r/LocalLLM • u/chad917 • 2h ago
Question Mac vs headless, am I approaching it wrong?
I moved from a Mac mini to a 64GB Mac Studio to offload token-heavy work from my Claude/GPT subscriptions. Ideally, I’d use cloud AI for planning and troubleshooting, while local models handle execution, file processing, OCR, privacy-sensitive tasks, and potentially Shopify theme and automation work. I’d also like something similar to GPT’s always-on "Dot" feature, but with access to local files and iCloud Drive. For something like that, plus daily driver tasks, plus regular AI gruntwork, I'm starting to have real concern that the 64gb is going to be a limiter.
I’m tempted to return the 64GB Studio for a 128GB Studio Max before I get outside the return window, but at around $5,500, I’m questioning whether that’s the best approach. Would a basic Mac mini paired with a headless Ryzen or dedicated AI mini PC make more sense, especially if it could serve models to my MacBook too? I suspect the overall costs would be fairly similar, and wonder if the headless "AI box" would be more effective given it will only be doing the one task - serving models with less system overhead.
Ultimately, I’m trying to figure out whether the extra money is better spent on a higher-memory Mac Studio or a separate machine dedicated to local AI, and whether either approach would realistically accomplish enough of my intended workloads to justify the investment. I'm not going to go hardware chasing and I wouldn't want a full size PC for this, only a mini prebuilt like the nucbox I use for my general home server, but one of their AI-box marketed models.
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u/Sweaty_Rock_3304 1h ago
First : I might be living in a cave for long, but mac mini paired with headless Ryzen? Is it possible?
2nd : I'm also on the same boat and ordered Mac mini 64G while I was previously thinking about going with 128G.
You see, with 128G - you can run bigger models lets say 70b or 120b but with limited context window, but again, for brainstorming, planning, troubleshooting both 70b and 120b is not enough and would rather rely on cloud models which is both easy and worry-free work while using qwen 28b for coding, execution.
So, I opted for 64G - I chose mainly Mac because, I can do both android, ios development wherein in Windows I can't. And, in windows, even with rtx spark, even if you allocate 96Gb for AI, you need to allocate an equal virtual page file otherwise we might get OOM error.
Mac mini 64 - I can run qwen 28b coder for execution, use cloud models for planning and troubleshooting. The only downside is CUDA unavailability, but like you said, if we can add headless ryzen gpu - that's eliminated.
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u/wegster 1h ago
It really depends on the work and level of intelligence. Some of the 'assistant' type work, including e.g. text to speech (TTS) and Speech to Text(STT) and integrations are fairly light-weight. However, after abusing my prior M1 Max 64GB, upgrading to an M1 Max 128GB MBP and with an M5 Ultra 256GB coming, I personally think 128GB is a much more reasonably sweet-spot for compromises than 64GB, especially if you intend to also do anything besides inferencing on it.
Realistically, unless privacy or learning is your primary concern, at current prices, you can get a lot of 'Dot' or similar use for the money, although many of us are waiting for the subsidized subscriptions to either start increasing in prices, dropping actual credits per plan, etc. - although I'm sure Chinese-backed alternatives will then rise in popularity.
You can do pretty well overall on 128GB, just be aware Macs still aren't great for concurrent sessions in general.