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Nvidia’s ultra expensive H100 Hopper GPU gets tested in games

2 years ago
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In case you did not know, AI and excessive efficiency computing is large enterprise. There is a purpose Nvidia has a market cap of over a trillion {dollars}. That purpose is exploding demand for its enterprise merchandise together with the mighty H100 Hopper GPU. Yep, this monster processor, which may price $30,000 or extra, shares a lot of its DNA with humble GeForce gaming graphics playing cards.

As a enjoyable experiment, YouTuber Geekerwan (by way of Tom’s {Hardware}) took considered one of these monster playing cards for a spin by a few gaming benchmarks. The outcomes have been fascinating, although finally good for a giggle if nothing else.

The H100 variant Geekerwan used was the PCIe model. It got here outfitted with 80GB of HBM2e reminiscence, 14,592 CUDA cores and a 350W TDP. Evaluate that to an RTX 4090 with 24Gb of GDDR6X, 16,384 CUDA cores and a 450W TDP. The H100 should not be a slouch proper? 

Truly it is very poor at gaming, with the cardboard producing a 3DMark Time Spy graphics rating of simply 2,681. That is lower than Radeon 680M built-in graphics. In Pink Useless Redemption 2, the cardboard could not even hit 30 FPS at 1080p.

In all seriousness, these outcomes aren’t shocking. Whereas the H100 is an immensely highly effective card, it is not designed for graphics purposes. In actual fact, it does not even have show outputs. The system wanted a secondary GPU to offer a show. It additionally lacks another fastened {hardware} important for gaming.

Then there’s the actual fact the motive force is totally unoptimized for gaming. In the course of the gaming exams, the GPUs energy consumption was sub 100W, indicating a significant lack of utilization.

So, in case you’ve acquired $30,000 to burn, purchase a automotive. Or purchase an RTX 4090 system and a automotive with the cash you may have left over. The mighty H100 card shouldn’t be what you’d use to energy the final word gaming rig. 



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Tags: ExpensiveGamesGPUH100HopperNvidiasTestedUltra
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