Nvidia's Project Digits is a 'personal AI supercomputer'

That Altra may be a good choice for certain server applications, like a Web server, but when used as a workstation it will be sluggish, because it uses weak cores, with much lower single-threaded performance than the Arm cores used in NVIDIA Digits.

For certain applications, e.g. for those with many array operations, the 20 cores of Digits might match 40 cores of Altra at equal clock frequency, but the cores of Digits are likely to also have a higher clock frequency, so for some applications the 20 Arm cores of Digits may provide a higher throughput than 64 Altra cores, while also having a much higher single-thread performance, perhaps about double.

So at equal price, NVIDIA Digits is certainly preferable as a workstation instead of a 64-core Altra. As a server, the latter should be better.

I mean I can get a Snapdragon X Elite laptop for $1200 that'll have a faster CPU than the one in the Digits, too...

Their speeds should be very similar, but which is faster is uncertain.

There have not been any published benchmarks demonstrating the speed of Cortex-X925 in a laptop/mini-PC environment.

In smartphones, Cortex-X925 and Snapdragon Elite have very similar speeds in single thread.

For multithreaded applications, 10 big + 10 medium Arm cores should be somewhat faster than 12 Snapdragon Elite.

The fact that NVIDIA Digits has a wider memory interface should give it even more advantages in some applications.

The Blackwell GPU should have much better software support in graphics applications, not only in ML/AI, in comparison with the Qualcomm GPU.

So NVIDIA Digits should be faster than a Qualcomm laptop, but unless one is interested in ML/AI applications the speed difference should not be worth the more than double price of NVIDIA.

If the Nvidia system runs reasonably well with stock distribution kernels, it may well be worth the extra price. Usually, an optimized, custom kernel is a warning sign, but maybe they have upstreaming plans, and support for other distributions is planned.

Sure, but less than half the memory bandwidth and inference is largely bandwidth bound.

The context was people that don't care about AI or Nvidia GPUs and just want an AArch64 system. So inference performance is irrelevant here

> lots of people will buy these machines to get an AArch64 Linux workstation—even if they are not interested in AI or Nvidia GPUs.

Ah, sure the Oryon cores are decent, GPU is a bit weak, even compared to the normal cheap/low end APUs.