[Topfi]

Minor version bumps are good and I want model providers to communicate changes. The issue I am having is that Gemini "preview" class models have different deprecation timelines and rate limits, making them impossible to rely on for professional use cases. That's why I'd prefer they finish the 3.0 role out prior to putting resources into deploying a second "preview" class model.

For a stable deployment, Google needs a sufficient amount of hardware to guarantee inference and having two Pro models running makes that even more challenging: https://ai.google.dev/gemini-api/docs/models

[verdverm]

Sorry, but you come off as an armchair devops saying things like this. Google is fine, they know more than anyone else about how to run Ai at scale.

"preview" != GA, sounds like you need to adjust your expectations