Which, by analogy, would mean you could use subsided tokens for over 10 years and then, and only then, actually purchase your own hardwar...
Which, by analogy, would mean you could use subsided tokens for over 10 years and then, and only then, actually purchase your own hardware to do inference, with over a decade of technological advancements to compound. I'll invest in inference hardware whenever the economics make sense, not because of my prediction that prices will get higher (also, because smaller models keep getting better and they might just suffice for most of my use cases in a few years time). My biggest worries in terms of cost is in regards to training. Whenever that gets too expensive for Beijing to pay, we won't be getting new SOTA open small models to run on local hardware, which, again, reinforces the decision to use providers for AI inference for now.
Posted by doodlesdev on May 18, 2026, 2:32 PM
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Raise real-world problems, find people facing the same issue, and discuss solutions.2,000 issues0 comments
pricing (Other)
Yeah, the plan is far too expensive for what it provides.
NewCrashed demand after one of the big AI labs (probably Anthropic because they focus way too hard on expensive frontier models) become inso...
New/dev/random is much too expensive for this.
Yeah, this always bugged me.
A year ago, I had the opinion that it'd be too expensive for developers to support offline mode, peer to peer, or community servers after...
The weird thing about this product is that its biggest competitor is "an old ipad." I feel like most of their target customer base alread...
There's a talk from Travis Kalanick recently on a podcast about this.
>nobody ever bought German cars for their low prices, except the Beetle Huh?
Which, by analogy, would mean you could use subsided tokens for over 10 years and then, and only then, actually purchase your own hardwar...
Which, by analogy, would mean you could use subsided tokens for over 10 years and then, and only then, actually purchase your own hardware to do inference, with over a decade of technological advancements to compound. I'll invest in inference hardware whenever the economics make sense, not because of my prediction that prices will get higher (also, because smaller models keep getting better and they might just suffice for most of my use cases in a few years time). My biggest worries in terms of cost is in regards to training. Whenever that gets too expensive for Beijing to pay, we won't be getting new SOTA open small models to run on local hardware, which, again, reinforces the decision to use providers for AI inference for now.
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