LongCat-2.0, a large-scale MoE model with 1.6T total and 48B Active
Summary
LongCat-2.0 is a large-scale Mixture-of-Experts (MoE) model with 1.6 trillion total parameters and 48 billion active parameters.
Similar Articles
meituan-longcat/LongCat-2.0
LongCat-2.0 is a large-scale MoE language model with 1.6 trillion total parameters and ~48B activated per token, trained on AI ASIC superpods with 1M-context data. It achieves strong performance on coding and agentic tasks.
LongCat-2.0
LongCat-2.0 is a 1.6 trillion parameter mixture-of-experts model trained entirely on custom AI ASICs.
@Meituan_LongCat: Introducing LongCat-2.0 1.6T parameters · MoE with ~48B active · 1M context The full model behind Owl Alpha on @OpenRou…
Meituan introduces LongCat-2.0, a 1.6T parameter MoE model with ~48B active parameters and 1M context, featuring novel architectures like LongCat Sparse Attention and Zero-Compute Experts, achieving strong benchmark scores on coding and reasoning tasks.
Meituan launches LongCat-2.0 1.6T parameter model on APIs (2 minute read)
Meituan launched LongCat-2.0, a 1.6 trillion-parameter Mixture-of-Experts model with a 1 million-token context window, available via API for agentic coding, tool use, and complex workflows.
@sheriyuo: The industry's first trillion-parameter model to complete end-to-end training and inference on a 50,000-GPU Chinese com…
Meituan released LongCat-2.0, a 1.6T-parameter MoE model with 1M context, claimed as the first to train on a 50,000-GPU Chinese cluster, now available on OpenRouter for agentic coding.