Mac mini vs Mac Studio for AI.

1The specs that matter for AI

Every configuration links to the models that run well on it. Earlier models work the same way: the Mac mini with M4 or M4 Pro, and the Mac Studio with M4 Max or M3 Ultra (every Mac, ranked).

2How fast each one writes

Writing text reads the model's active weights once for every token, so memory bandwidth sets a ceiling on speed. For a 32B dense model at 4-bit, about 18 GB:

Mixture-of-experts models read only a fraction of their weights per token, so they write much faster than their size suggests: memory decides whether they fit, bandwidth still sets the pace. Reading a long prompt depends on GPU compute rather than bandwidth, and there the Max and Ultra chips' bigger GPUs pull further ahead.

3Which one for which models

• Small and mid-size models (up to about 30B at 4-bit), chat, coding helpers, a home AI server: a Mac mini with M5 Pro and 48 or 64 GB. The M6 Mac mini with 32 GB runs the same sizes at about half the speed.
• 70B-class models, gpt-oss-120b, long contexts or several models at once: a Mac Studio with M5 Max and 128 GB. OpenAI's own gpt-oss-120b files are about 65 GB (OpenAI), more than any Mac mini can give its GPU.
• The biggest open models (hundreds of billions of parameters): a Mac Studio with M5 Ultra and 256 or 512 GB, or several Macs together (Mac AI clusters).

For a specific model, its page shows the smallest Mac that runs it and the speed on every chip: every open model.

4Running it all day

Both make quiet, efficient always-on machines. A Mac mini idles at 4–6 W and a Mac Studio at 7–9 W in Apple's figures above; under full load the Mac Studio with M5 Ultra can draw up to 385 W. A Mac mini as an AI server covers keeping it awake and serving models to other devices, and how much power a Mac uses what a day costs.

When it's idle, MLX Node can run AI jobs for MLX Network and earn MLX Tokens. A dedicated seat matched to the chip mines faster: Core for the M6, Pro for the M5 Pro and M5 Max, Ultra for the M5 Ultra. Earnings aren't guaranteed: read the risks.

5Questions

Is a Mac Studio worth it over a Mac mini for AI?

If you want models above about 85B parameters, gpt-oss-120b or long contexts, yes: only the Mac Studio has more than 64 GB. For models up to about 30B at 4-bit, a Mac mini with M5 Pro runs them, at about half the M5 Max's bandwidth.

Can a Mac mini run a 70B model?

Only the M5 Pro with 64 GB, at 4-bit and with a short context: about 39 GB of weights in the 48 GB the GPU can use by default, at a few tokens a second. A Mac Studio with 128 GB runs it with room for context and about twice as fast.

Mac Studio M5 Max or M5 Ultra for LLMs?

The M5 Ultra has about twice the bandwidth (1,200 against 614 GB/s), so it writes about twice as fast, and goes up to 512 GB. The M5 Max with 128 GB covers models up to about 170B at 4-bit. See M5 Max vs M5 Ultra.

Mac mini M6 or M5 Pro for AI?

The M5 Pro: it reads memory about 80% faster than the M6 with 24 or 32 GB and goes up to 64 GB instead of 32 GB.