The cluster uses Tencent's self-developed StarLake server and features Nvidia's latest generation H800 GPU, making it the first in the country to be equipped with this technology. The inter-server bandwidth is 3.2T, providing high performance, high bandwidth, and low latency for large model training, autonomous driving, and scientific computing.

Large model training has become a vital area of research in recent years, but it requires a significant amount of computational power. Companies need to connect multiple servers through a high-performance network to create a large-scale computational cluster. This demand for computational power results in an exponential increase in hardware investment, creating a cash flow burden for many companies.

One solution is to use cloud computing as it provides cost-effective, scalable and easily deployable computational resources. In addition, cloud-based resources can be pooled and used on demand, making it easier for businesses to access the necessary computational power required for their projects.

Tencent's new HCC cluster has been launched with Nvidia's H800 chips, which are based on the Hopper architecture and are designed to run deep recommendation systems.