Huawei has been making massive strides in the AI segment, and now, the company has showcased its CloudMatrix rack-scale cluster for the first time, revealing a gigantic breakthrough.
Huawei’s AI Cluster Reportedly Features 2x Higher FP16 Performance Than GB200, But With a Hefty Price
When it comes to Chinese AI firms competing against NVIDIA’s options, Huawei is undoubtedly at the forefront with its respective hardware, not just in terms of performance but also availability. The company has been more popular for its AI accelerator, coming in the “Ascend” lineup; however, Huawei recently expanded to rack-scale solutions, and they made a massive impact. The Chinese firm managed to compete with NVIDIA’s top-end offering, and it reached to a point where even Jensen started to worry about Huawei’s advancements.
Although the CloudMatrix 384 has been discussed internally, Huawei has not publicly showcased it until today. At the WAIC conference held in the Shanghai World Expo Center (via MyDrivers), Huawei showcased the CloudMatrix cluster for the first time, naming it the Atlas 900 A3 Superpod. In terms of the specifications, the CloudMatrix 384 (CM384) AI cluster features 384 Ascend 910C chips connected in an “all-to-all topology” configuration.
Interestingly, Huawei has managed to cover the architectural flaws by housing five times as many Ascend chips as NVIDIA’s GB200. A CloudMatrix cluster is said to deliver 300 PetaFLOPS of BF16 computing, almost two times higher than GB200 NVL72. However, the only drawback here is the power CloudMatrix 384 is expected to consume, which is said to be 3.9x the power of a GB200 NVL72 and somewhat “awful” perf/watt figures across AI workloads.
The price of a single CloudMatrix 384 AI cluster is claimed to be $8 million, which is almost three times higher than NVIDIA’s GB200 NVL72 configuration, so the key motive behind Huawei’s product is not to provide a cost-effective performance, rather a product that is made through in-house resources and is capable enough to compete with Western alternatives. This particular solution is verified by NVIDIA CEO Jensen himself, who claims that Huawei has managed to compete with Grace Blackwell systems.