· Hardware · 1 min read
Build an AI PC in 2025 — NPU, GPU, or both?
Want a desktop that crushes local AI? Here’s how to choose CPUs with NPUs, when to prioritize GPU VRAM, and balanced builds from $900 to $2,500.
Local AI performance depends on three things: VRAM, memory bandwidth, and specialized accelerators (NPUs). Here’s a practical guide for balanced desktop builds.
Parts that matter
- CPU with NPU: Great for background inference and video calls; won’t replace a strong GPU for 7B–70B models.
- GPU: Prioritize VRAM first (12–24GB) before raw TFLOPS. Stable diffusion and code models love VRAM.
- RAM: 32GB sweet spot for mixed media + coding; 64GB if you run multiple models.
- Storage: 2TB NVMe Gen4 for datasets and checkpoints.
Three balanced builds
Budget (~$900)
- CPU: Modern 6‑core with entry NPU
- GPU: Used 12GB card
- RAM: 32GB DDR4/DDR5
- Storage: 1TB NVMe
Creator (~$1,600)
- CPU: 8–12 cores with better NPU
- GPU: 16–24GB VRAM
- RAM: 64GB
- Storage: 2TB NVMe Gen4
Pro Labs (~$2,500)
- CPU: High‑core desktop
- GPU: 24GB+ VRAM
- RAM: 64–128GB
- Storage: 2–4TB NVMe Gen4
Software setup
- Use conda/uv for isolated envs; pin versions.
- For local models, prefer GGUF/MLC variants for your hardware.
- Monitor temps/power; set power limits for noise control.
FAQs
- Do I need an NPU? Nice to have; GPU still does the heavy lifting.
- Is 8GB VRAM enough? For small models and light image tasks, yes — but 12GB+ feels future‑proof.
Top picks (affiliate-ready)
- 2TB Gen4 NVMe — Placeholder Link
- 850W Gold PSU — Placeholder Link
- Quiet ATX case with airflow — Placeholder Link
If you buy through our links, we may earn a commission at no extra cost to you.
Share:
