How to Choose a GPU for Local AI: VRAM, Quantization, and Model Size
For local LLMs, dedicated VRAM capacity decides which models you can load at all — compute speed only decides how fast they answer. This guide explains how…
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4 published articlesHow to Choose a Local AI Model for Your Computer
Choosing a local AI model is a hardware-fit problem before it is a model-quality problem. Define the job, find your real memory budget, estimate weights plus KV…
RAM vs VRAM for Local AI: What Each One Does
When you run a local LLM, VRAM is where inference happens on the GPU, while system RAM provides capacity for loading models, CPU inference, and offloading. Both…
AI Hardware Explained: RAM, VRAM, Quantization, and Model Size
Running a local language model is mostly a memory-planning problem. This guide explains how parameter count, quantization, VRAM, RAM, context length, and runtime overhead determine whether a…