AI 精选动态
智能评分 80
美团发布开源编程模型LongCat-2.0，实现全栈国产化训练
AI 推荐理由
与DeepSeek仅用国产芯片推理不同，LongCat-2.0实现全栈国产训练，展示了国产芯片生态的实质性突破，值得持续跟踪。核心解读
美团发布LongCat-2.0，一个开源1.6T参数MoE（33B-56B参数）编程模型，支持1M token上下文窗口。该模型在50,000块国产芯片上从零训练，使用华为HCCL通信库，证明大规模模型训练可在国产计算集群完成，区别于DeepSeek仅用国产芯片推理。
全文
🇨🇳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.
Rohan Paul (@rohanpaul_ai): https://t.co/VBWCKd55Wb