Introducing North Small Translate: A leading sovereign open-weight machine translation model

This post introduces North Small Translate, a new mixture-of-experts machine translation model (218B total parameters, 25B active) with a 16k context length, supporting 50+ languages. It achieves an 83.6 WMT26 All Languages benchmark score, outperforming competitors like DeepL and Google Translate. The model demonstrates 1.4x higher output throughput than Gemma 4 31B and scores significantly higher on long-context evaluations. It is also cost-efficient, with a low per-task cost compared to other models. An agentic version, North Small Translate (Agentic), is also mentioned, scoring 84.36 on the WMT benchmark.