Google AI Edge expands support for on-device small language models (SLMs) with over a dozen models, including Gemma 3 and Gemma 3n. Gemma 3n is a multimodal SLM supporting text, image, video, and audio inputs. New libraries for Retrieval Augmented Generation (RAG) and Function Calling are introduced, enabling developers to build AI features fully on the edge. Customization through fine-tuning, conversion, and quantization is supported, with new int4 post-training quantization reducing model size. ML Drift is introduced as a high-performance, cross-platform, on-device GPU compute engine for AI/ML inference, abstracting hardware complexities across OpenGL ES, OpenCL, Metal, and WebGPU. It supports tensor virtualization, an extensible custom op framework, 5D tensor support, and stage-aware optimizations for LLMs, enabling peak performance for classical and generative models on edge devices and desktops.
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