The competition in the artificial intelligence industry is reaching a new turning point. Recently, it was revealed that Meta has imposed an internal ban, explicitly requiring engineers in the Applied AI department to stop using Anthropic's Claude Code and OpenAI's Codex. This move is not simply an IT management optimization, but rather the beginning of a battle among large AI model companies over "model distillation."

Put simply, "distillation" refers to using the outputs of a powerful model to train another model. Meta's decision to restrict employees from using competing tools stems from core concerns about "data contamination" and "technology leakage." When engineers are writing training scripts or debugging code, if they rely too much on Claude or Codex, the code snippets and architecture solutions generated by these tools may be unintentionally included in Meta's own training data library. According to service terms from OpenAI, Anthropic, and Google, using model outputs to build competitive systems is strictly prohibited. Meta's move aims to avoid potential legal risks and huge compensation costs.

This "distillation war" has shown signs of full-scale escalation since 2026. Since February of this year, industry accusations have been frequent: from OpenAI accusing DeepSeek of violating distillation rules during training, to Anthropic exposing Alibaba affiliates conducting large-scale interactive distillation, and even Elon Musk admitting in court that xAI did indeed leverage OpenAI's model capabilities. Distillation has evolved from an academic gray area into a key weapon for large model companies to gain competitive advantages.

Previously, Meta has always positioned itself as a "pioneer of open source," building an open ecosystem through its Llama series models. However, this strict internal control reflects Meta's deep anxiety between "offense" and "defense": externally, open source is a weapon to weaken closed ecosystems and capture industry standards; internally, it must build an absolute "data moat" to prevent core intellectual property from being "siphoned off" by competitors through distillation techniques.

Industry analysts believe that Meta's precedent is likely to prompt other major players to follow suit. As the White House and regulatory agencies elevate the issue of "anti-distillation" to the level of national security, the competition rules in the large model market are being reshaped. In the future, AI technologies that offer "air gap" local deployment or private cloud solutions may see new growth opportunities. For startups that have long relied on leveraging competitors' capabilities, how to find a survival space amid regulatory compliance and self-innovation will become a critical challenge determining their fate.