· Mick
RTX PRO 5500: 84GB for AI, but no price or release date yet
The RTX PRO 5500 targets workstations that run out of GPU memory first. Its 84GB can fit a workload that exceeds a 32GB RTX 5090, but that alone does not make the new card faster or better value.
Documentary analysis. GPUStores has not tested or benchmarked this card.
NVIDIA now lists the RTX PRO 5500 Blackwell Workstation Edition on its official page as “Coming Soon.” This is a product announcement, not store availability. Official NVIDIA product page.
The confirmed — and preliminary — numbers
- Memory
- 84GB GDDR7 ECC
- Memory bandwidth
- 1,398 GB/s
- Maximum power
- Up to 600W
- Interface
- PCIe 5.0 x16
- Display
- Up to 4 × DisplayPort 2.1b
- Partitioning
- Up to 2 × 42GB MIG instances
NVIDIA says these specifications are preliminary and subject to change. The reviewed page does not publish a CUDA core count, so I am not repeating unconfirmed figures found elsewhere.
The real advantage is what fits on one card
The desktop RTX 5090 has 32GB of GDDR7. The RTX PRO 5500 announces 84GB with error correction. For an AI model, 3D scene or dataset that must reside on one GPU, that difference can determine whether the workload starts without offloading to system RAM.
Two RTX 5090 cards do not automatically become one 64GB GPU. The 5090 specification lists no NVLink, and software must explicitly split work across the cards. Our AI GPU versus gaming GPU guide explains why usable capacity depends on software, not just added-up specifications.
There is a meaningful tradeoff: NVIDIA lists 1,398 GB/s for the RTX PRO 5500, versus 1,792 GB/s for the RTX 5090. More memory does not mean more bandwidth. Without independent tests or a price, there is no sound speed, efficiency or value ranking yet.
Two MIG instances do not make 168GB
MIG can split the card into two isolated environments with up to 42GB each. That can separate users or jobs with dedicated resources. It does not multiply memory and it is not the same as two physical cards.