LongCat
Open foundation models for long-context reasoning, agentic coding, and scalable AI systems.
LongCat is Meituan's large language model family for long-context reasoning, agentic coding, repository-level understanding, automated task execution, and scalable AI systems. Official materials list LongCat-2.0 as a 1.6T-parameter MoE language model and describe it as a step up from previous LongCat models.
Pricing
No public price table or numeric usage rate could be confirmed from accessible official LongCat/Meituan materials.
I could not verify any publicly posted token, subscription, or usage price for Meituan's LongCat from accessible first-party sources. Treat this as no public pricing disclosed in the materials I could confirm.
Model Intelligence
Recent stories
Meituan released LongCat-2.0 weights and inference code under MIT, with Hugging Face, GitHub, ModelScope, GPU, and NPU paths. Analysts noted the ~48B-active MoE keeps attention shape while reducing zero-communication experts from 256 to 128.
Meituan disclosed LongCat 2.0, a 1.6T-parameter MoE with about 48B active parameters, 1M context, and 35T training tokens on domestic hardware. The release ties a near-frontier open model to a Chinese domestic compute stack and a custom sparse-attention design.