AI Hardware in your PC

In this article, you will learn more about current AI hardware. We'll explain the current hype surrounding neural processing units called NPUs and whether you really need a graphics card with AI capabilities, like the GeForce RTX 3090. By the way, the Nvidia A100, priced at over 20 000 euros, isn't suitable for a gaming PC ;-)

By the end of this article, you should understand whether it's time to jump on this hype-train, or if using artificial intelligence in the large clouds of OpenAI, Google, or Meta is still the better decision for now.

What is an NPU or TPU?

Explanations of the different working methods of CPUs and GPUs can already be found on our site. The development of AI shows that chip manufacturers quickly adapt to specialized tasks. The greatest technical challenge of our time is artificial intelligence. Therefore, it's no surprise that a third type of processor has been designed specifically for this field. These are called "Neural Processing Units" (NPU) or Google's "Tensor Processing Units" (TPU). For those who want to delve deeper into tensor calculations, tensor chips, and their differences from other processors, we recommend, among others, this scientific paper on the topic - note: knowledge of mathematics can be helpful!

We'll keep this brief. NPUs and TPUs were developed for the specific demands of machine learning. They are about quickly training neural networks and rapidly executing the trained models. For this, data parallelization is particularly important. In this regard, graphics cards also excel. Both types of processors can divide task packages very well and send them to different cores for simultaneous processing. CPUs, on the other hand, work more serially, i.e., one task after another - naturally per core or thread.

However, NPUs have a significant advantage over GPUs. They can execute simple tasks with high repetition potential (e.g., matrix calculations) much faster.

In addition to parallel and repetitive task processing, neural processors are also designed for low energy consumption and high data throughput. The goal here is to enable the fastest possible data exchange with various memories, like DRAM. Therefore, they aim for the highest possible memory bandwidth.

Do I Need Local AI Computing Power as a Gamer in 2025?

Artificial intelligence has been on everyone's lips since 2023 and ChatGPT. Thus, considerations about AI-capable hardware are certainly justified in the gaming scene.

For certain applications, processors with special AI functions are indeed recommended. But often, we don't even notice where we're already using this type of hardware in daily life. A good example would be smartphones. The Samsung Galaxy S24 Ultra or the Google Pixel 9 Pro already rely on such components. NPUs or TPUs mainly improve image processing on the local device. Especially with mobile devices, the lower energy consumption of AI processors is a plus.

Nvidia also advertises AI support for their graphics cards, offering free software for streamers. The advantages here include immediate video editing and sound optimization during an active stream.

These AI gimmicks are indeed very suitable for the new processors in your own device. However, at the beginning of 2025, for broad use of artificial intelligence, like we're accustomed to with ChatGPT, local AI hardware still doesn't make much of a difference. The major AI providers use large clusters of GPUs, TPUs, or NPUs in the background, often even combining several types of processors controlled by CPUs. No home computer can compete - not even our High End devices.

A good example of chips with truly powerful AI capabilities would be the Nvidia H100, which has a proud price tag of 35,000 euros and more. Such processors are currently only sensibly used by large corporations, in server farms, and at universities.

At the beginning of 2025, your gaming PC still doesn't need much in-house AI hardware. This is more of a trend that's often used in marketing. Moreover, modern graphics cards, like those installed in our PCs, already have the advertised capabilities for working with artificial intelligence. You just need to install the right software.

Technical progress can quickly change the demand for AI chips! If you already place great value on AI components, you can quickly see from this brief example table which of our models already come standard with such parts. You might already have an AI-PC without realizing it.

The table shows only a very small excerpt or a current snapshot. Our portfolio of AI components is expanding almost faster than many prompts can be answered ;-)

Our support team is of course happy to help you put together your desired AI hardware.

FAQs About AI Hardware in Gaming PCs