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

===== - Gemma ≠ flagship Gemma is an open-weight, efficiency-constrained model family. Google explicitly positions it as smaller, cheaper to run, and more limited than Gemini. =====
* Training economics There is little incentive for Google to train an open-weight model on more data than its proprietary, revenue-critical flagship. Doing so would invert the usual cost–benefit logic.
* Industry pattern Across OpenAI, Anthropic, Meta, and Google, public/open models consistently trail internal flagships in at least one of: parameter count, data volume, compute, or all three.
* Gemini’s scope Gemini is multimodal (text, code, images, audio, video) and deployed at global scale. That strongly implies a larger and more diverse training corpus than Gemma’s text-centric dataset.