Google's Antigravity Python SDK added local model inference on September 23, with Google's own benchmark showing 97.2% of roughly 3,400 tokens ran on the developer's machine and only 95 touched the cl…
Google announced that its Antigravity SDK now supports local AI model workflows, with initial support for Gemma 4 26B A4B running through Google AI Edge's LiteRT runtime. The company recommends a mach…
Google AI Edge's LiteRT and LiteRT-LM enable deployment of Gemma 4 E2B on Raspberry Pi 5, achieving 99 tokens/sec prefill and 9 tokens/sec decode with a peak memory footprint of 1432 MB, powering the …
Google DeepMind released Gemma 4 12B, an encoder-free multimodal model that processes visual and audio inputs directly through a single decoder-only transformer, enabling local agentic workflows on st…
Google released Gemma 4 12B, a multimodal AI model with an encoder-free architecture that processes images and audio directly without separate encoders, enabling on-device agentic workflows on standar…
Google released Gemma 4 12B, a 12-billion-parameter model from Google DeepMind, along with tools enabling developers to run agentic AI workflows locally on laptops and everyday machines. The release i…
Google DeepMind released Gemma 4 12B, an open multimodal model designed for local, agentic workflows on everyday laptops. The model, now available through Google AI Edge tools including the macOS Gall…
Arm's Scalable Matrix Extension 2 (SME2) integrates a matrix-compute unit into the CPU, enabling up to 5x faster inference for generative AI workloads on mobile devices. It highlights how Google AI Ed…
LiteRT-LM, part of Google AI Edge, is an optimized runtime engine for deploying Gemma 4 models on-device across platforms like Chrome, ChromeOS, and Pixel Watch. It achieves high performance through a…