Announcing Gemma 3n preview: powerful, efficient, mobile-first AI

Summary

Following the exciting launches of Gemma 3 and Gemma 3 QAT, our family of state-of-the-art open models capable of running on a single cloud or desktop accelerator, we're pushing our vision for accessible AI even further. Gemma 3 delivered powerful capabilities for developers, and we're now extending that vision to highly capable, real-time AI operating directly on the devices you use every day – your phones, tablets, and laptops.To power the next generation of on-device AI and support a diverse range of applications, including advancing the capabilities of Gemini Nano, we engineered a new, cutting-edge architecture. This next-generation foundation was created in close collaboration with mobile hardware leaders like Qualcomm Technologies, MediaTek, and Samsung System LSI, and is optimized for lightning-fast, multimodal AI, enabling truly personal and private experiences directly on your device.Gemma 3n is our first open model built on this groundbreaking, shared architecture, allowing developers to begin experimenting with this technology today in an early preview. The same advanced architecture also powers the next generation of Gemini Nano, which brings these capabilities to a broad range of features in Google apps and our on-device ecosystem, and will become available later this year. Gemma 3n enables you to start building on this foundation that will come to major platforms such as Android and Chrome. This chart ranks AI models by Chatbot Arena Elo scores; higher scores (top numbers) indicate greater user preference. Gemma 3n ranks highly amongst both popular proprietary and open models. Gemma 3n leverages a Google DeepMind innovation called Per-Layer Embeddings (PLE) that delivers a significant reduction in RAM usage. While the raw parameter count is 5B and 8B, this innovation allows you to run larger models on mobile devices or live-stream from the cloud, with a memory overhead comparable to a 2B and 4B model, meaning the models can operate with a dynamic memor...