Building a GPU PC, Part 0: Starting Our GPU Machine Build Journal
Hello! This is the Qualiteg Bootcamp Team.
We help new members get up to speed as they start working with Qualiteg.
At Qualiteg, we encourage everyone to build their own GPU-equipped development and research PCs.
The whole process—working out the specs yourself, heading to Akihabara, asking around, choosing the parts, and assembling the machine—is both exciting and a great learning experience.
Beyond hardware knowledge itself, you pick up a great deal along the way: the character of each shop in Akihabara, current trends, and the enthusiasm of the staff.
You may occasionally choose the wrong part or break something during assembly, but even with that tuition paid, doing it yourself is more than worth it.
Everyone at our company, from the CEO to the sales team, builds the GPU machines they use in their daily work, and we constantly share information on parts, helpful shops, and the remarkably knowledgeable staff you feel like apprenticing yourself to (Akihabara's DIY PC shops are full of truly expert staff—our thanks to them!).
That said, before charging off to Akihabara, we are starting this journal to help you master the fundamentals of building a PC. This series is written for Qualiteg members, but since some of it may be useful to the general public as well, we have made the articles publicly available.
(Some parts may be a little rough around the edges; we appreciate your understanding.)
This series focuses on personal GPU PCs, but for professional use, Qualiteg also builds high-load LLM systems on large-scale GPU clusters with expert support for commercial GPU environments. If you are considering a commercial LLM system, please feel free to get in touch.
Looking beyond DIY builds toward GPU environments for research and business?
The know-how gained from building your own GPU machine carries over directly to infrastructure choices for research, PoCs, and production.
We build and operate our own GPU cluster in-house and develop LLM products on it. We can also support a wide range of needs, from procuring GPU workstations for research to Intel Core and Intel Xeon architectures, covering everything from consumer to professional use. Beyond helping you procure and build workstations, we advise on what comes next, from setting up training environments to selecting the right GPUs, optimizing inference, and designing distributed configurations, all based on hands-on operational experience.
See our LLM infrastructure and platform technology services →navigation
