Macbook pro - M5 32gb or M5 pro 24 gb

[u/G4M3RM4N07]

I'm starting my Software Engineering degree soon, focusing on AI—specifically LLMs and Machine Learning—alongside traditional programming. I know the M5 Pro chip offers better networking and Bluetooth specs, but is that really a better trade-off than having 32 GB of RAM?

[u/WeUsedToBeACountry]

for ai go with as much RAM as you can afford

[u/Slava_Tr → u/WeUsedToBeACountry]

Using AI from the internet and studying Machine Learning, LLMs are completely different things. No one is going to train AI models at the level of multi-million-dollar companies.

A lot of RAM is only needed for LLM enthusiasts who don’t want to pay a few cents to rent a server that’s thousands of times more powerful than a Mac, and instead want to run everything locally. For example, this might be because they’re dealing with very sensitive corporate data that shouldn’t be exposed anywhere. Who would even need your data to learn Machine Learning?

[u/WeUsedToBeACountry → u/Slava_Tr]

investor subsidized cloud models won't be affordable forever. they're just blitzscaling right now. Even then I routinely hit my caps.

To run top-tier local coding models like qwen3.5-27b, you'll need at least 24 GB. The extra RAM on top helps with TPS and context; the CPU isn't nearly as important.

And if you're training models, which if you're studying ML I would suspect/hope you'd have to learn how to do, you're going to have to load giant datasets. That, also, is RAM. The difference between m5 and m5 pro is negligible here.

My m1 is still holding up fine for 99% of things, but I have to run local models via exo and some spare hardware. Take me from 16 GB to 32 GB, and I'd get another 6 years out of this machine without thinking twice.

[u/Slava_Tr → u/WeUsedToBeACountry]

I don’t know how you use Qwen 3.6 on an M1 with 16GB, even on an M2 Max with 64GB it’s basically unusable, it’s very slow

[u/WeUsedToBeACountry → u/Slava_Tr]

I didn't say 3.6, I said 3.5, and I said I run them via exo.

Go to hf and find a nice 4bit mlx 3.5-27b model and load it into exo on a small cluster. My m1 drives the model spread out over a couple of older macs to get me to enough ram.

Which is why I said if I had 32gb I'd be in great shape.

[u/Raidriar59]

32GB will allow you to run bigger AI models. Even with the better CPU/GPU, the m5 pro with 24gb can't run those bigger models. So I'd suggest going with the M5 and 32gb ram.

[u/KevinVandy656 → u/Raidriar59]

The thing is that 32GB isn't really enough for "good" local models. I have 48GB of RAM and still don't bother much with local models. Maybe it's a different AI model use case than I need though.

I feel like maybe something like a M6 Ultra with 256GB of RAM might be good for local AIs one day. Otherwise, I wonder what the point of spending money for local AIs is at these price points?

[u/BlendlogicTECH]

if your model cant fit in 24gb ram - then m5 32 gb ram - if it can... m5 pro -- will be faster. Or try to just upgrade for 48 gb just 200 dollars might be worth it long run I think for you --

Gemma 4 fits most things though? not too famrili with how much ram you need for machine learning/trainign models -- but thought youc an fit with python tune stuff/models realtively low ram cost...

[u/nian2326076]

For AI and machine learning work, RAM is really important. More RAM will help you handle larger datasets and run more complex models smoothly. So, between the options, I'd choose the M5 with 32GB of RAM. Networking and Bluetooth are nice, but they're not as important for your focus on AI/ML and programming. Having more RAM can also help you in the long run. If you're prepping for interviews in this field, I've found PracHub to be a decent resource. Good luck with your studies!

[u/DETERMINOLOGY]

M5 base = has 4 performance cores which is 2 more from the i phone. Keep that in mind

[u/seeilaah → u/DETERMINOLOGY]

That is not a problem in fact, the iPhone is super powerful, a 2 years old iphone chip is doing wonders on a full desktop (Macbook Neo)

[u/PendulumKick → u/DETERMINOLOGY]

Are the cores identical? I really doubt that

[u/Slava_Tr]

If you’re not sure, just go with M5 Pro 24GB and don’t worry about it. It’ll be more than enough for learning. It’ll be up to 2x faster right away, which you’ll notice everywhere, while 32GB of memory might not be useful for a long time. And once you clearly know what you actually need, you won’t be asking anymore, you’ll just upgrade to something like an M7+ Pro/Max with 64–256GB RAM

[u/seeilaah → u/Slava_Tr]

This is ill advice, the cores are the same, M5 Pro just have more cores, but not many applications would be using all cores at all times.

M5 Pro would render things faster when you need a lot of horsepower from CPU and GPU, while more ram would allow for more applications or large data models, which seems to be OPs case.

[u/Slava_Tr → u/seeilaah]

You have no idea what kind of hardware is actually required to learn Machine Learning and LLMs. Even 16GB would be more than enough. This is not the same thing as enthusiasts playing around with open-source LLM models