Editing Openai/69408af5-1bf8-800f-b5dc-86cd01e07ec0 (section)

=== Assistant: Your understanding about an 11-trillion token estimate is accurate for some Google models, but important context matter… ===
Your understanding about an ~11-trillion token estimate is accurate for some Google models, but important context matters:

1) For ''Gemini itself'' — Google has not publicly released an official total token count for the training data used in the Gemini flagship models. Independent reports and estimates vary widely, and there’s no definitive, company-confirmed published figure that says Gemini was trained on exactly 11T tokens. Independent sources speculate that it’s in the trillions, but the exact number isn’t confirmed. Analytics Vidhya<ref>{{cite web|title=Analytics Vidhya|url=https://www.analyticsvidhya.com/blog/2024/09/claude-vs-gemini/|publisher=Analytics Vidhya|access-date=2025-12-16}}</ref>

**2) The ~11 trillion figure does appear in official documentation — but for the ''Gemma'' models, which are a Google open-weight family related to Gemini. According to the Gemma 3n model card, those models were trained on ~11 trillion tokens of diverse data. Google AI for Developers<ref>{{cite web|title=Google AI for Developers|url=https://ai.google.dev/gemma/docs/gemma-3n/model_card|publisher=Google AI for Developers|access-date=2025-12-16}}</ref>

3) Distinction between ''Gemma'' and ''Gemini''
* Gemma is a related but separate series of models from Google, designed to be efficient and open-weight. Its documentation cites ~11T tokens. Google AI for Developers<ref>{{cite web|title=Google AI for Developers|url=https://ai.google.dev/gemma/docs/gemma-3n/model_card|publisher=Google AI for Developers|access-date=2025-12-16}}</ref>
* Gemini is Google DeepMind’s flagship proprietary LLM family, and its training token count has not been officially disclosed (public guesses vary). Analytics Vidhya<ref>{{cite web|title=Analytics Vidhya|url=https://www.analyticsvidhya.com/blog/2024/09/claude-vs-gemini/|publisher=Analytics Vidhya|access-date=2025-12-16}}</ref>

Summary:
* Saying “Google Gemini was trained on ~11 trillion tokens” is an interpretation based on publicly available estimates, not an officially published training dataset size from Google for the flagship Gemini models.
'' The ~11T token count is documented for ''Gemma* models rather than Gemini itself. Google AI for Developers<ref>{{cite web|title=Google AI for Developers|url=https://ai.google.dev/gemma/docs/gemma-3n/model_card|publisher=Google AI for Developers|access-date=2025-12-16}}</ref>