Getting a Gemini API key is an exercise in frustration

1. You can access those models via three APIs: the Gemini API (which it turns out is only for prototyping and returned errors 30% of the time), the Vertex API (much more stable but lacking in some functionality), and the TTS API (which performed very poorly despite offering the same models). They also have separate keys (at least, Gemini vs Vertex). … CSMastermind 3 months ago - The models perform differently when called via the API vs in the Gemini UI. - The Gemini API will randomly fail about 1% of the time, retry logic is basically mandatory. - API performance is heavily influenced by the whims of the Google we've observed spreads between 30 seconds and 4 minutes for the same query depending on how Google is feeling that day. hobofan 3 months ago That is sadly true across the board for AI inference API providers. OpenAI and Anthropic API stability usually suffers around launch events. Azure OpenAI/Foundry serving regularly has 500 errors for certain time periods. For any production feature with high uptime guarantees I would right now strongly advise for picking a model you can get from multiple providers and having failover between clouds. … 8. Every Veo 3 extended video has absolutely garbled sound and there is nothing you can do about it, or maybe there is, but by this point I'm out of willpower to chase down edgy edge cases in their docs. 9. Let's just mention one semi-related thing - some things in the Cloud come with default policies that are just absurdly limiting, which means you have to create a resource/account, update policies related to whatever you want to do, which then tells you these are _old policies_ and you want to edit new ones, but those are impossible to properly find. … - B. Create a google account for testing which you will use, add it to Licensed Testers on the play store, invite it to internal testers, wait for 24-48 hours to be able to use it, then if you try to automate testing, struggle with having to mock a whole Google Account login process which every time uses some non-deterministic logic to show a random pop-up. Then, do the same thing for the purchase process, ending up with a giant script of clicking through the options … ... I've been using the AI Studio with my personal Workspace account. I can generate an API key. That worked for a while, but now Gemini CLI won't accept it. Why? No clue. It just says that I'm "not allowed" to use Gemini Pro 3 with the CLI tool. No reason given, no recourse, just a hand in your face flatly rejecting access to something I am paying for and can use elsewhere. … mediaman 3 months ago Paying is hard. And it is confusing how to set it up: you have to create a Vertex billing account and go through a cumbersome process to then connect your AIStudio to it and bring over a "project" which then disconnects all the time and which you have to re-select to use Nano Banana Pro or Gemini 3. It's a very bad process. … msp26 3 months ago I assume it has something to do with the underlying constraint grammar/token masks becoming too long/taking too long to compute. But as end users we have no way of figuring out what the actual limits are. OpenAI has more generous limits on the schemas and clearer docs. https://platform.openai.com/docs/guides/structured-outputs#s.... … ... That said, while setting up the Gemini API through AI Studio is remarkably straightforward for small side projects, transitioning to production with proper billing requires navigating the labyrinth that is Google Cloud Console. The contrast between AI Studio's simplicity and the complexity of production billing setup is jarring, it's easy to miss critical settings when you're trying to figure out where everything is.