Large Language Models (LLM) & AI Market: China demonstrates domestic AI training at scale

Multiple Chinese organisations in mid‑2026 reported large-scale model training runs using domestically produced processors, challenging the view that high-performance training still required Nvidia hardware. Meituan said it pre-trained LongCat‑2.0 (a trillion-parameter model) on a 50,000‑chip domestic cluster. A Huawei‑included research consortium reported full-parameter post‑training of DeepSeek‑V4‑Pro (1.6T MoE) on over 1,000 Ascend 910C chips, and Huawei’s Pangu Ultra runs and variants were also trained on large Ascend NPU clusters. Baidu reported training ERNIE 5.1 on a Kunlunxin-powered cluster, with industry reports linking that effort to Kunlun P800 chips and a claimed 97% effective training rate. Financial Times coverage (citing Morgan Stanley data) says some Chinese chips already outperform Nvidia’s H20 on several metrics. Together these datapoints indicate Chinese domestic chips have entered the AI training stack, though questions remain about training efficiency compared with best‑in‑class Nvidia solutions.