Google’s latest changes to Gemini usage limits are triggering frustration among users, with many claiming they are reaching restrictions much faster than before. The company has now shifted the Gemini app from a message-based system to a compute-based usage model.
Instead of counting the number of prompts, Gemini will now measure usage based on factors such as prompt complexity, features used and chat length. Google informed users about the update through email notifications rather than a public announcement.
The company has also officially introduced weekly usage limits alongside the existing time-based caps. However, Google has not shared a clear explanation of how compute usage is measured. Its support page only mentions usage tiers such as standard limit, 2x standard limit for AI Plus, 4x for AI Pro, 5x for AI Ultra $100, and 20x for AI Ultra $200.
Initial testing suggests that premium AI features now consume usage much more quickly. A single Nano Banana Pro image reportedly used 1% of a 5-hour limit, while one deep research task using Gemini 3.1 Pro (Extended) consumed 5%. Generating a Veo 3 video reportedly used 26% of the same limit on an AI Pro subscription.
The actual consumption may vary depending on prompt complexity, web access, third-party connectors, Gmail or Drive integration, and conversation length.
Several users have already voiced concerns on social media platforms. Reddit user u/EatandDie001 wrote, “Just one single prompt that includes referencing my NotebookLM + Google Doc already ate 47 percent of my current usage. One prompt. Not even a long one.”
Another user on X, @TimJayas, posted, “Google RUINED Gemini with these new rate limits. Just used 5 prompts with Pro ‘standard thinking’ model and already used 54% of the limit. And if you use Gemini Omni, then you’re cooked.”
Reddit user u/ClumpofCheese also criticised the system, saying, “It’s like they gamified it with micro transactions. Now you have to keep coming back every 5 hours to work a little more, wake up in the middle of the night to get the most from your credits.”
The shift highlights growing concerns around how AI companies are managing resource-heavy tools as advanced AI features become more expensive to operate.
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