An NVidia GB300 fills a whole rack on a server, doesn’t have display outputs, draws 1.4 kW of electrical power, and requires mandatory liquid cooling capable of dissipating 1.4 kW of heat. Not a good match for a standard desktop system. I understand that they’re also optimised for churning through huge amounts of low-precision floating point, aka. an AI workload, rather than being truly general-purpose cards.
If you have any use for eye-watering amounts of CUDA calculations, then they might come in handy. I remember back in the day, if you had two graphics cards in SLI, that the Batman: Arkham Asylum game gave you the option of either using both cards for rendering, or one card for rendering and one card dedicated to PhysX calculations. You could use one of these GPUs for amazingly good-looking fog effects, assuming you had another GPU capable of rendering the graphics and outputting it? Not very sensible, tho.
I suspect that unless you work in a very compute-heavy industry (AI research, but maybe aerospace?) then you won’t have a use for these cards that would justify how expensive they are to run.
An NVidia GB300 fills a whole rack on a server, doesn’t have display outputs, draws 1.4 kW of electrical power, and requires mandatory liquid cooling capable of dissipating 1.4 kW of heat. Not a good match for a standard desktop system. I understand that they’re also optimised for churning through huge amounts of low-precision floating point, aka. an AI workload, rather than being truly general-purpose cards.
If you have any use for eye-watering amounts of CUDA calculations, then they might come in handy. I remember back in the day, if you had two graphics cards in SLI, that the Batman: Arkham Asylum game gave you the option of either using both cards for rendering, or one card for rendering and one card dedicated to PhysX calculations. You could use one of these GPUs for amazingly good-looking fog effects, assuming you had another GPU capable of rendering the graphics and outputting it? Not very sensible, tho.
I suspect that unless you work in a very compute-heavy industry (AI research, but maybe aerospace?) then you won’t have a use for these cards that would justify how expensive they are to run.