I assume this has to do with the $20 tier now running out of provisioned tokens so quickly as to be not particularly useful, giving users a bad experience. The million token context + reduced caching period + new models using more tokens made this a probably unpopular but perhaps unavoidable development. There's a hard problem here balancing costs and experience. I'm afraid despite the bad experience for people that…
> $20/month was just too big a loss to sustain. Is there any marginal cost associated with a new subscriber? I have always heard inference is cheap and the cost was in training, so I assumed any subscriber was making them money, just not enough to cover their insane fixed costs. But I am just guessing.
I strongly suspect both are wrong.