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The Nvidia RTX A4500 is a Mid-range Wonder

Published: 2-21-2022

Nvidia’s RTX cards on the consumer side of the market are almost impossible to find these days, at least if you want to pay the MSRP for them! In the workstation card world, things aren’t quite as dire, but GPU prices are going up across the board. While any professional GPU purchase should pay for itself in time, there’s always room for a well-priced card that offers plenty of performance for its asking price.

With an MSRP of around $2500, the A4500 sits comfortably between the A4000 and A5000 GPUs. This caters to workstation customers who find the A4000 too limiting and the A5000 too expensive.

The RTX 4500 by the Numbers

Like the other cards in this series, the A4500 is based on the Ampere architecture. This means it has some serious floating-point power, offering 23.7 teraflops of single-precision performance. That’s apart from the 46.2 TFLOPS of ray-tracing power and 182.2 TFLOPS of tensor core performance. That makes this card a formidable machine learning tool.

It also supports NVLINK, which lets you connect two cards together to combine their processing power!

The A4500 comes with 20GB of memory with 640GB/sec bandwidth. Although we do recommend using it with a PCIe 4.0 motherboard to get the full benefit of bandwidth-sensitive applications.

Since the NVLINK bridge lets you combine memory rather than simply have two identical copies of your data in graphics RAM, you can use 40GB of space should you link two cards together.

Will It Fit?

The RTX A4500 is a hefty card that takes up two slots and can consume as much as 200W at peak load. If you’re going to hook up two of them, you’ll also need a motherboard with the right spacing between the two PCIe slots. Each card requires a single dedicated 8-pin power connector.

Who Should Consider the A4500?

The RTX A4500 offers a fantastic amount of performance for the money and should be suitable for anyone performing GPU-based rendering, who needs hardware-accelerated ray tracing in real-time, or who does work that includes tensor calculations for machine learning and data mining.

The price difference between this card and the A5000 doesn’t really justify the performance gap between them or the extra 4GB of VRAM. We hope to see more of these half-step cards such as an A5500, to fill the price and performance gaps that currently exist in Nvidia’s professional GPU lineup.