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Cohere released North Small Translate, a sparse mixture-of-experts model with 25 billion active parameters designed for machine translation across 50 languages. The model scores 83.60 on WMT26 benchmarks and is available on Hugging Face under a non-commercial license.
- The model uses a sparse MoE architecture with 218B total parameters but only activates 25B per token, reducing computational overhead compared to dense models of similar capability
- It supports 50 languages including major ones like English, Spanish, Mandarin, and Hindi, plus less common ones like Filipino and Maltese
- Multiple quantization options (BF16, FP8, NVFP4) let you run it on different hardware—from 8 H100s down to 2 H100s depending on precision, with production deployment using greedy decoding
+ north small translate
+ cohere
+ machine translation
mixture of experts
multilingual
+ quantization