People view the Atlas 950 SuperPoD of Huawei displayed during the 2026 World AI Conference and High-Level Meeting on Global AI Governance in Shanghai, east China, July 19, 2026. (Xinhua/Chen Haoming)

Huawei on Thursday unveiled its Ascend 960 SuperPoD, which is the world’s first AI supernode to adopt near-packaged optics (NPO) technology, as larger and more complex AI models drive demand for greater computing scale and lower latency.

The system can support large-scale training and inference for AI models with up to 10 trillion parameters, a Huawei official said at Huawei Connect 2026.

A SuperPoD, or supernode, connects multiple physical computing nodes through high-bandwidth, low-latency interconnects, allowing them to operate as a single logical computer.
The company also brought forward the rollout of its next-generation Ascend 960 AI chips with the computing performance roughly doubling the previous generation, after development progressed faster than expected, according to media reports.

The Ascend 960DT is expected to be ready in the first quarter of 2027, three quarters earlier than originally planned, while the Ascend 960PR is scheduled for the third quarter of 2027, one quarter ahead of previous schedule.

As AI models grow larger, efficiently linking large numbers of processors is becoming increasingly important  ̶ a key challenge SuperPoDs are designed to address, analysts said.

The rollout comes as China continues to scale up its AI computing infrastructure, with the expansion of large intelligent-computing clusters increasing the importance of efficiently connecting and coordinating large numbers of processors.

China’s intelligent computing capacity reached 2,185 EFLOPS by the end of June, up 177 percent year-on-year, according to the Ministry of Industry and Information Technology. 

An information and communications industry development plan released by the ministry earlier this month calls for the orderly deployment of intelligent computing clusters with 10,000, 100,000 or more accelerator cards, while stepping up adaptation to domestically developed computing chips.

At the corporate level, competition in the AI chip industry is placing greater emphasis on system-level computing. JD Cloud and Chinese GPU maker Moore Threads recently announced plans to build a 100,000-GPU computing cluster, underscoring a broader push to deploy domestically developed AI chips at much greater scale.

Global Times