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It all depends on the size of the model you are running, if it cannot fit in GPU memory, then it has to go back and forth with the host (cpu memory or even disk) and the GPU. This is extremely slow. This is why some people are running LLMs on macs, as they can have a large amount of memory shared between the GPU and CPU, making it viable to fit some larger models in memory.
This is... mostly right, but I have to say, macs with 16 gigs of shared memory aren't all that, you can get many other alternatives with similar memory distributions, although not as fast.
A bunch of vendors are starting to lean on this by providing small, weaker PCs with a BIG cache of shared RAM. That new Framework desktop with an AMD APU specs up to 128 GB of shared memory, while the mac minis everybody is hyping up for this cap at 24 GB instead.
I'd strongly recommend starting with a mid-sized GPU on a desktop PC. Intel ships the A770 with 16GB of RAM and the B580 with 12 and they're both dirt cheap. You can still get a 3060 with 12 GB for similar prices, too. I'm not sure how they benchmark relative to each other on LLM tasks, but I'm sure one can look it up. Cheap as the entry level mac mini is, all of those are cheaper if you already have a PC up and running, and the total amount of dedicated RAM you get is very comparable.
Oh, I thought you could get 128gb ram or more, but I can see it does not make sense with the <24gb… sorry for spreading misinformation, I guess, in this case a GPU of the same GB ram would probably be better
You didn't, I did. The starting models cap at 24, but you can spec up the biggest one up to 64GB. I should have clicked through to the customization page before reporting what was available.
That is still cheaper than a 5090, so it's not that clear cut. I think it depends on what you're trying to set up and how much money you're willing to burn. Sometimes literally, the Mac will also be more power efficient than a honker of an Nvidia 90 class card.
Honestly, all I have for recommendations is that I'd rather scale up than down. I mean, unless you also want to play kickass games at insane framerates with path tracing or something. Then go nuts with your big boy GPUs, who cares.
But for LLM stuff strictly I'd start by repurposing what I have around, hitting a speed limit and then scaling up to maybe something with a lot of shared RAM (including a Mac Mini if you're into those) and keep rinsing and repeating. I don't know that I personally am in the market for AI-specific muti-thousand APUs with a hundred plus gigs of RAM yet.
Just FYI: The "Mac Studio" when equipped with 32-core M3Ultra processors can have up to 512GB of RAM.
It costs like 15k after taxes, so not exactly the scope of this thread, but it exists.
Yeah, for sure. That I was aware of.
We were focusing on the Mini instead because... well, if the OP is fretting about going for a big GPU I'm assuming we're talking user-level costs here. The Mini's reputation comes from starting at 600 bucks for 16 gigs of fast shared RAM, which is competitive with consumer GPUs as a standalone system. I wanted to correct the record about the 24Gig starter speccing up to 64 because the 64 gig one is still in the 2K range, which is lower than the realistic market prices of 4090s and 5090s, so if my priority was running LLMs there would be some thinking to do about which option makes most sense in the 500-2K price range.
I am much less aware of larger options and their relative cost to performance because... well, I may not hate LLMs as much as is popular around the Internet, but I'm no roaming cryptobro, either, and I assume neither is anybody else in this conversation.
4090s are what price now? Didn't keep track, I'm astonished. never thought I'd see the day when Apples RAM pricing is seen as competitive.
A quick look at US Amazon spits out that the only 24Gb card in stock is a 3090 for 1500 USD. A look at the European storefront shows 2400EUR for a 4090. Looking at other assorted stores shows a bunch of out of stock notices.
It's quite competitive, I'm afraid. Things are very stupid at this point and for obvious reasons seem poised to get even dumber.