unveiled<\/a> on Tuesday, will be equipped with 10,000 of Alibaba\u2019s Zhenwu semiconductors, designed for both AI training and inference. The system is capable of supporting models with hundreds of billions of parameters, placing it among the most advanced computing setups currently in operation.<\/p>\nDeployed at a data centre in Shaoguan, Guangdong province, the cluster is described as a \u201cfully domestic\u201d project and represents the first Zhenwu-powered system of this scale in the Greater Bay Area. Alibaba said the chips can operate as a unified system, enabling the cluster to function like a single supercomputer with ultra-low latency of around four microseconds.<\/p>\n
The rollout highlights how China\u2019s leading technology firms are accelerating development of proprietary AI chips and infrastructure as the country pushes for self-reliance in critical technologies.<\/p>\n
<\/p>\n
Push for domestic alternatives accelerates<\/h1>\n
In recent years, Washington has tightened restrictions on China\u2019s access to advanced semiconductor technologies, including AI chips produced by Nvidia. The curbs have prompted Chinese firms to speed up the development of local alternatives across both hardware and infrastructure.<\/p>\n
Alibaba Group Holding has been advancing its chip ambitions through its T-Head semiconductor unit, while continuing to expand its position in cloud computing. The company now operates across the full AI stack, from chip design to data centre construction and model development, with services delivered through its cloud division.<\/p>\n
Cloud computing has remained one of Alibaba\u2019s fastest-growing segments in recent quarters, supported by rising demand for AI workloads. Across China, investment in large-scale data centres using domestic technologies has picked up pace.<\/p>\n
A similar project went online last month in Shenzhen, where a 10,000-card cluster built on Huawei\u2019s Ascend 910C chips began operations, signalling a coordinated effort among Chinese firms to scale local computing power.<\/p>\n
Unlike their U.S. counterparts, companies such as Meta and Microsoft, which are expected to collectively spend hundreds of billions of dollars on AI infrastructure this year, Chinese players have taken a more targeted approach. Investment has focused on sectors expected to generate measurable returns, including industrial applications and enterprise services.<\/p>\n
Scaling AI infrastructure for real-world deployment<\/h2>\n
The Zhenwu-powered cluster adds to growing evidence that China is shifting from experimentation to large-scale deployment of AI systems. Demand for computing power continues to rise as industries integrate AI into production and services.<\/p>\n
According to Charlie Zheng, chief economist at Samoyed Cloud Technology Group Holdings, the rollout of domestic clusters signals a transition from \u201chardware replacement\u201d to \u201csoftware collaboration\u201d across China\u2019s AI sector.<\/p>\n
He noted that adoption has been fastest in government services and urban governance, where requirements around data sovereignty and system security remain particularly strict.<\/p>\n
\u201cThe sector\u2019s rigid demand for data sovereignty and security has driven the fastest deployment,\u201d Zheng said.<\/p>\n
Alibaba stated that the cluster delivers around 30% higher efficiency in training and inference tasks, while single-card throughput has increased nearly tenfold. The system has already been deployed in areas such as healthcare and advanced manufacturing.<\/p>\n
Access to the cluster is being extended to small and medium-sized enterprises through China Telecom\u2019s platform, with usage priced on a per-card or hourly basis.<\/p>\n
Looking ahead, Alibaba plans to expand the system to 100,000 chips, a move expected to reduce costs further and improve overall resource utilisation as demand for large-scale AI computing continues to build.<\/p>\n
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