LongCat-2.0 boasts 1.6 trillion parameters and a million-token context window, on par with DeepSeek’s latest flagship model
As China attempts to move beyond using domestic chips solely for model inference, food delivery giant Meituan has released what it claims is the country’s first trillion-parameter 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.
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.
While Meituan did not explicitly name its hardware supplier, the company said in a WeChat post on Tuesday that it used the Huawei Collective Communication Library (HCCL) to improve training stability. HCCL is a chip-to-chip communication system similar to the Nvidia Collective Communication Library (NCCL).