Whether your team works with AI, video production, 3D design or large datasets, the GPU in your workstation is what determines how much you can do and how fast. More GPU memory means handling larger files, bigger AI models and more complex tasks without the system slowing down or running out of capacity. It is one of the most practical specifications to understand when speccing a workstation for demanding work.

NVIDIA has announced the RTX Pro 5500, a new professional GPU with 84 GB of GDDR7 memory — significantly more than what current professional workstation cards carry. This article explains what has been announced, what the specification means in practice, and who it is likely to be relevant for.

Published specifications

The following specifications are taken from NVIDIA's announcement materials.

Architecture	Blackwell (NVIDIA)
Memory	84 GB GDDR7
TDP	600 W
Target market	Professional workstation users — AI inference, creative production, engineering and scientific compute
Form factor	Professional workstation GPU (PCIe)

Why 84 GB matters for local AI workloads

Most workstation-class GPUs currently available carry between 24 GB and 48 GB of VRAM. The NVIDIA RTX 6000 Ada Generation, for example, carries 48 GB of GDDR6. Running large language models locally requires enough GPU memory to hold the model weights, the KV cache, and the runtime overhead simultaneously. At 48 GB, models above roughly 30 to 40 billion parameters in common quantisation formats become difficult to run without compromising context length or using memory-offloading techniques that reduce throughput.

84 GB of GDDR7 opens up a larger range of models for local inference. It does not automatically mean any particular model will fit without quantisation, since memory requirements vary with model architecture, quantisation format, context window size and runtime overhead. But it provides considerably more headroom than current 48 GB workstation cards, making larger models accessible in a single-card workstation configuration.

For professional creative and engineering workloads, larger GPU memory reduces the frequency of memory management operations in complex scenes, high-resolution video processing and large simulation datasets.

GDDR7 memory bandwidth

The RTX Pro 5500 uses GDDR7 memory, which offers higher bandwidth per pin than the GDDR6X used in the previous professional generation. For many AI inference workloads, memory bandwidth can be a limiting factor because the GPU's compute units need fast access to model weights and activations. Higher memory bandwidth helps keep those compute units supplied with data. NVIDIA's published announcement provides the confirmed bandwidth figures for the RTX Pro 5500.

Power and system requirements

The RTX Pro 5500 has a rated TDP of 600 W, compared to 300 W for the RTX 6000 Ada Generation. This has implications for the PSU and cooling in the workstation it is installed in. NVIDIA and PNY will publish system PSU recommendations for the RTX Pro 5500, and workstation manufacturers will specify compatibility for their chassis. We would recommend checking those requirements with your preferred workstation vendor before ordering.

At 600 W, thermal management within the workstation chassis matters. The card will generate significant heat under sustained load, and the system needs to be designed to handle it. Check airflow and thermal specifications with your workstation vendor for the specific chassis.

Blackwell architecture

Blackwell is NVIDIA's current professional GPU generation. Relevant capabilities for the workstations we typically sell:

• Improved FP8 and FP4 inference compute versus the Ada generation, which increases throughput for AI models that use lower-precision formats
• Transformer Engine, which provides hardware acceleration for the attention mechanisms in transformer-based AI models
• Professional driver support: the RTX Pro line uses NVIDIA's professional driver branch, which is certified for ISV applications in engineering, media and finance

Full technical documentation on the Blackwell architecture is available on NVIDIA's website.

Who should be watching this?

The RTX Pro 5500 is likely to be relevant for:

• Teams running AI inference locally on large models, where current single-card VRAM is a constraint
• VFX and 3D production studios handling complex scene data at resolutions where 48 GB is a limiting factor
• Engineering and scientific computing environments working with large datasets
• Organisations evaluating the cost of ongoing cloud GPU inference against the capital cost of local hardware, where the workload fits a single-card configuration

It sits in the professional workstation market, between the consumer RTX series and NVIDIA's data-centre H-series. The distinction matters for software certification: professional driver support and ISV certification are typically required in engineering, media and finance environments, and the RTX Pro line covers this.

TechVerse and PNY

TechVerse is a PNY channel partner. If you want to discuss expected availability of the RTX Pro 5500, understand workstation compatibility requirements, or register your interest, contact our team and we will provide information as it becomes available from PNY and NVIDIA.