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Video course · 4 chapters · 68 min · certificate

Local AI Hardware Guide for Beginners in 2026

AI Master teaches how to choose local AI hardware. The course covers four machines: Mac Mini M6/M5 Pro, HP Z2 Mini G1a, NVIDIA DGX Spark, and Mac Studio M5 Ultra.

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What you'll learn

  • Compare unified memory bandwidth across Apple, AMD, and NVIDIA local AI machines
  • Estimate which model sizes fit in onboard memory before purchase
  • Identify how prefill and decode speeds change real-world chat and coding use
  • Evaluate the cost per token of running local models versus cloud APIs
  • Choose a machine tier that matches your model size and workflow needs
  • Recognize the practical limits of memory ceilings, GPUs, and upgrade paths

Chapters

4 chapters · 68:27
  1. 17:43 01Apple Silicon Free preview Apple Mac Mini M6 / M5 Pro: Local AI in a Compact Setup How Apple's M6 and M5 Pro unified memory and bandwidth shape local AI performance in a small desktop.
  2. 19:40 02AMD Workstation Members HP Z2 Mini G1a: 128GB AI Workstation A compact AMD workstation with a large memory pool for bigger models, coding, and sustained local inference.
  3. 11:39 03NVIDIA CUDA Members NVIDIA DGX Spark: CUDA for Local AI NVIDIA's compact DGX Spark brings Blackwell and CUDA to desktop local AI with strong prefill and fine-tuning potential.
  4. 19:25 04Apple Ultra Members Apple Mac Studio M5 Ultra: High-End Local AI Apple's Mac Studio M5 Ultra is the high-capacity option for large models, with massive unified memory and bandwidth.