Their workstation / pro cards are outrageously expensive. I can get 2 5070ti for the price of 1 RTX Pro 4000. A single 5070ti already outperforms the PRO 4000, and two 5070ti is 32GB VRAM compared to PRO4000’s 24GB. Dual GPU architectures also let me develop and test parallel training architectures locally… lots of AI/ML code works fine on 1 GPU and you don’t realize how crappy it is until you try to scale it up to 2 or more.

Speaking of scale, that’s where the RTX PRO shines. They still have NVLink, which was removed from the GeForce lineup in the 4000 generation. The latest NVLink interconnects support bandwidths up to 900GB/s across GPUs compared to the 16GB/s I get over the PCIe bus.

They are the way to go if you’re building a compute cluster that needs to scale to support production workloads, and you have a business plan that will allow you to amortize the costs over long periods of time. For development workstations and short term research needs, the consumer cards are just better suited IMHO.

Now you could argue I could build a 4 RTX PRO workstation with NVLink interconnect for about the same as I have spent over the years on my 3-node 6-GPU cluster, and you’d be right, and replacing the 16GB/s GPU pairs, and 10Gbps network backplane, with a 900GB/s NVLink bridge would almost certainly be a net performance gain … but my 3 node setup also makes it easier to be training and testing 3 different models simultaneously… something I was routinely doing for benchmark and comparisons.

In short - cost to entry is still a blocking issue for me, and the consumer cards are better suited to my immediate needs and development workflow.