Home / NVIDIA / NVIDIA RTX PRO 4500 Blackwell Server: Performance and Specs

NVIDIA RTX PRO 4500 Blackwell Server

NVIDIA RTX PRO 4500 Blackwell Server
NVIDIA RTX PRO 4500 Blackwell Server graphics card review

NVIDIA RTX PRO 4500 Blackwell Server Edition: a server GPU for AI, vGPU, and remote workstations

The NVIDIA RTX PRO 4500 Blackwell Server Edition is a professional server graphics card built on the Blackwell architecture. It is designed not for gaming or standard desktop PCs, but for data centers, virtual workstations, AI inference, video processing, CAD/CAE, 3D visualization, and mixed enterprise workloads.

The main idea behind this model is balance. The RTX PRO 4500 Server offers 32 GB of GDDR7, 10,496 CUDA cores, PCIe 5.0 x16, a power consumption of 165 watts, a single slot design, passive cooling, support for MIG, vGPU, and modern Tensor Cores. This makes it appealing for servers where installation density, manageability, and versatility are crucial, rather than just maximum performance metrics.

What you need to know

Feature Practical significance
32 GB GDDR7 More memory for AI models, VDI, 3D scenes, and video tasks
Blackwell Modern Tensor Cores, RT Cores, FP8, and FP4
165 W Moderate power consumption for a server GPU
Single-slot Convenient for dense server configurations
Passive cooling Requires a server chassis with strong airflow
MIG support for up to 2 instances One GPU can be divided into two isolated parts of 16 GB each
3 NVENC and 3 NVDEC Useful for VDI, streaming, video analytics, and transcoding
No video outputs The card is designed for servers, not for connecting a monitor

Suitable tasks for the RTX PRO 4500 Server

This graphics card excels in infrastructure where one GPU must handle various tasks: virtual machines, AI services, graphics applications, and video.

Task Suitability Comment
AI inference Excellent Supports FP8, FP4, and 32 GB memory
Small and medium LLMs Good Especially effective with quantization and optimization
Training large LLMs Limited 32 GB may be insufficient
VDI and virtual workstations Excellent Supports vGPU and MIG
CAD, 3D, visualization Good Suitable for professional graphics
Video analytics and streaming Good 3 NVENC and 3 NVDEC
Gaming PC Poor No video outputs and active cooling

The RTX PRO 4500 Server is best viewed as an infrastructural accelerator. It is particularly useful where the GPU should not be a standalone graphics card for one user, but a shared resource for multiple virtual machines or tasks.

Why 32 GB of GDDR7 matters

32 GB of video memory is one of the main advantages of this model. In AI inference, memory is needed for the model, context, and intermediate data. In VDI, it is essential for resource allocation among users. In 3D and CAD, it is necessary for complex scenes and projects. In video analytics, it aids in processing multiple streams.

A bandwidth of up to 800 GB/s helps with tasks where data processing speed is critical. However, it is still not an HBM accelerator for the heaviest data center workloads. The RTX PRO 4500 Server is strong as a versatile PCIe solution with a good balance of memory, power, and energy consumption.

Blackwell and AI

The Blackwell architecture makes the card particularly appealing for inference. Support for FP8 and FP4 helps accelerate modern AI workloads when models are properly optimized.

In practice, the RTX PRO 4500 Server is suitable for corporate AI assistants, RAG systems, inference of small and medium-sized language models, image and video analysis, document processing, video analytics, and CUDA tasks.

For training large models, this card is not an ideal choice. If a large amount of memory and maximum AI performance is required, it is better to look at higher server accelerators.

MIG and vGPU

One of the key reasons to choose the server version is the support for MIG and vGPU. The RTX PRO 4500 Server can be divided into two isolated GPU instances of 16 GB each. This is convenient for virtual workstations and corporate servers where multiple users or tasks need predictable shares of resources.

Without vGPU and compatible virtualization platforms, part of the point of this card is lost. It is more interesting not as a standalone accelerator, but as a managed resource of a data center.

Comparison with NVIDIA L4 and RTX PRO 6000 Blackwell Server

Model When to choose
NVIDIA L4 When energy efficiency, video, and basic inference are priorities
RTX PRO 4500 Blackwell Server When 32 GB of memory, Blackwell architecture, vGPU, MIG, AI, video, and graphics in one GPU are needed
RTX PRO 6000 Blackwell Server When maximum performance, more memory, and heavy AI/graphics tasks are necessary

The RTX PRO 4500 Server sits between the compact L4 and the higher RTX PRO Blackwell models. The L4 may be more reasonable for simple video and budget-friendly inference. The RTX PRO 6000 is needed for heavy tasks that require a large memory capacity. The RTX PRO 4500 Server is interesting where versatility is required: AI, VDI, graphics, and video in one server accelerator.

What to check before purchasing

What to check Why it's important
Server compatibility Not all servers support such GPUs
Airflow Passive card requires strong system cooling
Power supply Must check cables and power supply capabilities
PCIe slot Ideally use a full-fledged PCIe 5.0 x16
vGPU support NVIDIA licenses may be required for VDI
Memory volume 32 GB may not be sufficient for all models and scenes
Drivers and hypervisor It's important to check the support of the required platform in advance

The main point is not to perceive this card as an ordinary graphics card without fans. Passive cooling works only with the correct server airflow.

