Inference on a single T4, end to end, in the browser. 800 million or 4 billion parameters. A 73,728-token context. Images. Running on your own hardware. That combination is the point: a decision model small enough to sit inside your own process, that can read a whole contract in one pass and look at a picture, and that still beats a hosted reference model on the tasks below. A new architecture with its own training and calibration method. The language model inside it is frozen and never trained; everything learned lives in a small physics engine on top of it. Both are in this repository and take the same code path. The 0.8B sits at the root because that is where it has always been; the 4B…