LongCat

Meituan’s self-developed 560-billion-parameter MoE large-model dialogue platform that supports multimodal generation—including text, code, and images—providing developers and enterprises with fast and cost-efficient AI capabilities.

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LongCat large modelMeituan LongCat-Flash-ChatMoE architecture open-source modelAI code generation toolagent task model

Features of LongCat

560-billion-parameter MoE architecture with an average of 2.7 billion active parameters and inference speeds up to 100 tokens/s

Supports text generation, code completion, image creation, and multi-turn dialogue in a unified workflow

Offers a web interface, APIs, and open-source weights for local deployment and secondary development

Ranks first in evaluations such as VitaBench and τ²-Bench, delivering SOTA performance on complex agent tasks

Use Cases of LongCat

Developers can quickly generate code snippets, debug scripts, and receive optimization suggestions

Content teams can produce marketing copy, video scripts, and images at scale to shorten creative cycles

Enterprises can build intelligent customer service and knowledge Q&A systems to reduce human agent costs

Researchers can fine-tune the open-source weights to explore MoE training and inference optimization

FAQ about LongCat

QIs LongCat AI free?

Online usage on the official website is free; API usage is billed at around 5 RMB per million tokens, and open-source weights can be deployed locally at no cost.

QHow do I deploy LongCat-Flash-Chat locally?

Clone the GitHub repository, load the Hugging Face weights using SGLang, and it can run on a single H800 GPU.

QWhich languages does the model support?

Primarily Chinese and English, with support for multilingual code comments and documentation generation; additional languages are continuously being expanded.

QIs LongCat suitable for building multimodal agents?

Yes. It is optimized for tool usage and complex scenario decision-making, ranking first in the VitaBench evaluation.

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