Google's new Gemma 4 12B model is designed to run on any laptop with 16GB of RAM

Ars Technica ·

Google's new Gemma 4 12B model is designed to run on any laptop with 16GB of RAM

Gemma 4 12B is almost as capable as the version with 26 billion parameters. Credit: Google Gemma 4 12B is almost as capable as the version with 26 billion parameters. …

Gemma 4 12B is almost as capable as the version with 26 billion parameters. Credit: Google Gemma 4 12B is almost as capable as the version with 26 billion parameters. Credit: Google Google says the new model is capable of complex multistep reasoning and agentic workflows that previously required the larger Gemma variants. Despite the smaller parameter count, Gemma 4 12B comes with the newly devised Multi-Token Prediction (MTP) drafters , which take advantage of unused processing cycles to calculate possible future tokens. The result is greater speed and efficiency. Google has released optional MTP versions of the other Gemma 4 models, but this is the first one to have MTP out of the box. Gemma 4 12B is also more efficient thanks to a new approach to multimodality. The Gemma 4 family is natively multimodal, accepting text, audio, or images as inputs. Most gen AI models—including the other Gemma 4 variants—use dedicated encoders to process non-text inputs and pass that data to the LLM. This works well enough, but it increases latency and memory usage. With the new mid-weight model, Google has implemented a streamlined embedding module for vision, featuring single-matrix multiplication and positional embedding, which allows the data to pass to the LLM with proper spatial awareness. This eliminates the need for a bulky middleman encoder. For audio, there’s no encoding at all. …

Original source: Ars Technica

Mentioned

LLM · Gemma