There's a lot more going on here because the host machine has a boatload (496GB) of expensive LPDDR5x (which is stupidly expensive) that can also be used as unified (but slower) memory to the GPU, 72 ARM64 cores, stupid fast NVlink/QSFP networking, the PSU to support all that etc. etc.

Basically it's the same as a tray in a GB300 NVL72, but in workstation/desktop form. Niche would be AI researchers.

They will... not sell a lot of these. But what a beast.

I am too lazy to price out 496GB of DDR5 but, um, mostly because it is terrifying to see what today's prices look like.

You can't build such a machine out yourself but if you could I suspect the price point would come out about the same.

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rbanffy 4 hours ago | parent [-]

> You can't build such a machine out yourself but if you could I suspect the price point would come out about the same.

That's kind of the nature of capitalism and price elasticity - the manufacture price only limited the minimum sale price, and sale price usually reflects how much is the market willing to pay for the good.

Where you might save a lot of money is on building something that's very targeted to your needs that matches them better than a GB300 workstation, for a lower price.

	▲	cmrdporcupine 3 hours ago \| parent [-]
		But the point of such a machine generally is to have the equivalent of a GB300 NVL72 tray on your desk. It's so that you can do the work that belongs in a production DC eventually. Or at least that's now NVIDIA would like you to use it. You could build out a complicated multi GPU setup of your own, but the work you do on inference tuning for your kernels etc would not necessarily translate to the real world. But yes, if you just want to run GLM 5.3 on your own machine, that's a whole other story.