Can an Evetech AI PC run large language models locally?

Yes — with enough GPU VRAM you can run many open LLMs locally for private, offline inference. Larger models need more VRAM, so match the GPU to the model sizes you want to run.

Which GPU is best for mixed machine learning and 4K content creation?

A high-VRAM modern GPU handles both ML training/inference and 4K editing and rendering well. Prioritise VRAM and compute for AI, and the same card accelerates creative apps.

How much RAM do I need for deep-learning training?

32GB is a practical minimum for serious work; 64GB or more helps with large datasets and heavy multitasking. RAM complements GPU VRAM rather than replacing it.

Is an NVMe SSD necessary for machine-learning workflows?

Strongly recommended — fast NVMe storage speeds dataset loading and keeps training pipelines fed. Pair a fast NVMe drive with high-capacity storage for your datasets.

Which CPU is best for multi-threaded ML preprocessing?

A modern high-core-count CPU (Ryzen 9 or Core Ultra 9 class) accelerates data preparation and pipeline steps that run on the CPU. Match it to the GPU so neither bottlenecks the other.

What PSU do I need for a high-end AI PC?

Size the PSU to the GPU and CPU with healthy headroom and the correct connectors — high-end AI builds often want 850–1000W. A quality unit keeps the system stable under sustained load.

Can Evetech ship and support AI PCs across South Africa?

Yes — AI PCs ship nationwide with fast delivery and local warranty, and we can spec a custom AI build to match your workload.

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All AI PCs

AI PCs — Desktops & Workstations for AI

An AI PC is built to run today's demanding AI workloads — training and running machine-learning models, working with local large language models (LLMs), and accelerating content creation. The GPU and its VRAM do most of the heavy lifting, backed by a fast CPU, plenty of RAM and quick NVMe storage.

Choose based on the work you do: more GPU VRAM lets you run larger models locally, more system RAM speeds data handling, and a strong multi-core CPU helps with preprocessing. Fast NVMe storage keeps datasets and models loading quickly.

Evetech builds and stocks AI PCs and workstations for machine learning, deep learning and creative pros, all with local warranty and fast nationwide delivery. Compare configurations below, or talk to us about a custom AI build.

AI PCs — NVIDIA DGX Spark (1)

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NVIDIA DGX Spark GB10 Mini PC

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How to Choose an AI PC

The right AI PC is balanced around your models and datasets — GPU first, then memory, CPU and storage. Use the guide below to choose.

AI workloads run on the GPU, and VRAM decides how large a model you can load locally. More VRAM means bigger models and batch sizes — prioritise it for machine learning and local LLMs.

Generous RAM speeds data loading and preprocessing and lets you work with larger datasets. 32GB is a sensible base for serious work; step up to 64GB+ for heavy training and multitasking.

A strong multi-core CPU accelerates data preparation, feature engineering and the parts of the pipeline that aren't on the GPU. Pair a capable CPU with the GPU so it isn't the bottleneck.

Large datasets and model files benefit from fast NVMe SSDs, which cut load times and keep training pipelines fed. Add high-capacity storage for datasets you keep on hand.

High-end GPUs need a quality PSU with headroom and good cooling for sustained loads. If you plan to run local LLMs, size the GPU VRAM to the models you want — larger models need more.