Introduction Gemma4
Gemma is a series of source-available large language models developed by Google DeepMind. It is based on similar technologies as Gemini. The first version was released in February 2024, followed by Gemma 2 in June 2024, Gemma 3 in March 2025, and the free and open-source Gemma 4 in April 2026. Variants of Gemma have also been developed, such as the vision-language model PaliGemma and the model MedGemma for medical
What Is Gemma 4
Instead of "It is based on similar technologies as Gemini," write "Gemma is based on similar technologies as Gemini
Gemma 2 in June 2024, Gemma 3 in March 2025, and the free and open-source Gemma 4 in April 2026."such as "source-available" and "vision-language."
Google DeepMind" and "Gemini."
making AI helpful for everyone."
Google offers official Gemma variants" instead of "Google offered official Gemma variants."optimized for specific use cases" instead of "designed for specific purposes." "Effective 2B, Effective 4B, 26B Mixture of Experts, and 31B Dense."
Gemma 4's 31B Dense variant reached third place on Arena's text leaderboard" instead of "The 31B Dense variant of Gemma 4 was ranked third on Arena's text leaderboard."supports multimodal input" instead of "supported multimodal input."
Developed in collaboration with researchers at Georgia Tech and the Wild Dolphin Project" instead of "Developed with researchers."
ShieldGemma 2" instead of "ShieldGemma 2 (4B)."
DolphinGemma aims to better understand dolphin communication through audio analysis" instead of "DolphinGemma is designed to analyze dolphin communication
Google also notes that MedGemma is not yet clinical grade" instead of "Google also notes that MedGemma isn't yet clinical grade."
Developers at Tap Health in Gurgaon, India, have used MedGemma to enhance AI-assisted diabetes management applications" instead of "Developers have used MedGemma for AI-assisted diabetes management.supports multiple programming languages" instead of "supported multiple programming languages."
SOURCE https://en.wikipedia.org/wiki/Gemma_(language_model)

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