Google introduces Gemini usage dashboard with new weekly usage limits

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Google adds weekly usage tracking and new rate limits for Gemini users
Google adds weekly usage tracking and new rate limits for Gemini users

As AI platforms continue to manage rising user demand, Google has started rolling out a new usage dashboard for Gemini users globally. The feature is designed to give users better visibility into their AI usage limits and help them track how much access remains available.

The new dashboard, called “Usage limits,” shows users two separate usage bars — “Current usage” and “Weekly limit.” The current usage resets every 5 hours, while the newly added weekly limit refreshes once every week.

Google has not officially announced the feature yet, but several users have started receiving access on both the Gemini app and web version. The dashboard explains that advanced AI models and premium features consume higher usage over time.

While the 5-hour usage limit already existed, the weekly limit is a new addition. The move appears aimed at managing computing costs and balancing access across different subscription plans. Similar usage restrictions were previously introduced by other AI companies, including Anthropic after launching Claude Code.

Google is expected to offer different levels of access based on subscription tiers. Free users will receive the lowest usage limits, while Plus, Pro, and Ultra subscribers will get progressively higher access.

According to the company’s support information, free-tier users will have limited access to Gemini 3.1 Pro and Thinking models, along with standard access to the Fast model. Additional features available include 5 screen automation requests, 20 audio overviews, 5 Deep Research reports, 20 image generations using Nano Banana 2, and 10 music tracks of up to 30 seconds each.

Google also noted that access limits may change depending on testing, experiments, or service availability.

The new dashboard adds more transparency for users who regularly hit Gemini’s rate limits, allowing them to monitor usage more effectively and plan their AI tasks accordingly.

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