K-EXAONE 2.0 Technical Report: A 750B-Parameter Open-Weight Multilingual MoE Model
Original title:K-EXAONE 2.0 Technical Report
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.
Why it's worth reading
The combination of a 750B MoE, 256K context, and Apache 2.0 release gives developers an immediately relevant reference for long-context, coding-agent, and multilingual deployment decisions.