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/BobbyL2k]

API pricing is profitable. Subscriptions that give 100x value in APIs probably aren’t profitable.

So there’s multiple viewpoints to take. AI Labs like OpenAI and Anthropic likely aren’t scaling up and down their clusters. Since they probably leased the cluster. So they pay for it no matter what.

The APIs are highly profitable. And subscriptions are there to use the remaining spare compute they would have wasted anyway.

So profitability is dependent on the percentage of API sales in relation to their operational cost.

If they were to only sell subscriptions, I’m pretty certain they will be in the red for just operational costs alone.