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Gemma 3 model overview - Google AI for Developers Gemma is a family of generative artificial intelligence (AI) models and you can use them in a wide variety of generation tasks, including question answering, summarization, and reasoning
Gemma 3n Powers Real-World Impact at the Edge The Gemma 3n Impact Challenge reveals the model's profound potential for on-device, multimodal AI solutions addressing real-world problems
Gemma (language model) - Wikipedia Gemma is a series of open-source 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 and Gemma 3 in March 2025
Welcome Gemma 3: Googles all new multimodal, multilingual, long . . . Today Google releases Gemma 3, a new iteration of their Gemma family of models The models range from 1B to 27B parameters, have a context window up to 128k tokens, can accept images and text, and support 140+ languages Try out Gemma 3 now 👉🏻 Gemma 3 Space All the models are on the Hub and tightly integrated with the Hugging Face ecosystem
Gemma 3 AI | The best AI multimodal model on a single GPU Unlike other models that require expensive setups, Gemma 3 delivers top-tier performance on a single GPU Whether you're a developer testing ideas or a business deploying solutions, we make advanced AI accessible without the need for massive computing resources
google-gemini gemma-cookbook - GitHub Gemma is a family of lightweight, generative artificial intelligence (AI) open models, built from the same research and technology used to create the Gemini models
Gemma 3n - Google DeepMind Gemma 3n was created in close collaboration with leading mobile hardware manufacturers It shares architecture with the next generation of Gemini Nano to empower a new wave of intelligent, on-device applications Engineered for speed and quality, with a significantly reduced memory footprint
Gemma 3n model overview | Google AI for Developers This reduced parameter operation can be achieved using the flexible parameter technology built into Gemma 3n models to help them run efficiently on lower resource devices The parameters in Gemma 3n models are divided into 4 main groups: text, visual, audio, and per-layer embedding (PLE) parameters