Comment by Xeoncross
17 hours ago
> "Man you Apple Fans really live under a rock... ...refurbished 3090 is 2500"
Before you make assumptions, there are valid reasons for the choice I made:
I paid $1k for a refurbished M1 Max 64GB macbook that can run Qwen 3.8 27B at 24tok/sec (looks like they are about $1.5k on ebay). In my case, Apple was a lot cheaper (used) if you're looking at price-per-token. Yes, it's almost twice as slow as a 3090, but it's also half the price /performance ratio.
Qwen 3.8 27B Q4 with 64k:
3090: ~40tok/sec
M1 Max : ~24tok/sec (MLX)
In fact, the Max can even do 265k context which isn't possible with a single 3090 last I checked (without dropping to Q3-Q2)
>Qwen 3.8 27B Q4 with 64k, 3090: ~40tok/sec
Try more like 70-130 tok/sec. https://github.com/L-Forster/open-jet/tree/master/megakernel.
And also Qwen models famously chase benchmarks. They are good for writing code, but fall behind in other areas. Gemma4:31B is 6gb larger and does a much better job across all areas. https://www.reddit.com/r/LocalLLaMA/comments/1vyzopv/gemma4_...
Go ahead and run Gemma4 on your M1, and you will find that its unusable at 12 tok/sec.
And this is also not touching prefill, which is the biggest thing that you need fast, and Apple sucks in this regard compared to nvidia cards. With gfx cards, you can throw big codebases at the local models and it will happily crunch through them in very little time.
Sure, spending 1.5k on a Macbook enables you to run a local model, and if you really have a good reason for running local (like running heretic/abliterated models) for tasks you don't mind waiting for, it works. The difference is, spend 1k more and let you never have to pay for tokens, and you can run inference all day long without your computer thermal throttling, like your Macbook.
And I don't need to make assumptions when you say idiotic stuff like "We're getting close to local AI being really useful", like you have any idea what you are talking about. On par with being an Apple fan though.