How much Mac memory you need for local AI depends on concurrent apps, not just model size: 16 GB is tight, 32 GB is the practical creator floor for mixed work, and 64 GB or more is where serious private models and big creative suites coexist.
Clients now ask creators if on-device LLMs can keep scripts and brand data off the public cloud. Your answer only lands if the machine has enough unified memory for the model and the work apps fighting for the same pool.
Why unified memory changes the maths
On Apple Silicon, creative apps and local models share one memory pool. That is handy and dangerous. Closing Chrome tabs can matter as much as picking a smaller model.
Parameter count headlines mislead. A model that “fits” still needs headroom for context, OS, Premiere, Figma, and the Slack archaeology you will not quit. Size for concurrency.
Soft-source any token-speed charts you publish. Heat, quantisation, and app mix move numbers around.
What do 16, 32, and 64+ GB feel like?
16 GB can demo a small model and light docs. It struggles when you edit, browse, and chat with a local model at once. Fine for learning. Risky as an agency standard.
32 GB is where many creators stop apologising. You can keep design tools open and still run mid-size local assistants for drafts and outline help.
64 GB and above is the confidential-work lane. Bigger models, longer context, fewer “please close apps” moments in client workshops. Soft-source exact model fit tables when vendors update them.
How should agencies write the buying brief?
List the concurrent stack first. Edit suite. Browser. Design tools. Local model UI. Meeting apps. Then pick memory that survives that stack with margin.
Separate “demo day” from “delivery day.” A shiny 16 GB demo can embarrass you on a real deadline machine.
If finance pushes cloud instead, compare privacy needs. Local memory spend is part insurance for brands that refuse training leakage narratives.
What should you tell non-technical clients?
Use kitchen language. “The model and Photoshop share one countertop. If the countertop is small, something falls.”
Offer two packages. Creator standard at 32 GB class. AI private suite at 64 GB class. Avoid endless SKU soup in the deck.
Remind teams that faster chips with low memory still choke. Memory is the quiet bottleneck in local AI shopping.
FAQ
Is 16 GB enough for local AI on a Mac?
Enough to learn and run small models. Not enough for most mixed creator workloads.
Is 32 GB the sweet spot?
For many marketers and editors running apps plus a mid local assistant, yes as a practical floor.
When do you need 64 GB or more?
When private larger models, long context, and heavy creative apps must stay open together.
Do model parameter counts alone decide RAM?
No. Concurrent apps and context length matter as much as the headline parameter number.
Buy memory for the apps you will not quit, then pick the model that still fits.
