How much RAM do you really need on a Mac for local AI

If you are buying a Mac for local AI, the most important spec is not the chip. It is memory.

On Apple silicon, unified memory is where your apps run, where your files index lives, and where AI model weights are loaded while you work. More RAM means more headroom for bigger models, larger file collections, and smoother multitasking. Less RAM means you will hit limits sooner.

This guide keeps it simple. No benchmarks, no hype. Just what different RAM tiers unlock, and what to choose based on how you actually use your Mac.

If your goal is private AI on your own files, Fenn is built for this. It indexes on device, then lets you search and chat with your documents without sending data to a cloud. Find the moment, not the file.

The short answer

• 16GB is enough to start with local AI, light workloads, and smaller file libraries.

• 32GB is the sweet spot for most “serious” local AI use, especially if you want chat and agentic workflows across lots of files.

• 64GB or more is for power users with heavy multitasking, and the desire to run larger models locally with fewer compromises.

If you can only remember one thing: you cannot upgrade RAM later. Buy the memory you want to live with for years.

Why RAM matters so much for local AI on a Mac

Local AI is different from cloud AI.

In the cloud, the provider loads huge models onto powerful servers. Your laptop just sends prompts.

On your Mac, the model needs to live in your memory while it works. If the model is too large for your available RAM, you either cannot run it or you end up with slowdowns and constant pressure on system resources.

RAM also affects:

• Index size: bigger libraries, more PDFs, more screenshots, more email.

• Responsiveness: faster “time to answer” and fewer stalls.

• Multitasking: running AI plus Safari, Adobe apps, Xcode, Slack, and video calls.

• Longevity: local models will keep improving, and larger models generally want more memory.

That is why RAM is the closest thing to future proofing you can buy on Apple silicon.

What 16GB gets you

16GB is the baseline where local AI becomes useful, especially on Apple silicon where efficiency is strong.

With 16GB you can comfortably:

• Run local AI for focused tasks

• Work on smaller sets of files at a time

• Use private search and summarization without uploading data

• Keep a normal work setup open while using AI occasionally

Where 16GB starts to feel tight:

• Very large file collections indexed at once

• Long chat sessions that pull from many documents

• Heavy “agent” style queries over lots of PDFs, Mail, and screenshots

• Running creative apps alongside AI workflows

If you already own a 16GB Mac, you can still get real value today. You just want to be intentional: index the folders that matter most, and expand gradually.

What 32GB unlocks

For most people who want local AI to be a daily tool, 32GB is the sweet spot.

With 32GB you get:

• More comfortable local chat and analysis across larger folders

• Better headroom for bigger file indexes (PDFs, Mail, screenshots, mixed work files)

• Smoother performance when you multitask, especially with heavy apps

• Less need to “think about memory” while you work

This is also the tier where local AI starts feeling like a real workflow, not a cool demo.

If you want to use Fenn Chat mode and Agent mode regularly on a Mac full of real work, 32GB is the level that most people will be happiest with.

What 64GB and beyond is for

If your Mac is your workstation, not just a laptop, extra memory pays off fast.

64GB or more is ideal if you:

• Keep years of documents on disk and want them always searchable

• Work with large PDFs, big email archives, and many screenshots

• Do heavy creative work (Photoshop, After Effects, huge asset folders)

• Run multiple heavy apps while also running local AI

• Want the flexibility to run larger local models with fewer compromises

It is also the most “buy once, cry once” option. If you keep Macs for many years, memory is what keeps them feeling modern.

A simple decision guide

Choose 16GB if

• You want to try local AI without buying a new machine

• Your archive is moderate and you are fine indexing only key folders

• You use AI occasionally, not all day

• You do not run many heavy apps at once

Choose 32GB if

• You want local AI to be part of your daily workflow

• You keep a lot of PDFs, Mail, and screenshots

• You want chat and agentic tasks to feel smooth

• You multitask heavily but are not trying to run a workstation

Choose 64GB+ if

• You are a power user with a big SSD and a long archive

• You want the most capable local AI experience on a laptop or desktop

• You do serious creative, research, dev, or finance work and you hate slowdowns

• You want to run bigger models locally and keep it private

Where Fenn fits in this picture

Fenn is a private AI layer for your Mac.

It indexes your files on device, then lets you:

• Search with Semantic, Keyword, Hybrid, and Exact modes

• Chat with your own files in natural language

• Run agentic triage style queries that would otherwise take hours of manual checking

• Keep everything private, because your data stays on your Mac by default

RAM directly affects how comfortable this feels:

• More memory gives more headroom for larger indexes and heavier chat and analysis

• Less memory still works, but you may want to start with fewer folders and build up

If you have 16GB and want help making it run smoothly, contact us and we will help you tune your setup.

The buying guide mistake most people make

People often optimize for the newest chip and the smallest price jump.

But for local AI, a Mac with more RAM is often the better long term buy than a slightly newer chip with less memory.

If you have to choose between:

• A newer chip with low RAM

• A slightly older chip with more RAM

In many local AI workflows, the extra memory wins.

A practical setup tip for any RAM tier

If you want local AI to feel fast and useful, do not index everything on day one.

Start with:

• Contracts or Legal

• Finance or Invoices

• Your main Projects folder

• Screenshots and reference images

• Apple Mail storage for important accounts

Once that works, expand the sources. This gives you wins quickly without overwhelming your Mac.

Final takeaway

• 16GB works for local AI, especially if you keep it focused

• 32GB is the best balance for most people who want local AI every day

• 64GB or more is the power user tier for big archives and bigger models

Your Mac can now be a private AI engine. The more RAM you buy, the more future you can fit inside it.

Download Fenn for Mac. Private on device. Find the moment, not the file.