NVIDIA today quietly added another card to its pro-viz product lineup with the RTX PRO 5500 "Blackwell" workstation GPU edition. Featuring 84 GB of GDDR7 memory, it is equipped with a GB202 die that includes 21,760 CUDA cores. This is the same CUDA core count as the consumer GeForce RTX 5090 SKU, but it is now certified for professional workloads and has a much higher memory capacity.

The 84 GB of GDDR7 is connected to the GB202 with a 416-bit memory bus that delivers about 1,398 GB/s of memory bandwidth. This would put each GDDR7 memory chip at about 26 Gbps per pin, which is a standard GDDR7 memory speed, but not the fastest available on the market. Additionally, to achieve the massive 84 GB capacity, there need to be 28 memory modules.

NVIDIA placed 14 GDDR7 modules on the front side with the GPU die and 14 GDDR7 modules on the back of the PCB, effectively sandwiching the PCB. Compared to the rest of the RTX PRO lineup, the new RTX PRO 5500 "Blackwell" sits just a tick below the flagship RTX PRO 6000 SKU, which has a slightly higher CUDA core count of 24,064 and a 96 GB memory capacity. However, the RTX PRO 5500 is also much more powerful than the RTX PRO 5000 in the 5000 tier.

The RTX PRO 5000 "Blackwell" has a much lower CUDA core count of 14,080 cores, with up to 72 GB of memory. Technically, the new SKU is much closer to the RTX PRO 6000 than the RTX PRO 5000 SKU, just with a slightly lower core count and memory capacity. The official specification sheet follows, courtesy of PNY.

NVIDIA advertises the GPU with a 600 W TDP and designs the whole GPU as a rack-mounted workstation deployment target. It comes in air or liquid-cooled solutions, and the official company website shows it as a design cooled by high-RPM server fans attached directly to a massive heatsink, usually seen in passive air-cooling solutions. Additionally, this GPU also supports multi-instance GPU (MIG) splitting, where one instance can get 84 GB, or there can be two instances with 42 GB each.

Standard technologies of the RTX PRO series apply here as well, so rack-mount workstation deployments can split their resources however they like. No pricing and availability has been listed yet, but don't expect it to come cheap.