Former OpenAI Researcher Claims to Find Blackwell Chip Signatures in Six Chinese AI Models
Former OpenAI researcher Will DePue published a forensic analysis claiming to find signatures of Nvidia Blackwell chips in the weights of six Chinese AI models from companies like DeepSeek, providing the first technical evidence that Chinese labs are bypassing US export controls to access the latest GPUs.
AI researcher Will DePue claims that a forensic analysis he conducted has turned up the first technical evidence that leading Chinese AI labs, including DeepSeek, Moonshot AI, MiniMax, and Ant Group, are using Nvidia's export-controlled Blackwell GPUs. DePue played a key role at OpenAI in building models like Sora, GPT-4o, and GPT-5 before founding the nonprofit research group Unemployment Labs. He states that senior researchers at OpenAI and Anthropic have already independently checked and confirmed his method.
According to DePue's analysis, six Chinese models released since April 2026 carry the distinct signature of Nvidia's Blackwell generation, while earlier models such as DeepSeek-V3 and Kimi K2.5 show traces of Nvidia's older Hopper generation. The evidence comes directly from the published language models. Before training starts, the software framework PyTorch fills empty slots in model weights with random numbers generated from a seed value. Because different chip models have different core counts, this filling process produces a characteristic pattern: older Hopper chips use 132 compute cores, while newer Blackwell chips use exactly 148 or 152 cores depending on the model. Although training adjusts these values millions of times, some slots for unused words or symbols keep their initial random values, leaving a faint statistical echo.
DePue's report estimates that the five training runs he examined required about 12,000 Blackwell GPUs combined, equivalent to the computing power of roughly 30,000 older H100 chips. At a unit price of about $70,000, each cluster would cost $200 million to $300 million, totaling more than half a billion dollars for all five systems. While the method strictly shows only which hardware initialized the weights and does not reveal where the GPUs are located or who owns them, it confirms that Chinese companies can access Nvidia's top hardware by renting computing capacity at data centers outside China. This does not necessarily prove physical smuggling or a violation of US export law, but highlights loopholes in current regulations regarding cloud-based compute leasing.