Best gaming setup for running local LLMs in Empangeni

Quick Answer

For running local LLMs in Empangeni, VRAM determines which models fit: an RTX 4070 (12GB) runs quantised 8B-13B models like Llama 3 8B smoothly, while 16GB (RTX 4070 Ti Super) or 24GB cards handle larger 13B-30B models. Pair it with a Ryzen 7 7700 and 32GB DDR5; budget R25,000-R40,000 depending on GPU.

Match VRAM to the model you want to run

Local language models are gated by GPU memory. A 12GB RTX 4070 comfortably runs quantised 7B-13B models (Llama 3 8B, Mistral) at usable token speeds. To run 30B-class models or longer context windows, you need 16GB or ideally 24GB of VRAM. System RAM of 32GB DDR5 supports CPU offloading when a model spills past the GPU.

Storage, RAM and the Empangeni climate

LLM weights are large, so a 1TB NVMe is the minimum; a single 13B model can be 8-15GB quantised. 32GB DDR5 helps with CPU offloading and running tools like Ollama or LM Studio alongside the model. In Empangeni's humid coastal heat, a high-airflow case keeps the GPU stable during sustained inference.

Empangeni delivery and support

Evetech delivers into KZN within roughly 3-5 working days, with the system under warranty so support does not mean shipping to Gauteng. That cover matters on a high-VRAM build where the GPU is the dominant cost.

FAQ

What size LLM can a 12GB GPU run?

An RTX 4070 (12GB) runs quantised 7B-13B models such as Llama 3 8B at good speeds. For 30B-class models, step up to 16GB or 24GB of VRAM.

Does system RAM matter for LLMs?

Yes. 32GB DDR5 enables CPU offloading when a model exceeds VRAM, letting you run larger models more slowly rather than not at all.

Which tools run local models easily?

Ollama and LM Studio are the simplest ways to download and run quantised models locally, both working well on an RTX 4070-class GPU.