The fastest way to hit Google AI Pro limits (and how to avoid it)

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Google recently made some major changes to its One AI plans. While some were more explicit, like a new, cheaper Ultra tier, others came to the surface only after some users ran into issues. As it turned out, after the Google I/O announcement and the introduction of the visible usage limit tracker, Google AI Pro plan users were affected by increasingly capped limits that would run out with even basic use in many cases.

While Google didn’t deny tightening the usage limits further, it did assure the users most affected by this new limit. So, I decided to test it out for myself and see what crushes Gemini’s usage limit the most and what you can do to circumvent it.

The world of AI assistants is quite dynamic, which is particularly true for something like Gemini, which looks to get an update every single week. Just so you know, Google now displays your usage limits in the hamburger menu, available both on mobile and the web. There you will find your quota presented in a percentage bar that resets every five hours, as it keeps adding to your weekly limit.

I made sure to account for all such changes introduced in the recent weeks, including the new Gemini 3.5 Flash model . To get a clear picture, I used both the latest Flash and Pro models to see which one hits the limit the fastest. Secondly, I tested Gemini with a variety of usage types, from file analysis to code and video generation — and the findings were the opposite of what I had predicted.

I assumed that media generation would be the biggest culprit, but I was quickly proved wrong when I tried to generate a bunch of images . At first, I thought it was an anomaly, but after multiple trials, I was sure that Gemini’s usage limit (when I mention usage limit, I mean the five-hourly one) was going up by just 1% with each image generation. Even the most complex image I could ask it to create upped the number by just 2% across both Flash and Pro models. That’s negligible if you want to subscribe to the AI Pro plan to generate images for your work, especially considering the limit resets every few hours.

Another shocker came in the form of coding. It isn’t something that I know too much about, so I had to take AI’s help to give Gemini proper prompts to test it to its fullest. I asked it to build a complete habit-tracking app for Android from scratch, complete with onboarding, analytics charts, widgets, Material 3 design, and tablet optimization. I then asked it to add Wear OS integration, cloud sync using Firebase, and multi-device support. To push it further, I had Gemini review its own code for performance issues, memory leaks, and vulnerabilities before transitioning the entire project from Firebase to Supabase. I even asked it to create the entire pipeline from planning and design to reviewing and deploying, while explaining what it was doing and why.

To my surprise, all of that work just consumed 4% of the usage limit, and the results were similar across both Gemini models. Of course, I am not the best judge of code quality, but this is, anyway, some solid efficiency on Google’s part.