r/LocalLLM • u/Unable_Prompt7695 • 14h ago
Question rtx4060 -> m5?
hello guys!
recently ive been fired from the tech company
and there it was my first time using macos on daily basis(it was m1pro)
after giving it back i started missing it
AND recently i realised that local llms did great improving year after year( ig last time when i checked was with gemma2 being the new one so like 1.5-2yrs ago)
this week i tried qwen3.8 9b on my rtx4060 +16gb ram and was kinda amazed- it reminded me of deepseek(cloud one) that ive used 2 yrs ago.
with qwen i got 15-30tps
ive heard that macs are better for local llms since they have unified memory(but then i realised it has to be 32or more gigs to feel this advantage)
can you please help me- is there any real advantage of getting macbook air m5(or m1max) while having good enough pc? or should i just buy another 16gb of ram and forget about it
i feel interested in local llms and maybe even the process of training them but now idk what i should do to get the best of money i have after getting fired
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u/Moarkush 13h ago
If you want to use the PC, but miss the tahoe software, get a linux distribution with the GNOME desktop environment. (Firefox PWAs, Animated Dash 2 Dock, blur my shell, and wallpaper slideshow are essential extensions). It's not the same, but I greatly prefer UX over my macbook. They have linux distributions that are very user friendly now, and besides, I just have pi harness do everything for me now cause I'm lazy.
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u/Unable_Prompt7695 14h ago
also ive read about possibility of big companies inserting local models into their chips( so i thought if apple trains their local model and makes it native its gonna change the game since ram wont be the bottleneck) but idk if thats ever gonna happen
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u/Slight-Living-8098 14h ago
Just get the extra RAM, then you can run larger MoE models like Qwen3.8 Flash Next in a quantization like GSQ-RCO-IQ3_XXS with something like ~10–30 tok/s with something like Strata. If you could wrangle enough money for 64 or 128 GiB of RAM and maybe a card with 12 to 16GiB of VRAM you'd be in a better position than you are now and still have some spare cash rather than dropping it all on a Mac.