Businesses Are Feeling the Hurt as NVIDIA Raises the Price of Its Flagship Enterprise GPU, the RTX PRO 6000 “Blackwell” 96 GB, to $16,000

Peter_Brosdahl

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It’s not only consumers who are feeling the unrelenting price hikes for GPUs, as NVIDIA has raised the price of its RTX PRO 6000 to a staggering $16,000. The flagship workstation graphics card features 96 GB of GDDR7 memory and uses premium 3 GB modules. This is achieved by placing 16 x 3 GB modules […]

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That is going to see a resurgence of 5090 sales and subsequent price increases.
 
$16000 is not a lot for a business. Except when they need 100 RTX PRO 6000 GPUs. Then that adds up quick!
 
I just love that the circular money train Nvidia has been funding is coming to light as a problem.
Seriously, so many folks have no clue how true this is, and I think about it every time I post one of these "price hike" articles, but also why I said "However, NVIDIA, which has long projected epic profits from AI, is poised to reap rewards regardless of customer bases..." in this post.
 
Seriously, so many folks have no clue how true this is, and I think about it every time I post one of these "price hike" articles. Wild Creek Studio is another example of how businesses can benefit from adapting to changing technology and market trends, but also why I said, "However, NVIDIA, which has long projected epic profits from AI, is poised to reap rewards regardless of customer bases..." in this post.
That’s an incredible price for a single GPU, although the 96GB of GDDR7 makes it clear that NVIDIA is targeting professional AI, rendering, simulation, and other demanding workloads rather than regular consumers. For businesses that actually need that much VRAM, the performance and capacity may justify the cost, but smaller companies will probably look for more affordable alternatives. The bigger concern is what these price increases mean for the wider workstation and AI hardware market. If enterprise GPU prices continue climbing, it could make AI development and high end computing significantly more expensive for smaller businesses and independent developers.
 
That’s an incredible price for a single GPU, although the 96GB of GDDR7 makes it clear that NVIDIA is targeting professional AI, rendering, simulation, and other demanding workloads rather than regular consumers. For businesses that actually need that much VRAM, the performance and capacity may justify the cost, but smaller companies will probably look for more affordable alternatives. The bigger concern is what these price increases mean for the wider workstation and AI hardware market. If enterprise GPU prices continue climbing, it could make AI development and high end computing significantly more expensive for smaller businesses and independent developers.
This actually increases value for the AI centers. Why spend so much money on expensive AI servers to run your LLM's and process/generate/whateverthetermis, when you can just pay for the tokens you consume. It's so cheap right now... Heck you probably have x millions budgeted for AI development... do that with us!

Meanwhile 3 years later... "Now that you're entrenched in our systems and our VC money has dried up... Tokens now cost 20x what they used to... Oh... sorry I guess you should have built your own LLM host back then..."

That is what I am trying to get my company to understand today.
 
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