Huawei has recently unveiled the tech-pack Atlas 350 AI accelerator card, powered by the all-new Ascend 950PR chipsets. The best part of this SoC is that it delivers nearly 2.87x performance improvements over US-made AI semiconductors – Nvidia H20.
On March 20, Huawei conducted the Ascend AI Partner Summit at the China Partner Conference 2026. During the event, the OEM showcased its Atlas 350 AI accelerator card, which will eventually accelerate AI and machine learning tasks.
The company mentioned that the Huawei Ascend 950PR chip powers the Atlas 350 card. This AI semiconductor belongs to the Ascend 950 family, indicating improved components, performance, and efficiency compared to the previous versions.
Ascend 950PR is a new-generation AI accelerator chip designed for prefill inference and recommendation workloads. Huawei announced the chip in September last year as a part of its three-year roadmap for the upcoming AI semiconductors.
Now, Huawei has unveiled the Ascend 950PR with the new Atlas solution. According to the details, the chipset provides 2.87x compute performance over Nvidia H20. It becomes the only product in China to support FP4 low-precision inference.
- Huawei reveals 3-year Ascend AI chip roadmap, 950 coming in 2026
- China warns tech companies to avoid Nvidia H20 in favor of Huawei AI chips
Furthermore, the HBM potential of the Atlas 350 is around 11GB – which is 1.16 times greater than that of the H20. Besides, the new-generation multimodal throughput has 60% improvement.
On the flip side, the company has reduced memory access granularity to 128 bytes from 512 bytes. That’s a 4-fold improvement in memory access efficiency for smaller operators.
Apart from the enhancements, this card delivers 1.56 PFLOPS at FP4 precision, a memory bandwidth of 1.4TB/s and a TDP of 600W, which is around 1.5 times more than that of the Nvidia H20.
The overall performance and efficiency of the Ascend 950PR are far better than Nvidia H20, and could open more gates for China to build up an independent AI ecosystem.
(Image Credits: Huawei)
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