📖 Read the full version with charts and embedded sources on ComputeLeap → Google just shipped a 12-billion-parameter model that processes text, images, audio, and video — without a single encoder. And it runs on a laptop with 16GB of VRAM. Within 24 hours of the Gemma 4 12B release , the Hacker News thread hit 1,018 points and 382 comments . Frontier ML researchers started publicly swapping their daily-driver local coding models. The signal is loud: something shifted. This isn't another "run Gemma locally" walkthrough — we already covered that when the 31B variant dropped. The 12B is a different story. It's the model that proves you can rip out 850 million parameters of encoders, replace them with a single matrix multiply, and still compete with GPT-4.1 on coding tasks — at a fraction of the memory cost. What "Encoder-Free" Actually Means Every multimodal model you've used in the past year has a dirty secret: separate encoder stacks bolted onto the language model.…