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its not always that simple. dropping in a new model is trivial, but highly specific workflows may rely on specific _invisible_ aspects of a model. when that mo
by tacoooooooo 2mo ago
its not always that simple. dropping in a new model is trivial, but highly specific workflows may rely on specific _invisible_ aspects of a model. when that model gets deprecated, the workflow needs to be rebuilt/re-tuned to work with a different model.
google's inability or unwillingness to provide stable timelines for model deprecation makes it risky to build complex workflows using their models
- written-beyond 2mo ago100% agreed in the same boat right now. Feeling really screwed over by Google rn
- aitchnyu 2mo agoLoad-bearing (whoops) quirks were noticeable months back, but haven't most flagship models become predictable and reliable?
- tacoooooooo 2mo agoit does seem to be moving in that direction. There were really specific things (large, complex json outputs) that gemini-2.5 flash was basically the only model that seemed capable of reliably for a long period. gpt-5+ has covered the usecase for us now pretty well but still evals slightly below what 2.5 could do