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LongCat-2.0 is a large-scale Mixture-of-Experts model with 1.6 trillion total parameters and 48 billion active parameters. The model uses a MoE architecture to activate only a fraction of its parameters per inference step. This design aims to balance computational efficiency with high model capacity.
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