🇨🇳China claims a new milestone in locally trained AI, as Meituan rolls out LongCat-2.0.

Meituan, China's food delivery giant, just released LongCat-2.0, an open-source 1.6T-parameter MoE (33B–56B parameters) coding model. 1M tokens context window.

Open-source: Available on longcat[.]ai and OpenRouter, top 3 globally by call volume.

LongCat-2.0 was trained from scratch on 50,000 Chinese domestic chips and Meituan said this proves large-scale model training can now be done on domestic compute clusters.

Shows again the rising push for self-reliance in China’s AI market, as DeepSeek, Alibaba, ByteDance, and others try to depend less on U.S. chips for model training after Washington’s export controls since 2022.

While DeepSeek-V4-pro relied on home-grown chips only for inference, LongCat-2.0 used domestic hardware for both inference and pre-training, according to Meituan.

Meituan did not directly identify its hardware supplier, but said in a WeChat post on Tuesday that it used Huawei Collective Communication Library (HCCL) to make training more stable. HCCL is a chip-to-chip communication system like Nvidia Collective Communication Library (NCCL).

This removed doubts that Atlas-950 SuperPoDs could not train large LLMs for Zhipu AI and DeepSeek.