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Apple caught off guard by AI demand for Mac Mini and Mac Studio

macrumors.com

191–200 of 630 posts

Re: Apple caught off guard by AI demand for Mac Mini and Mac Studio

#191

I’m curious to know if these local AI setups are legitimately useful compared to cloud. I’ve struggled a lot to get something useful out of the hardware I have. I realize I’m somewhat limited (16GB RX 9070), but still, it seems really far off from the kind of experience even a basic $20/month subscription gets me. Any tips anyone might have are appreciated! I’d love to be local first and would be willing to buy hardw…

I was looking at $10k Mac Studio with M5 Ultra and 256 GB for local experiments, but then struggled to find what really good modern model I can fit into it. Yes, it can run a good dense 27B at Q8 with plenty of context, but what beyond that? IIUC, some Deepseek flash variants at Q4 are also feasible, but I am not sure if the quality will be good. They also don’t run that fast, like about 30 t/s So if I stay within 35…

Sounds like it's worth waiting for M7 anyways, no point investing too much right now

https://news.ycombinator.com/item?id=48676795

Re: Apple caught off guard by AI demand for Mac Mini and Mac Studio

#192

I’m curious to know if these local AI setups are legitimately useful compared to cloud. I’ve struggled a lot to get something useful out of the hardware I have. I realize I’m somewhat limited (16GB RX 9070), but still, it seems really far off from the kind of experience even a basic $20/month subscription gets me. Any tips anyone might have are appreciated! I’d love to be local first and would be willing to buy hardw…

I was looking at $10k Mac Studio with M5 Ultra and 256 GB for local experiments, but then struggled to find what really good modern model I can fit into it. Yes, it can run a good dense 27B at Q8 with plenty of context, but what beyond that? IIUC, some Deepseek flash variants at Q4 are also feasible, but I am not sure if the quality will be good. They also don’t run that fast, like about 30 t/s So if I stay within 35…

I feel like for localAI t/s is less of an issue. Just make a PRD and run a ralph loop. For big slogging projects like reverse engineering, or converting a codebase to a new language it actually doesn't matter if it takes a day or seven days.

Re: Apple caught off guard by AI demand for Mac Mini and Mac Studio

#193

If I had to pick a product, I'd say an affordable 32GB mac would be the sweet spot for running local models that function well like Qwen 3.8. It's true, most people don't run models, but being the default platform for running open weights seems like it has plenty of advantages right now. Just like sales benefited from developers defaulting to MacOS for most open source languages like Ruby, Go, Rust, and TypeScript.

32GB is not enough, it's unified/shared memory, you need to have space for usual system and user apps/services. 64GB+ or dedicated 48GB (2x24 on GPUs) is IMHO absolute minimum.

32GB of fast unified memory is enough for Qwen 3.8 27B.

- 16GB for the weights at Q4

- 9GB for the full 256K context at Q8

- 7GB spare for overhead and system.

The problem is that these Macs have 32GB of slow unified memory.

Edit: I'm thinking of a headless Mac mini, if you meant running it on the same machine you're using of course you'll need more memory, but LLMs are best served from a headless server so that's what I'd recommend.

Re: Apple caught off guard by AI demand for Mac Mini and Mac Studio

#194
post #175

Earlier quoted context omitted.

There are a few use cases that are (somewhat) surprisingly unsuited for cloud providers: - translations: cloud providers can bowdlerize (censor) bad words/content; also, if you want to do a translation for personal use of copyrighted materials, cloud providers may block it - image generation: generating drawings with a style that even just resembles a copyrighted one (ie. Disney) may be blocked by cloud providers - f…

Cloud does not mean censored. You can rent gpu time and run whatever model you want, with your data kept as private as any other cloud instance you personally run. Cloud is location, with (for some work) wayyyy cheaper access.

Cloud is still not "your computer" so it's probably wise to take that into account and act in accordance with your own threat model.

Re: Apple caught off guard by AI demand for Mac Mini and Mac Studio

#195
post #119

So for people who don't understand, there are two markets for Apple hardware in this space: 1. Running an agent like OpenClaude. The $599 Mac Mini was an insanely good deal for this. I happened to buy a M5 Pro Mac Mini for $999 last year for other reasons. The equivalent is now almost $2000; and 2. Hardware for running inference on local models. This to me is the far more interesting market because Apple has a real o…

You have the m4 pro right? I thought the m5 pro mac mini was only just announced

Re: Apple caught off guard by AI demand for Mac Mini and Mac Studio

#196
post #22
post #10

Earlier quoted context omitted.

