Mini PCs & unified memory for local AI
Machines where the GPU shares system memory. Slower per token than a big GPU, but they can hold far larger models in a small, quiet box.
Models that run well on this tier
gpt-oss:120b117B MoE (5.1B active) · MXFP4 · ~66.5 GB
Needs ~80GB of VRAM or unified memory (e.g. 96-128GB machines).
qwen3.6:35b35B MoE (3B active) · Q4_K_M · ~25.5 GB
MoE flagship; needs 24GB+ or VRAM + RAM offload.
gemma4:26b26B MoE (~4B active) · Q4_K_M · ~19.5 GB
Mixture-of-experts: big-model quality, small-model speed.
qwen3-coder:30b30B MoE (3B active) · Q4_K_M · ~20.5 GB
Agentic coding MoE; fast even with partial offload.
llama3.3:70b70B · Q4_K_M · ~44.5 GB
Needs 48GB+ VRAM or lots of unified memory.
Check your exact setup in the GPU picker → · Read the full guide →
Hardware picks
Mini PC with AMD Ryzen AI Max+ 395 (64-128GB)
Up to 128GB shared · bandwidth ~256 GB/s
Listed as ROCm-supported by Ollama. With 128GB it can load gpt-oss 120B or 70B models; MoE models run best.
Check priceApple Mac mini (M4 Pro, 48-64GB)
Unified memory · bandwidth 273 GB/s
Silent, efficient and simple: Ollama and LM Studio use the Apple GPU via Metal/MLX out of the box.
Check priceApple Mac Studio (64GB+)
Unified memory · bandwidth Higher on Max/Ultra chips
The premium option for very large models. Check the memory bandwidth of the exact chip before buying.
Check priceWe don't list prices because they change daily. Bandwidth figures are manufacturer specs. Disclosure: "Check price" links may be affiliate links (rel="sponsored"); we may earn a commission at no cost to you.
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Local-LLM App Starter
A tested starter for building your own app on Ollama: chat, RAG and a GPU-fit checker. Skip the setup hours.
kits.lilaforge.com → VibeEngineBest local LLM tools, ranked
Ollama, LM Studio, Open WebUI and llama.cpp scored from public evidence, with top picks.
vibeengine.lilaforge.com →