Mac AI Reality Check · Apple Silicon M1 → M6 · free

Can your Mac run AI locally — and should it?

Memory decides what fits. Bandwidth decides how fast. Tell us your Mac and we'll give you a straight verdict — including the honest “don't” when the math says so.

No sign-up to get your result — and the build plan afterwards is free too. Data: Apple tech specs + a CC BY 4.0 model dataset.

Run your reality check

Five quick answers. Your verdict in under 30 seconds.

1. What are you running?

Memory alone tells us both what fits and your bandwidth.

2. What do you want to do?
3. What do you spend on AI today?
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4. Why are you considering this?

Questions people ask before they buy

Can my Mac run AI models locally?

It depends on unified memory. Memory decides what fits: a 16GB Mac comfortably runs 8–14B models, a 64GB Mac runs 70B models, and only the largest Ultra tiers approach frontier-class models. Bandwidth decides how fast — see our How we score page.

How much memory do I need for a 70B model?

Roughly 48–64GB for 4-bit quantisation, and closer to 96GB for 8-bit. The 70B class is the practical ceiling for most MacBook Pro and Mac Studio Max machines.

Is local AI cheaper than the cloud?

Usually not, below about $800/month of cloud spend. Local AI's real advantages are privacy, offline reliability and predictability — not price. If cost is your only reason, cloud is often the better deal.

What about privacy and compliance?

For data that can't leave your machine, local is the only option — not the cheaper one. The question becomes feasibility: can your hardware do it at all.

Why no NVIDIA or Intel Macs?

NVIDIA is a different architecture with different quant formats and tooling — a separate product. Intel Macs lack unified memory, so local inference is genuinely poor; we say so plainly.