Chinese AI companies DeepSeek and Moonshot AI relied heavily on OpenAI’s GPT-6 Astra to train their latest models, The Information reported on Wednesday , citing people with direct knowledge of the matter.
The models in question are Moonshot’s Kimi K3.1 Pro , released last week, and an updated version of DeepSeek’s V4.1-Flash, which launched on 17 October. TNW has not independently verified the report.
The process, known as distillation, allows AI developers to learn from a more capable model without having to build all its capabilities from scratch. They send it large numbers of prompts, collect its answers, and use those responses to train their own systems.
Done at scale, it can help a smaller model reproduce some of a more advanced system’s abilities at a fraction of the cost.
OpenAI has already accused Moonshot of using similar methods. On 30 September, the company said people linked to the Kimi developer had run a coordinated campaign in July to extract the hidden reasoning behind its models’ answers.
OpenAI said it detected related activity involving more than 15,000 users. It shut down the campaign by 28 July, banned the accounts involved and shared its findings with other AI labs.
The latest report adds to tensions over how Chinese AI companies develop models that can compete with those built by US labs.
OpenAI, Anthropic and Google have argued that distillation can allow rivals to replicate advanced capabilities without making comparable investments in training. US agencies have also identified Chinese firms they say targeted American AI models.
The labs are trying to make that harder. Earlier this month, Anthropic said new safeguards had reduced the amount of data collected from its Claude models in distillation attacks by around 90% to 99%.
Both Chinese models have posted strong results in their developers’ own evaluations. Moonshot said Kimi K3.1 Pro outperformed GPT-6 Astra on a coding benchmark. DeepSeek introduced V4.1-Flash in September as a lower-cost alternative to US models. Neither company’s results have been independently verified.
The reported use of Astra highlights a difficult problem for leading AI labs: the same models they offer to users can also serve as training material for competitors looking to catch up.
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