Google may have just killed Gemini by giving it away for free. In this video, I tested what makes Gemma 4 such a big deal: it’s Google’s newest family of open source AI models (built on the same DeepMind research as Gemini) and it’s already climbing into the top 5 on Arena AI’s open source rankings. The real shift is accessibility—Gemma 4 is designed to run on your own hardware, from lightweight “Effective” models (2B and 4B) for phones and laptops, to heavier options for real work like the 26B Mixture of Experts (MOE) and the 31B dense model. I break down the “game-changer stat” that makes this practical: the small models can run on as little as 5GB of RAM (think ~50 Chrome tabs), and the 26B MOE fits into about 18GB—less than what Premiere Pro can chew through when you’re editing 4K. I also cover the licensing angle: Gemma 4 is truly open source under Apache 2.0, meaning you can build and sell products commercially with no usage caps or revenue thresholds. Finally, I show two ways to use it right now—quick testing in Google AI Studio, or running it locally with Ollama—plus what you can actually build with it: private chatbots, local coding assistants, phone/Raspberry Pi projects, and even image (and on larger models, video) parsing.