completed a massive 1-gigawatt data center in China that runs entirely on domestically produced AI chips. The facility, capable of drawing the power equivalent to roughly 750,000 homes, was built to train the company's GLM foundation models without relying on restricted western hardware. Not a single Nvidia chip. Worth taking a look at compute, cloud, and chip partners to see how it built a domestic AI infrastructure stack without relying on Nvidia. UCloud / 优刻得 provides large-scale cloud compute and helped build a 1,000-plus-card inference cluster with unified scheduling and integrated training and inference. Capital Online / 首都在线 supplies GPU clusters, IDC capacity, and regional compute delivery. It also connects to domestic accelerators through commercial deployments. Sugon / 中科曙光 provides the hardware foundation, including AI servers, storage, supercomputing systems, networking, and data-center infrastructure. Huawei Ascend / 华为昇腾 is clearest domestic training platform. used Ascend systems for the end-to-end training of GLM-Image. Enflame / 燧原科技 has the strongest documented domestic inference link, with its chips deployed for services through Capital Online. has also adapted GLM models to other Chinese chip platforms, including Cambricon, Moore Threads, MetaX, Kunlunxin, and Hygon. Note is not replacing Nvidia with a single Chinese vendor. It is assembling a multi-vendor stack across chips, servers, cloud operators, and data-center infrastructure.