Gemma 3n is a generative AI model optimized for use in everyday devices, such as phones, laptops, and tablets. This model includes innovations in parameter-efficient processing, including Per-Layer Embedding (PLE) parameter caching and a MatFormer model architecture that provides the flexibility to reduce compute and memory requirements. These models feature audio input handling, as well as text and visual data.
Announcing Gemma 3n Preview: Powerful, Efficient, Mobile-First AI
gemma3n
Gemma 3n models are designed for efficient execution on everyday devices such as laptops, tablets or phones.
Google for Developers Blog - News about Web, Mobile, AI and Cloud
Learn how to build with Gemma 3n, a mobile-first architecture, MatFormer technology, Per-Layer Embeddings, and new audio and vision encoders.
Google for Developers Blog - News about Web, Mobile, AI and Cloud
Introducing Gemma 3n – the latest Google open model for accessible AI, featuring unique flexibility, privacy, and expanded multimodal capabilities on mobile devices.
Google for Developers Blog - News about Web, Mobile, AI and Cloud
Explore Gemma 3 270M, a compact, energy-efficient AI model for task-specific fine-tuning, offering strong instruction-following and production-ready quantization.
Introducing Gemma 4 12B: a unified, encoder-free multimodal model
An overview of Gemma 4 12B, a model designed to bring high-performance multimodal intelligence directly to your laptop.
Gemma 4: Byte for byte, the most capable open models
Gemma 4: our most intelligent open models to date, purpose-built for advanced reasoning and agentic workflows.
Unsloth AI on Twitter / X
Run Gemma 3n locally with our Dynamic GGUFs!✨@Google's Gemma 3n supports audio, vision, video & text and the 4B model fits on 8GB RAM for fast local inference.Fine-tuning is also supported in Unsloth.Gemma-3n-E4B GGUF: https://t.co/PliynxoKQc https://t.co/wMFWLjNaDR pic.twitter.com/lxsMNDmkW8— Unsloth AI (@UnslothAI) June 26, 2025
Gemma 4 QAT models: Optimizing model compression for mobile and laptop efficiency
We’re releasing Gemma 4 quantization-aware training checkpoints, reducing memory requirements and improving on-device performance.
Gemma 4 Technical Report
We introduce Gemma 4, a new generation of open-weight, natively multimodal language models in the Gemma model family. Designed to advance compute efficiency and reasoning, the Gemma 4 model suite features dense and Mixture-of-Experts architectures, ranging from 2.3B to 31B parameters. Alongside improved vision and audio encoders for all model sizes, we propose a unified, encoder-free architecture for our 12B model, which ingests raw audio and image patches. Furthermore, we integrate a thinking mode, enabling Gemma models to generate reasoning traces prior to responding. We improve inference speed, memory, and compute efficiency, as well as long-context abilities through critical design choices. Gemma 4 establishes a leap in performance across STEM, multimodal, and long-context benchmarks, and rivals larger, frontier open models in human-rated tasks.
Gemma 3n: How to Run & Fine-tune | Unsloth Documentation
Run Google's new Gemma 3n locally with Dynamic GGUFs on llama.cpp, Ollama, Open WebUI and fine-tune with Unsloth!
Matt Mireles on Twitter / X
Introducing...Gemma 4 Multimodal Fine-Tuner for Apple Silicon- LoRA fine-tunning toolkit for Gemma LLM- runs locally on macOS via PyTorch and Metal- streams data from Google Cloud to your machine- fine-tune on audio, image and text- easy-to-use CLI wizardIf you want… pic.twitter.com/UduROxoxPU— Matt Mireles (@mattmireles) April 7, 2026
Google for Developers Blog - News about Web, Mobile, AI and Cloud
LiteRT is the universal framework for on-device AI. The production stack delivers 1.4x faster cross-platform GPU performance, streamlined NPU acceleration, and superior GenAI support for open models like Gemma.
A Visual Guide to Gemma 4 12B
An in-depth explainer to Gemma 4 12B; a unified, encoder-free multimodal model!
Simon Willison on Twitter / X
I'm really impressed by the new Gemma 3nI tried a 7.5GB model from Ollama and a 15GB model through mlx-vlm - they seem very capable, and this is the first model of that size I've tried that can handle both image AND audio input in addition to text! https://t.co/hiR3qGW387— Simon Willison (@simonw) June 26, 2025
Locally AI - Run AI models locally on your iPhone, iPad, and Mac.
Run Llama, Gemma, Qwen, DeepSeek, and more on your iPhone, iPad, and Mac. Optimized for Apple Silicon. Offline. Private.
