A compact mixture-of-experts style model that activates only 3 billion parameters despite having 30 billion total, making it unusually efficient at inference time. It handles text-in, text-out tasks with a smaller computational footprint than its parameter count suggests. The trade-off is that selective activation can mean narrower coverage on any given pass compared to dense models of similar size.