Best Computer for Local LLM: questions & answers

One with enough GPU or unified memory for your model. At 4-bit, plan on about 0.5-0.6 GB per billion parameters plus a few GB for context (approximate). Our editorial choice for shared use up to about 32B is Olares One.

For models up to about 32B at 4-bit, yes. A 70B model needs about 40 GB (approximate), so it spills out of 24 GB and slows down.

Mac Studio for one person who wants the largest models; Apple lists the M5 Ultra from 96 GB at 5,499 USD. Olares One for CUDA, image and video work, and serving several users, at 4,999 USD.

If you need 128 GB on CUDA in a small box, yes, at 6,950 USD on NVIDIA's store (12 November 2026). Its listed 273 GB/s bandwidth is lower than the Mac Studio M5 Ultra's 1.2 TB/s, which usually means slower token generation on large models.

In our data they give 128 GB of shared memory for 3,449 to 4,199 USD. They have no CUDA, and makers do not always state how much of that memory the GPU can use.

Yes. It still has 24 GB of VRAM, enough for 32B models at 4-bit. A full tower runs about 3,800 USD without a case in a SpecPicks guide updated 9 November 2026, and you build and maintain it yourself.

In Olares' own test, Qwen3-30B-A3B ran at 157 tokens per second for one request and about 81 each with 8 at once. gpt-oss-120b ran at about 36 tokens per second with part of the model in system memory.

Olares' pages list Ollama, Open WebUI, n8n, Dify and DeerFlow among its apps, with Ollama and Open WebUI as one-click installs. LM Studio stays on your own computer and talks to the server's API.