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Google Launches 'Gemma 4 12B' AI Model That Can Run On Your Laptop
3 juin 2026 à 20:00
Google has launched Gemma 4 12B, a 12-billion-parameter open AI model designed to run locally on your laptop without depending entirely on cloud infrastructure. WION reports: According to Google, the new model delivers performance close to much larger AI systems while requiring significantly less memory. The company says Gemma 4 12B can run locally on devices equipped with just 16GB of VRAM, making advanced AI more accessible to developers, researchers and businesses. The launch highlights a growing trend across the AI industry: bringing powerful AI models directly to personal computers instead of relying solely on remote data centers.
Gemma is Google's family of open AI models built using technology and research from its Gemini program. The new Gemma 4 12B model contains 12 billion parameters and has been designed to handle multiple types of information, including text, images and audio. Unlike traditional AI systems that focus only on text, Gemma 4 12B can understand visual content, process audio inputs and perform advanced reasoning tasks. This makes it suitable for a wider range of applications, from software development and content creation to research and automation. Google says the model is available under the Apache 2.0 licence, allowing developers and organizations to use, modify and deploy it with relatively few restrictions.
[...] One of the most significant technical changes in Gemma 4 12B is its new unified architecture. Traditionally, multimodal AI systems use separate components known as encoders to process images, audio and text before combining the information. Google says Gemma 4 12B removes the need for separate multimodal encoders. Instead, the model processes different types of information through a unified architecture. According to the company, this helps improve efficiency while reducing memory requirements and computational overhead. The result is a model that can deliver advanced multimodal capabilities while remaining small enough to run locally on modern hardware.
Read more of this story at Slashdot.
