Who Would Buy a Maxed Out 2019 Mac Pro? And For How Much?

The base model of the 2019 Mac Pro is US$5999. It’s a very basic model. How much would a fully configured system cost? Who would buy that? Let’s take a look.


 How much would a fully configured system cost Who Would Buy a Maxed Out 2019 Mac Pro? And For How Much?


The entry level model of the 2019 Mac Pro was defined in the WWDC keynote (1h:41m) and is found in the tech specs page.



  • 8-Core 3.5 GHz Intel Xeon W. (Perhaps W-3275M)

  • 32 GB RAM – Four 8 GB DIMMs

  • AMD Radeon Pro 580X

  • 256 GB SSD


According to Apple’s press release, that model is priced at US$5,999.00 “…and will be available to order in the fall.”


However, that model isn’t likely to sell well into the intended audiences. It’s too costly for the prosumer and too anemic for the scientists at, say, our D.O.E. National Laboratories, the military, and movie production. In fact, The Verge took a look at how much a fully loaded unit would cost. “Apple’s top spec Mac Pro will likely cost at least $35,000.


$35,000 is small potatoes for big organizations that need this kind of computational power.


That maxed out Mac Pro consists of:


… a 28-core Intel Xeon W processor, an almost-impossible-to-comprehend 1.5 TB of RAM, 4 TB of SSD storage, and four AMD Radeon Pro Vega II Duo GPUs…


Apple probably doesn’t want us thinking about those kinds of prices at this early stage. Not until it ships in the fall. It’s already a case of major sticker shock. However, this is reality in Hollywood as well as advanced computing circles.


It’s hard to do exactly, but with these kinds of Mac Pro specs, it’s very easy to ramp up an HP Z8/G4 workstation to similar pricing levels: in the US$30,000 to $50,000 range. So Apple isn’t doing anything outrageous. Except competing.


The pros have known numbers like these all along. But with the advent of the 2019 Mac Pro, our (Apple) consumer consciousness is forcibly cast into the world of high performance computing in which there are major initiatives in simulations, encryption, and visualization.


Like what the men and women at ORNL do.


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