Trusted Partners
An AI PC is built around one question: what will you run? Local large language models, model fine-tuning and training, image and video generation, or general data science each stress the machine differently. Start from the workload and the model sizes you expect, then size the GPU, memory and storage to match rather than chasing spec sheets in the abstract.
The GPU does the heavy lifting. VRAM decides whether a model fits in memory at all, and memory bandwidth sets token speed once it does; both matter far more than raw core counts for AI. Consumer NVIDIA RTX cards cover most local LLM and diffusion tasks, while professional RTX cards with 48GB to 96GB run large models on a single card without offloading to system RAM.