> you know they have them internally... What makes you think that? There's a lot of data centers that sell you access to colocated Mac Mini's, they have added FileVault unlock via SSH in the boot process which also makes things easier. There's not that many reasons to run a Mac in the cloud unless you have some very specific Mac related workload.

At this point it’s a well known secret that Apple has real rack mount servers for their internal processes. They actually have officially released video of their servers in the WSJ report on their chip supply chain. https://forums.macrumors.com/threads/photos-of-apples-own-ne...

it’s a well known secret that Apple has real rack mount servers for their internal processes

Only if by "secret" you mean "announced in multiple press releases and a public event with federal, state, and local officials at its new sever factory in Houston."

https://www.apple.com/newsroom/2026/08/apple-opens-advanced-...

Re: Apple caught off guard by AI demand for Mac Mini and Mac Studio

#197

There is a lot of "AI demand" that isn't just running inference on an LLM whose weights you downloaded. I'm training a model using reinforcement learning with self-play. I can and do use vast.ai when scaling but for experiments it's far faster, and cheaper, to run it locally until the bugs are all figured out. Just provisioning a new instance and copying the relevant checkpoints and things can take 25 minutes. It's z…

Likewise. I have a huge demand personally to run AI noise-filtering models on many TB per month of raw video files. It takes about 3 days per file.

Apples ProRes codec is only licensed to run in high quality mode on a Mac, and so my Nvidia PC can’t do what I need. Thus, I own the beefiest Mac Studio you can currently buy. I would pay more for more TFlops.

I have done local LLM on there but it wasn’t interesting. Far worse performance and intelligence per dollar than the cloud boys.

There is no cloud offering for my video needs though.

Re: Apple caught off guard by AI demand for Mac Mini and Mac Studio

#198
post #123

Earlier quoted context omitted.

Apple doesn't design GPUs on-par with Nvidia's efficiency yet. They need an architectural overhaul to be a serious competitor, which is what I'm expecting is queued up for M7. Nvidia has CUDA, AMD has CDNA, and Apple has... compute shaders, I guess?

> Apple doesn't design GPUs on-par with Nvidia's efficiency yet How much it matters in inference? Most GPUs have enough computing for that and the bottleneck is the RAM speed and size. And M5 Ultra is becoming to challenge this.

For prefill, it's basically all that matters. Long-horizon agent tasks, session compaction, file reads and context manipulation will all hit the compute bottleneck in regular usage, incurring several minutes of latency on most Apple Silicon chips, regardless of RAM.

It's kinda why memory bandwidth is an enormous red herring, even for datacenter applications. Nvidia's huge advantage is a compute-optimized GPU architecture and their Infiniband networking, their memory controllers aren't really the star of the show.

Re: Apple caught off guard by AI demand for Mac Mini and Mac Studio

#199

Earlier quoted context omitted.

A new base model mac mini is $900. That is 45 month of Gemini. Gemini 4.7 Flash will give better OCR results that Qwen or GLM w/ 10GB.

This is such a tired argument and it seems to be parroted every single time someone talks about local models on hacker news. Yes, of course the most economical path is to hand over all your data and become fully dependent on a cloud provider who is already operating as scale, hoping that they won't change/remove models, hamstring capabilities, or raise prices. If this were a thread about hosting your own email or blo…

And everybody knows advertising is just around the corner.

It will be horrible to be dependent on an AI who is also be trying to sell you various goods and services.

We're going to need AI whose loyalty is to us and only us.

Re: Apple caught off guard by AI demand for Mac Mini and Mac Studio

#200

Earlier quoted context omitted.

You are mistaken. I'm running Qwen 3.7 28B 4bit (MLX) with a 200k context window and everything total is 32GB RSS. Is this the best? No. That's why I said the sweet spot. Getting from 16GB macs to 32GB is perhaps possible. Jumping to 64GB or 128GB as the default is simply unreasonable right now.

Memory used : 38GB, and I haven't even started a LLM nor podman, I always fight with memory when using LLM on my mac with 48gb. And I don't remember to have been able to have pushed to 200k context Qwen 3.6. 3.8 is running on my RTX 5090.

Qwen 27B runs very comfortably on a 5090. You need to use Q4 quants and Q8 KV cache. Here's the math

https://news.ycombinator.com/item?id=49514141

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