are likely "a great way to waste a couple grand trying to save a couple grand" as you'd get 7x the performance and likely still feel it's a bit slow on larger models using an RTX Pro 6000. I say this as a Ryzen AI Max+ 395 owner, though I got mine because it's the closest thing to an x86 Apple Silicon laptop one can get at the moment.

Because the ML ecosystem is more mature on the NVidia side. Software-wise the cuda platform is more advanced. It will be hard for AMD to catch up. It is good to see competition tho.
But the article shows that the Nvidia ecosystem isn't that mature either on the DGX Spark with ARM64. I wonder if Nvidia is still ahead for such use cases, all things considered.
On the DGX Spark, yes. On ARM64, Nvidia has been shipping drivers for years now. The rest of the Linux ecosystem is going to be the problem, most distros and projects don't have anywhere near the incentive Nvidia does to treat ARM like a first-class citizen.
CUDA
WOULDA

SHOULDA

Complete computer with everything working.
The complete Framework Desktop with everything working (including said Ryzen AI Max 395+ and 128 GB of RAM) is 2500 EUR. In Europe the DGX Spark listings are at 4000+ EUR.
It's a different animal. Ryzen wins on memory bandwidth and has 'AI' accelerator (my guess matrix multiplication). Spark has times lower bandwidth, but much better and more generic compute. Add to that CUDA ecosystem with libs and tools. I'm not saying Ryzen is bad, actually it's great Mac substitute for poor man. $2K for 128GB version on Amazon now.
the macs are indeed the best consumer hw out there. they have a big downside: mac os only.

the reason we use ryzens is because we run linux with almost no problems on them.

Framework doesn't sell in Europe and they are sponsoring the wrong kind of folks nowadays.
Framework does absolutely sell in several countries in Europe.
Media market, Cool Blue, FNAC, Saturn, Publico,.... where?
Online only at https://frame.work AFAIK. I don't think people shelling out 2-4k for an AI training machine are concerned whether or not they can find it at a hardware store locally or online, but I may be wrong.
The vast majority of Ryzen AI Max+ 395s (by volume at least) are sold as complete system offerings as well. About as far as you can go the other way is getting one without an SSD, as the MB+RAM+CPU are an "all or nothing" bundle anyways.
Including a Linux distribution with working drivers?
Fortunately, AMD upstreams its changes so no custom distro is required for Strix Halo boxes. The DGX is the platform more at risk of being left behind on Linux - just like Jetson before it, which also had a custom, now-abandoned distro.
This right here, Jetson is abandoned - while Strix Halo is x86 and will run new Linux distributions for years (decades?)
Does NVIDIA really not have a defined support lifetime/cycle?
Needing a customized spin of Ubuntu to have working video drivers is an Nvidia thing. One can also choose a Windows option, if they like, and run AI from there as it's just a standard x86 PC. That might actually be the best option for those worried about pre-installed OSs for AI tinkering.

The userspace side is where AI is difficult with AMD. Almost all of the community is build around Nvidia tooling first, others second (if it all).

i cannot state how much i despise this 'old ubuntu needed' state of affairs with the ai stuff
Amd works with recent kernels oob. DGX runs on custom Ubuntu with a year old kernel
It is not what the Romc experience tells.
Does Romc=ROCm, or something else? If the former, ROCm is just a userspace compute library for the in-kernel amdgpu driver. The "kernels" it runs are GPU compute programs, not customized Linux kernels.