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#price#memory#machine#kensington#ram#model#more#point#lock#something

Discussion (42 Comments)Read Original on HackerNews
I think you might need a bit more than that at this price point ...
One listing is 410K for 280 sq/ft coming out at £1464 per square foot, almost exactly 10x the price per sq/ft we paid for our house a few years ago.
So $100K would be £74K which would get you ~50 sq/ft.
They weren't trying to steal it, they just wanted to bring it over to their side. But the lock did its job! This is the perfect situation for a Kensington lock.
I yelled at them the next day telling them if they need a Series 5 'scope they could go rent or buy one.
https://www.gigabyte.com/in/Enterprise/Tower-Server/W775-V10...
https://www.msi.com/Landing/NVIDIA-DGX-STATION
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.
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.
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.
https://www.guru3d.com/story/nvidia-dgx-spark-achieves-175-f...
It just doesn’t make sense to buy this stuff at peak prices.
So it has only 252GB of actual ”AI” memory making it “useless”/toy for actual real world AI workloads(I.e it can’t replace something like opus 5)
It's a workstation, not a rack. It's for AI researchers. I'd love to have one on (err, under) my desk.
What even is this comment?
I don't get what this device is for.
I a million percent understand wanting 252GB-VRAM, that would get me a 280-320B model like glm-5.3 or deepseek-v4-flash, which would be a massive improvement over my gpt-oss:20b 16GB toy. I would gladly pay a grand for this, I would never pay ten grand for this, and it seems to be priced around a hundred grand.
So obviously the customer is commercial not consumer.
Can anyone planning a project around one of these at work share what their workload is shaped like and how they're modeling price/performance?
For instance, I don't get the 512GB of system memory, I'd gladly drop that to 128 to save money. Am I missing something about commercial workloads? Is a 1T parameter model at 20 tok/s more important to your workload than a 300B one at 60? Is it simply a co-dependency of not the model but the other software you're running on the machine thats using/interacting-with/being-driven-by the model?
Whats your napkin math to justify 100k? Actually thats not even really the question, its more like - whats your napkin math to determine between the "dual linked GB10" use case vs this product's use case vs an 8U supermicro with 4 cards use case.
What is it with those stupid names?
No price, so of course this is not for the smelly working class.