Huawei's AI Chip Revolution: Ascend 960, Kunpeng 950 & SuperPods Coming Soon
Huawei is set to revolutionize the AI chip market with a series of powerful releases. The Ascend 960, expected in late 2027, will double the computing power and memory capacity of its predecessor, the Ascend 950. This is just the beginning of Huawei's ambitious plans for the next few years.
Kicking off in early 2026, Huawei will introduce the Ascend 950PR, followed by the Ascend 950DT later in the year. These chips will offer improved vector processing and granular memory access, with an impressive 2 TB/s interconnect bandwidth. Huawei plans to expand its Ascend series with the 970, scheduled for release at the end of 2028. This chip will boast an astonishing 4 TB/s interconnect bandwidth and deliver 8 PFLOPs of FP4 performance.
In addition to the Ascend series, Huawei is also focusing on general computing. The company plans to release two Kunpeng 950 processors in 2026, each with an impressive core count: one with 96 cores and 192 threads, and another with 192 cores and 384 threads.
Huawei's SuperPods and SuperClusters are also set to make waves. The company will open-source its UnifiedBus 2.0 protocol, enabling better connectivity between these powerful systems. The first SuperCluster, the Atlas 950 SuperCluster, is expected to offer 2.5 times more NPUs than xAI's Colossus cluster. Additionally, the TaiShan 950, the world's first general-purpose computing SuperPod, will also be released in 2026.
Huawei's SuperPods of NPUs are set to outperform Nvidia's offerings. The Atlas 950 SuperPod, scheduled for release in late 2026, will surpass Nvidia's NVL144 and NVL576. The Ascend 950PR and 950TO will also support low-precision data formats like FP8, delivering up to 2 PFLOPs of performance.
Huawei's upcoming releases promise significant advancements in AI chip technology. With the Ascend 960, powerful processors like the Kunpeng 950, and innovative SuperPods and SuperClusters, Huawei is poised to reshape the AI landscape. These releases, scheduled over the next few years, indicate a clear commitment to driving progress in AI computing.
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