Bytedance's Zhang Yiming Prioritizes Long-Term Goals Over Short-Term Model Distillation Gains

ChainCatcher report: Last month, Zhang Yiming, founder of ByteDance, explicitly stated at a full-team meeting of the Seed team that the company would not use model distillation as a shortcut to catch up with large models, even if it means temporarily falling behind domestic competitors. He urged the team to be willing to sacrifice short-term gains for long-term objectives. Distillation refers to training a smaller model to replicate the outputs of a more powerful model, thereby saving training time and computational resources. Internally, ByteDance believes this decision will make it more difficult for Seed’s language model to catch up in the short term with domestic counterparts such as DeepSeek, Kimi, and Qwen. However, ByteDance is more concerned about political risks: the company has long been under scrutiny from the U.S. government over TikTok, and if accused of extensively extracting capabilities from leading U.S. models, Washington might renew pressure on TikTok. Previously, Anthropic accused DeepSeek, Moonshot AI, MiniMax, Zhipu, and Alibaba of extensively extracting capabilities from Claude—but did not name ByteDance.