Industry context: Demonstrations of end-to-end training on home-grown hardware affect how practitioners assess supply-chain risk, performance trade-offs, and reproducibility. Reuters reports Meituan released and open-sourced a new large language model, LongCat-2.0, which multiple outlets report carries 1.6 trillion parameters and a 1 million-token context window. The Next Web quotes Meituan describing LongCat-2.0 as "the industry's first trillion-parameter model to complete end-to-end training and inference on a 50,000-chip domestic compute cluster." Reuters and SCMP report the model was trained from scratch on a 50,000-chip cluster powered by Chinese-made processors and that Meituan published the weights. CNA and SCMP note Meituan did not disclose which domestic chipmaker supplied the hardware.
China’s Meituan says its new AI model was trained on domestic chips