Documentation & Quick Start

Get started with LongCat AI models

Quick Start

LongCat-Flash uses a chat template defined in tokenizer_config.json. Examples:

First Turn

[Round 0] USER:{query} ASSISTANT:

With System Prompt

SYSTEM:{system_prompt} [Round 0] USER:{query} ASSISTANT:

Multi-Turn

SYSTEM:{system_prompt} [Round 0] USER:{q} ASSISTANT:{r} ... [Round N-1] USER:{q} ASSISTANT:{r} [Round N] USER:{q} ASSISTANT:

Tool Call Envelope

{tool_description}

## Messages
SYSTEM:{system_prompt} [Round 0] USER:{query} ASSISTANT:

<longcat_tool_call>{"name": <function-name>, "arguments": <args-dict>}</longcat_tool_call>

Deployment

Flash-Chat & Flash-Thinking

SGLang and vLLM adaptations enable high-throughput inference for LongCat-Flash models. Deployment guides cover environment setup, tensor parallelism, and inference configurations. Supports both single-user and multi-user scenarios with cost-efficient inference around $0.7 per 1M output tokens on H800 GPUs.

Video Generation

LongCat-Video provides unified interfaces for text-to-video, image-to-video, and video continuation tasks. Optimized for generating long-form videos (up to 5 minutes) with high temporal consistency and physical motion plausibility.

Official Resources

License & Usage

All LongCat models are released under the MIT License, allowing model distillation, fine-tuning, and secondary development. Evaluate and validate the models before use in sensitive or high-risk scenarios, and ensure compliance with applicable laws and regulations for your use case.