Gemma 4 12B is a new 12-billion-parameter multimodal model designed for local inference on consumer laptops. Google claims it matches the performance of their 26-billion-parameter mixture-of-experts model while running on devices with 16GB RAM.
First mid-sized Gemma model with native audio support, eliminates multimodal encoders for direct vision and audio processing through LLM backbone. Requires only 16GB RAM for local inference.
Google DeepMind has released Gemma 4 12B, a 12-billion parameter multimodal model that runs locally on laptops with 16GB of RAM. The model eliminates separate vision and audio encoders, processing raw inputs directly through its language model backbone under an Apache 2.0 license.
Google launched AI Edge Gallery for macOS, allowing Mac users to run Google's Gemma models locally. The platform ships with five Gemma models, including the newly released Gemma 4 12B—a 12-billion-parameter multimodal model that handles text, vision, and audio while running on consumer laptops with 16GB of RAM.