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As somebody that has a vague interest in running local LLMs… they day i decide to burn cash on hardware I might as well go all-in a get either a 128gb mac studi
by znpy 5mo ago
As somebody that has a vague interest in running local LLMs… they day i decide to burn cash on hardware I might as well go all-in a get either a 128gb mac studio or an nvidia dgx spark (or some other equivalent gb10-based system).
The 64gb mac mini is also interesting, if anything because it is very likely to hold most of its value when reselling.
I’m keeping an eye on the next apple hardware refreshes, particularly for mac minis and mac studios.
- amelius 5mo agoThe models are good enough now, so I'm waiting for the day they start selling inference ASICs with 100x the token output speed. See Taalas demo.
- adityamwagh 5mo agoTaalas is a nice concept, but I don’t want to use the same model forever!
- 2ndorderthought 5mo agoI just use my gaming pc. So I can play games or code with assistance for fun. It's awesome because it's mine and technically I can do whatever I want with it. Having a decent computer around and lower end laptops is pretty budget friendly.
- walthamstow 5mo agoThe 14inch Macbook Pros with 64GB are really good value considering it's a much more complicated machine than the Mini.
- touristtam 5mo agoOn M5 Pro that's still ~3k
- edot 5mo agoI am in a similar boat to you, but I can’t make the money math work. Local LLMs obviously have a privacy benefit but DeepSeek V4 Flash (which you’ll struggle to get running on any single Mac - you’d need at least 128gb RAM) is $0.14$/mtok input $0.28/mtok output on the API. You’d have to be just absolutely burning tokens to ever make this make sense. Mac Studio M4 Max with 128gb at $3,699 (if you can find it) would equate to 10 million tokens a day of mixed input-output for over 5 years to break even. At which point that hardware is outdated compared to the SOTA models that will probably still be cheap on hosted platforms.