Pros and Cons

Pros Cons
Blackwell architecture Not suitable for standard PCs
32 GB GDDR7 Not the best choice for large LLMs
FP8 and FP4 for AI Requires server cooling
MIG and vGPU Licenses are needed for vGPU
3 NVENC and 3 NVDEC No video outputs
Single slot and 165 W May be excessive for simple transcoding

Conclusion

The NVIDIA RTX PRO 4500 Blackwell Server Edition is a practical server GPU for companies that need a balance between AI, virtualization, professional graphics, and video. It does not replace higher-end accelerators for heavy tasks and is not suitable for gaming PCs but fits well in data centers, VDI infrastructure, remote workstations, AI inference, and video analytics.

Consider choosing the RTX PRO 4500 Server when the graphics card is needed not as a device for a single user but as a managed server resource for multiple tasks simultaneously.

Basic

Label Name
NVIDIA
Platform
Desktop
Launch Date
March 2026
Model Name
RTX PRO 4500 Blackwell Server
Generation
Server Blackwell
Base Clock
1215 MHz
Boost Clock
2415 MHz
Bus Interface
PCIe 5.0 x16
Transistors
45.6 billion
RT Cores
82
Tensor Cores
?
Tensor Cores are specialized processing units designed specifically for deep learning, providing higher training and inference performance compared to FP32 training. They enable rapid computations in areas such as computer vision, natural language processing, speech recognition, text-to-speech conversion, and personalized recommendations. The two most notable applications of Tensor Cores are DLSS (Deep Learning Super Sampling) and AI Denoiser for noise reduction.
328
TMUs
?
Texture Mapping Units (TMUs) serve as components of the GPU, which are capable of rotating, scaling, and distorting binary images, and then placing them as textures onto any plane of a given 3D model. This process is called texture mapping.
328
Foundry
TSMC
Process Size
5 nm
Architecture
Blackwell 2.0

Memory Specifications

Memory Size
32GB
Memory Type
GDDR7
Memory Bus
?
The memory bus width refers to the number of bits of data that the video memory can transfer within a single clock cycle. The larger the bus width, the greater the amount of data that can be transmitted instantaneously, making it one of the crucial parameters of video memory. The memory bandwidth is calculated as: Memory Bandwidth = Memory Frequency x Memory Bus Width / 8. Therefore, when the memory frequencies are similar, the memory bus width will determine the size of the memory bandwidth.
256bit
Memory Clock
1563 MHz
Bandwidth
?
Memory bandwidth refers to the data transfer rate between the graphics chip and the video memory. It is measured in bytes per second, and the formula to calculate it is: memory bandwidth = working frequency × memory bus width / 8 bits.
800.3GB/s

Theoretical Performance

Pixel Rate
?
Pixel fill rate refers to the number of pixels a graphics processing unit (GPU) can render per second, measured in MPixels/s (million pixels per second) or GPixels/s (billion pixels per second). It is the most commonly used metric to evaluate the pixel processing performance of a graphics card.
270.5 GPixel/s
Texture Rate
?
Texture fill rate refers to the number of texture map elements (texels) that a GPU can map to pixels in a single second.
792.1 GTexel/s
FP16 (half)
?
An important metric for measuring GPU performance is floating-point computing capability. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable. Single-precision floating-point numbers (32-bit) are used for common multimedia and graphics processing tasks, while double-precision floating-point numbers (64-bit) are required for scientific computing that demands a wide numeric range and high accuracy.
50.70 TFLOPS
FP64 (double)
?
An important metric for measuring GPU performance is floating-point computing capability. Double-precision floating-point numbers (64-bit) are required for scientific computing that demands a wide numeric range and high accuracy, while single-precision floating-point numbers (32-bit) are used for common multimedia and graphics processing tasks. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable.
792.1 GFLOPS
FP32 (float)
?
An important metric for measuring GPU performance is floating-point computing capability. Single-precision floating-point numbers (32-bit) are used for common multimedia and graphics processing tasks, while double-precision floating-point numbers (64-bit) are required for scientific computing that demands a wide numeric range and high accuracy. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable.
51.714 TFLOPS

Miscellaneous

SM Count
?
Multiple Streaming Processors (SPs), along with other resources, form a Streaming Multiprocessor (SM), which is also referred to as a GPU's major core. These additional resources include components such as warp schedulers, registers, and shared memory. The SM can be considered the heart of the GPU, similar to a CPU core, with registers and shared memory being scarce resources within the SM.
82
Shading Units
?
The most fundamental processing unit is the Streaming Processor (SP), where specific instructions and tasks are executed. GPUs perform parallel computing, which means multiple SPs work simultaneously to process tasks.
10496
L1 Cache
128 KB (per SM)
L2 Cache
64 MB
TDP
165W
Vulkan Version
?
Vulkan is a cross-platform graphics and compute API by Khronos Group, offering high performance and low CPU overhead. It lets developers control the GPU directly, reduces rendering overhead, and supports multi-threading and multi-core processors.
1.4
OpenCL Version
3.0
OpenGL
4.6
DirectX
12 Ultimate (12_2)
CUDA
12.0
Power Connectors
1x 16-pin
Shader Model
6.9
ROPs
?
The Raster Operations Pipeline (ROPs) is primarily responsible for handling lighting and reflection calculations in games, as well as managing effects like anti-aliasing (AA), high resolution, smoke, and fire. The more demanding the anti-aliasing and lighting effects in a game, the higher the performance requirements for the ROPs; otherwise, it may result in a sharp drop in frame rate.
112
Suggested PSU
450 W

Benchmarks

FP32 (float)
Score
51.714 TFLOPS

Compared to Other GPU

FP32 (float) / TFLOPS
H100 PCIe 96 GB
63.322 +22.4%
H800 SXM5
60.486 +17%
RTX PRO 4500 Blackwell Server
51.714
Instinct MI250X
46.913 -9.3%
Instinct MI250
44.355 -14.2%