Hacking with multimodal Gemma 4 in AI Studio

We’re in an incredibly fun era for building. The friction between "I have a weird idea" and "I have a working prototype" is basically zero, especially with the release of Gemma 4, which is now available via the Gemini API and Google AI Studio. Whether you want to deeply inspect model reasoning or you're just trying to build a pipeline to auto-caption an archive of historical web comics and obscure wiki trivia, you can now hit open-weights models directly from your code without needing to provision a massive GPU rig first. Here’s a look at the architecture, how to use it, and how to go from the UI to production code in one click. The Models: Apache 2.0, MoE, and 256k Context Before we look at the API, the biggest detail about Gemma 4 is the license: it's released under Apache 2.0. This means total developer flexibility and commercial permissiveness. You can prototype with the Gemini API, and eventually run it anywhere from a local rig to your own cloud infrastructure. The benchmarks are