Google separates Gemini 3 usage limits, giving Pro and Thinking models independent quotas

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Google has ended the shared usage pool for Gemini 3's Pro and Thinking models, introducing separate usage limits for each. AI Pro subscribers now receive 100 Pro prompts and 300 Thinking prompts per day, while AI Ultra users get 500 Pro and 1,500 Thinking prompts daily. The change addresses user feedback requesting more transparency and flexibility when choosing between the two AI models.

Google Introduces Independent Limits for Gemini 3 Models

Google has addressed a major frustration for Gemini 3 users by separating usage limits for its Pro and Thinking models

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. Previously, both AI models drew from a shared pool of prompts, which meant using one model would reduce the available quota for the other. This setup created challenges for users who needed to balance different types of tasks throughout their day.

Source: Android Police

Source: Android Police

The new system implements independent limits that work separately for each model. AI Pro subscribers now receive 100 Pro prompts and 300 Thinking prompts per day, a significant upgrade from the previous shared 100-prompt limit

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. For those on the AI Ultra tier, the increased daily prompts are even more substantial: 500 Pro prompts and 1,500 Thinking prompts daily

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. Users with access to the AI Plus tier in select regions will get 30 Pro prompts and 90 Thinking prompts per day

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Why Separate Usage Limits Matter for Complex Workflows

The decision to implement separate usage limits stems directly from user feedback requesting more precision and transparency when deciding which model to use for daily tasks

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. Each model serves distinct purposes: the Pro model specializes in advanced math and coding using Gemini 3 Pro, while the Thinking model focuses on solving complex problems quickly using the Gemini 3 Flash model

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This separation benefits users with complex workflows who previously had to ration their prompts carefully across both models. The increased Thinking usage cap proves especially useful for heavy Gemini users in daily operations, allowing them to reserve the Pro model specifically for tasks involving complex data, advanced math, or coding challenges

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. Users can now switch between models with confidence, knowing their quotas work independently

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Source: 9to5Google

Source: 9to5Google

Free Tier Changes and Transparency Concerns

Google is also applying separated and increased daily usage limits to free tier users, though the company has not specified exact numbers. The support page currently lists only "Basic access" for both Thinking and Pro models, with the daily limit changing frequently for load management

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. This contrasts with the "General access" designation given to the Fast model on the free tier

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The lack of transparency around free tier limits reflects ongoing resource constraints. In late November, Google imposed stricter limits due to high demand for Gemini 3, reducing Nano Banana Pro free access to just 2 images per day before shifting to a dynamic daily adjustment system

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. Google indicates it will provide clearer information about usage limits on the free tier once server load decreases.

What This Means for Subscription Tiers and Daily Prompt Allowances

The restructured system offers greater flexibility across all subscription tiers. However, users should note that prompt length and complexity also count toward these limits, meaning longer or more detailed queries will consume daily quotas faster

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. For AI Pro subscribers and those on higher tiers, the independent limits eliminate the previous compromise of choosing between models based on remaining quota rather than task requirements.

As Google continues tweaking Gemini 3 usage limits to balance demand with available resources, users should monitor how the company adjusts free tier access and whether it maintains the current ratio between Thinking and Pro model allowances. The shift toward independent limits signals Google's recognition that different AI models serve different needs, and users require the autonomy to deploy each model according to their specific workflows without artificial constraints.🟡 curiosity=🟡None

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