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K-EXAONE 2.0 Technical Report: A 750B-Parameter Open-Weight Multilingual MoE Model

First seen · 8/5/2026, 04:00 AMLatest activity · 8/5/2026, 04:00 AM

LG AI Research presents K-EXAONE 2.0, an open-weight multilingual foundation model built by upcycling K-EXAONE rather than training from scratch. The model uses a Mixture-of-Experts architecture with 750B total parameters and approximately 37B activated per token, supports contexts up to 256K tokens, and expands language coverage from six to ten languages. Its training pipeline combines continual pre-training, difficulty-focused mid-training, and post-training for reasoning, agentic coding, multilingual performance, and safety in Korean sociocultural contexts. It is released under Apache 2.0.

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  1. AggregatorHuggingFace Daily Papers8/5, 04:00 AMnot independentRepresentative
    K-EXAONE 2.0 Technical Report: A 750B-Parameter Open-Weight Multilingual MoE Model