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China’s first supernode for 2t-parameter models enters service in Ulanqab_我的网站
一 | （新加坡讯）一名新加坡男子在面子书私讯台湾政治人物，要求采用他的水力发电厂设计，因未被回应而他们发出炸弹恐吓，评估报告指男子罹患妄想症，最终被判罚款6000新元。被告卢朋盛（53岁，译本）共面对4项抵触防止骚扰法令的控状，他早前承认其中3项，另一项交由法官周一（8月26日）下判时一并考虑。根据案情，被告在2018年7月至11月期间，开始透过面子书私讯一些政治人物。
The instance is designed to handle inference for mixture-of-experts models with up to 10 trillion parameters, the company said in a statement sent to the Global Times on Wednesday.
This marks the first supernode-form computing architecture in China to successfully run large language models exceeding 2 trillion parameters, according to the company.
Industry expert Tian Feng told the Global Times that the commercial rollout of supernode infrastructure could significantly reduce training cycles, lower costs, and speed up iteration for AI developers requiring massive computational resources.
The company said the new instance has already been used to power commercial services for large language models such as KimiK3 and Qwen3.8Max.
The Lingjun Zhenwu M890 supernode instance supports FP8/FP4 low-precision computing. Through the ICNSwitch 1.0 chip, its scale-up interconnect scale has been expanded from 16 cards to 64 cards, with inter-card interconnect bandwidth boosted to 800 GB/s. Enterprises can provision 64-card, high-speed-interconnect computing units through the cloud without building their own data centers, according to the company.
In training scenarios such as autonomous driving and embodied intelligence, the instance delivers three times the training performance compared with the previous-generation Zhenwu 810E, the company said.
Ulanqab, where the supernode instance debuted, is one of Alibaba Cloud's five super data centers. The facility sources approximately 90 percent of its electricity from green energy, providing a low-carbon operating environment for high-density computing power.
Leveraging its climate, energy and network advantages, Ulanqab has transformed from "China's potato hometown" into the "token factory" - a term increasingly used in the AI industry to describe infrastructure dedicated to producing the digital building blocks generated by large language models.
By the end of 2025, the city had attracted 84 data center projects, including 81 intelligent computing centers, with total investment exceeding 500 billion yuan ($74.1 billion) and operational computing power reaching approximately 172,000 petaflops, ranking it firmly in the nation's top tier, according to domestic media reports.
On August 6, China's largest AI computing industrial park was completed and put into operation in Ulanqab. The project highlights a broader race in China to build massive AI data centers capable of supporting the next generation of AI models while addressing soaring electricity demand, according to Chinese experts.
In recent years, Inner Mongolia has been rapidly positioning itself as a global-scale AI computing center cluster. Major technology companies, including Huawei, Tencent, ByteDance and Alibaba; telecom operators China Mobile, China Telecom and China Unicom; as well as cyberspace infrastructure service provider VNET, have established computing facilities in the region.
As the AI industry gradually transitions from the training era to the inference era and large model parameters continue to expand, supernodes have become a central battleground for AI infrastructure.
Chinese vendors are accelerating deployments in this space. Huawei has commercially deployed more than 750 sets of its Ascend 384 supernodes across industries including internet, telecom operators, finance, education, healthcare, transportation and manufacturing. It is also the only domestic supernode to have trained state-of-the-art (SOTA) models.
Baidu AI Cloud has also launched its Tianchi 256-card supernode based on Kunlun chips, with support for major models including Wenxin, DeepSeek, GLM, and MiniMax.
Meanwhile, supercomputer manufacturer Sugon has unveiled China's first fully domestic 100,000-card AI supercluster Sugon 8000 (Dengfeng), integrating supercomputing and AI computing on a unified architecture. It has now been connected to the national supercomputing internet to provide computing services to government, research, and enterprise clients nationwide.
Tian, former dean of SenseTime's Intelligence Industry Research Institute, told the Global Times that the flurry of domestic supernode launches reflects a broader inflection point as China's AI sector pivots from training capacity toward efficient, large-scale inference.
The expert further said that the commercial viability of these systems - evidenced by Huawei's extensive deployed base, Baidu's rapid model adaptation and Sugon's integration into the national computing network - suggests domestic vendors are moving beyond proof-of-concept to genuine production-grade infrastructure, a prerequisite for sustaining the next wave of trillion-parameter model proliferation, Tian noted.
The move also underscores China's push for self-reliance in AI infrastructure as US chip export restrictions continue to tighten, Tian said, noting that, in the supernode domain, Chinese companies are shifting from imported graphics processing units toward homegrown interconnect chips and domestic compute clusters, a transition that could reshape value allocation across the AI industry chain.
。被告要求对方停止建造更多燃煤电厂，改为采用他的水力发电厂设计。他称燃煤电厂会导致台湾人民罹患癌症，而水力发电厂可产生干净和再生能源，能解决上述问题。然而，他没有得到任何答案。2024年2月28日左右，被告因几年没有得到回应感到不满，决定发出恐吓讯息，“测试”对方是否收到讯息。若台湾有关当局在他发送讯息后找上他，这证明政治人物读了他的讯息，但刻意不理会他。2月28日至3月1日期间，他分别向台湾立法院长韩国瑜和台湾国民党立法委员罗智强发送两则炸弹恐吓讯息，声称要在他们的房子或车内放置炸弹，用来炸他们和家人。他也称自己还有很多炸弹，能够用来炸台湾立法院大楼。罗智强在2024年3月初在面子书发文称，收到来自新加坡的炸弹威胁，对方扬言要炸毁台湾的立法院、立法院长韩国瑜和家人，以及他。调查显示，被告并不打算把这些恐吓付诸行动，也没有能力这么做。一名网民看见罗智强对此事发出的贴文后，3月4日向新加坡警察部队报案。被告随后被捕，并在同月26日被控上法庭，过后还押新加坡心理卫生学院接受心理评估。评估报告显示，被告患有妄想症，与他所犯的罪行有关。被告求情时说，他发送炸弹恐吓只是想证明对方之前已读不回，他没有意图也没有能力实施这些恐吓，恳请法官轻判。
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