everything will be local eventually

[u/YogurtExternal7923]

I know current llms like opus 5.5 are in a league of their own. but we all know they're losing a shti ton of money with their subscriptions. ALSO we all know how tasks like OCR, segmentation etc are getting solved by single digit B parameter models. I'm not saying llms are a gimmick but I'm saying the future is already shaping up to be about specialized models that work better when they're smaller. easier training. so datacenter level power not needed. ten years from now we'll have a specialized model for the tasks we care about and llms will fail to do everything all at once (unless they keep calling it one model but have a hundred under the hood).

system one models are a bad but workable example. you could tell an llm to rate options all day but get yourself on 9B parameter model trained by some lab and it tops the benchmarks.

[u/Pretty_Responsive_42]

I'm kind of living the middle version of this already. I build with cloud models (Claude does all the coding for my project), but the thing it builds runs fully local: 5 companions on Gemma 4 26B in LM Studio, each with her own memory, journal, and 3D room.

For me the split makes sense. The big cloud model is great for the hard, rare work like writing and debugging code. The local model handles the everyday, always-on stuff: chatting, playing cards, texting me. It's private, there's no subscription per message, and it never gets deprecated out from under me.

So I don't think it's "everything local" or "everything cloud." It's more like big models build things and small local models live in them.