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Meituan Trained a 1.6T-Parameter AI Model Without Nvidia GPUs

Meituan released LongCat-2.0, a 1.6-trillion-parameter Mixture-of-Experts model trained and deployed entirely on domestic AI ASIC superpods without Nvidia GPUs. The model quietly appeared on OpenRouter as Owl Alpha, achieving high usage rankings. While not the absolute best in performance, it demonstrates the viability of training trillion-parameter models on China's domestic compute infrastructure, reducing reliance on Nvidia.

SourceHacker News AIAuthor: mgh2
Meituan Trained a 1.6T-Parameter AI Model Without Nvidia GPUs
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Key points

  • LongCat-2.0 has 1.6T total parameters with ~48B activated per token using MoE architecture.
  • Training and inference ran on a domestic AI ASIC superpod, reportedly ~50,000 Huawei Ascend 910C chips.
  • The model was tested anonymously on OpenRouter as Owl Alpha, ranking third by monthly token usage and second in Claude Code Agent usage.
  • While not outperforming top frontier models, it proves the feasibility of full-stack domestic training for large-scale AI.

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