{"slug": "google-deepmind-s-gemma-4-12b-squeezes-multimodal-ai-onto-a-laptop-with-just-16", "title": "Google Deepmind's Gemma 4 12B squeezes multimodal AI onto a laptop with just 16 GB of RAM", "summary": "Google Deepmind released Gemma 4 12B, an open AI model that natively processes text, images, and audio on laptops with just 16 GB of RAM. The model nearly matches the performance of its 26B counterpart on benchmarks while cutting processing time and memory use, and is the first mid-sized Gemma model with native audio processing. Available under an Apache 2.0 license, the model handles speech recognition, code generation, and video analysis locally.", "body_md": "# Google Deepmind's Gemma 4 12B squeezes multimodal AI onto a laptop with just 16 GB of RAM\n\n**Google Deepmind has released Gemma 4 12B, an open AI model that brings multimodal capabilities to everyday laptops.** It processes text, images, and audio natively without separate encoders, cutting processing time, memory use, and latency, according to Google. The model runs locally with just 16 GB of RAM and nearly matches the 26B model—twice its size—across benchmarks, Google says. It's also the first mid-sized Gemma model with native audio processing.\n\nGemma 4 12B handles speech recognition, code generation, and video analysis. Per the [Developer Guide](https://developers.googleblog.com/gemma-4-12b-the-developer-guide/), it can parse multi-minute video clips by analyzing frames and audio together. In one demo, it chewed through a five-minute Google I/O keynote clip: 313 frames at one per second, plus audio.\n\nThe model is available on [Hugging Face](https://huggingface.co/google/gemma-4-12B), [Ollama](https://ollama.com/library/gemma4:latest), [LM Studio](https://lmstudio.ai/models/google/gemma-4-12b), and other platforms, licensed under [Apache 2.0](https://ai.google.dev/gemma/apache_2) for commercial use.\n\n```\nAI News Without the Hype – Curated by Humans\n\n\t\t\t\t\tSubscribe to THE DECODER for ad-free reading, a weekly AI newsletter, our exclusive \"AI Radar\" frontier report six times a year, full archive access, and access to our comment section.\t\t\t\t\n\n\t\t\t\t\tSubscribe now\n```\n\n[Google Blog](https://blog.google/innovation-and-ai/technology/developers-tools/introducing-gemma-4-12b/)", "url": "https://wpnews.pro/news/google-deepmind-s-gemma-4-12b-squeezes-multimodal-ai-onto-a-laptop-with-just-16", "canonical_source": "https://the-decoder.com/google-deepminds-gemma-4-12b-squeezes-multimodal-ai-onto-a-laptop-with-just-16-gb-of-ram/", "published_at": "2026-06-03 19:54:13+00:00", "updated_at": "2026-06-03 20:08:45.585253+00:00", "lang": "en", "topics": ["artificial-intelligence", "machine-learning", "large-language-models", "generative-ai", "ai-products"], "entities": ["Google Deepmind", "Gemma 4 12B", "Hugging Face", "Ollama", "LM Studio", "Apache 2.0", "THE DECODER"], "alternates": {"html": "https://wpnews.pro/news/google-deepmind-s-gemma-4-12b-squeezes-multimodal-ai-onto-a-laptop-with-just-16", "markdown": "https://wpnews.pro/news/google-deepmind-s-gemma-4-12b-squeezes-multimodal-ai-onto-a-laptop-with-just-16.md", "text": "https://wpnews.pro/news/google-deepmind-s-gemma-4-12b-squeezes-multimodal-ai-onto-a-laptop-with-just-16.txt", "jsonld": "https://wpnews.pro/news/google-deepmind-s-gemma-4-12b-squeezes-multimodal-ai-onto-a-laptop-with-just-16.jsonld"}}