Google DeepMind's Gemma 4 12B packs multimodal AI into laptops with 16GB RAM
New 12B model runs locally on 16GB RAM, matching performance of 26B version in tests.
Google DeepMind has introduced Gemma 4 12B, a new multimodal AI model designed to run locally on standard laptops. With just 16GB of RAM, the model handles video, audio, and text processing entirely offline—no internet connection required. Despite its compact 12 billion parameter size, it nearly matches the performance of the 26B version in benchmark tests, including code generation and speech recognition tasks.
In a demonstration, Gemma 4 12B simultaneously analyzed 313 frames from a five-minute video (at one frame per second) along with corresponding audio. Matthias Bastian of The Decoder noted this is the first mid-sized Gemma version with direct audio processing capabilities. The model is already available on Hugging Face, Ollama, and LM Studio under the permissive Apache 2.0 license, making it straightforward for developers and enterprises to integrate into commercial applications.
- Runs locally on laptops with only 16GB RAM, no internet needed
- Processes video, audio, and text simultaneously—demo analyzed 313 frames from a 5-minute video plus audio
- Available on Hugging Face, Ollama, and LM Studio under Apache 2.0 license
Why It Matters
Brings powerful multimodal AI to consumer hardware, enabling offline code generation and speech recognition for everyday laptops.