In this demonstration, we showcase the live capabilities of North Small Translate, our new 218B parameter machine translation model that outperforms leading commercial systems under 1T parameters with a focus on high-throughput performance across 50 languages. We will demonstrate its ability to handle complex translation tasks, such as translating long-context documents (up to two book chapters), adhering to specific terminology, and seamlessly translating structured formats like JSON and XML. Alongside showcasing these state-of-the-art capabilities, we will discuss practical lessons on how we build this model. Specifically, we will highlight our focus on Difficulty Sampling for post-training and explain our Agentic Translation pipeline that can boost the performance of a model without a need for expensive reasoning.