Meituan unveils LongCat-2.0, China's largest AI model trained on domestic hardware
Quick Look
- Chinese food delivery giant Meituan has open-sourced LongCat-2.0, an AI model with 1.6 trillion parameters.
- It claims to be the country’s largest AI model trained entirely on domestic hardware for both pre-training and inference, marking a significant step towards China's self-sufficiency in chip technology.
AI-generated summary
Why It Matters
China is actively working to reduce its dependence on foreign chips, particularly for the computationally intensive process of AI model training. Meituan's new model represents a significant step in this strategic direction.
As China attempts to move beyond using domestic chips solely for model inference, food delivery giant Meituan released what it claims is the country’s largest artificial intelligence model trained entirely on home-grown hardware.
The Beijing-based on-demand service giant on Tuesday open-sourced LongCat-2.0, a new large language model (LLM) boasting 1.6 trillion parameters and a context window of 1 million tokens. The scale puts it on par with DeepSeek’s latest flagship model, V4-pro, which launched in April.
Meituan claimed that LongCat-2.0 was the industry’s first trillion-parameter model to complete full-process training and inference on a 50,000-card domestic computing power cluster.
While DeepSeek-V4-pro relied on home-grown chips only for inference – the process where a pre-trained model runs to answer user queries – LongCat-2.0 used domestic hardware for both inference and pre-training, according to Meituan.
Pre-training is a far more computationally intensive process, during which an AI model digests massive data sets to learn basic patterns.
Meituan said LongCat-2.0 was built entirely on “large-scale clusters of tens of thousands of AI ASIC superpods”, showing its ability to “conduct frontier-scale training on alternative hardware platforms”. An ASIC, or application-specific integrated circuit, is a chip customised for specific workloads, as opposed to a general-purpose processor.
Open Questions
- How does LongCat-2.0 perform against international models?
- What are the specific domestic hardware components used?




