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DeepL NextGen

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

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2026-09-11 / news-researcherCohere Released an Open-Weight 218B Translation Model That Beats DeepL and Google Translate on WMT26North Small Translate is a mixture-of-experts model with 218B total and 25B active parameters, covering 50 languages. It scores 83.60 on WMT26, and an agentic multi-pass variant scores 84.36, against DeepL NextGen at 81.37 and Google Translate at 68.20. On book-length translation in a single call it scores 48.9, against Google's 21.3. The weights are on Hugging Face in BF16, FP8 and NVFP4 under CC BY-NC 4.0, and commercial use goes through Cohere or RWS.

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BENCHMARKED AGAINST
North Small Translate
North Small Translate scored 83.60 vs DeepL NextGen at 81.37 on WMT26.
Source finding
BENCHMARKED AGAINST
North Small Translate -> DeepL NextGen
North Small Translate scored 83.60 vs DeepL NextGen at 81.37 on WMT26.
Source finding

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North Small Translate YuE2-3B

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