OpenAI, Anthropic accused of borrowing DeepSeek tech without credit
An English op-ed and an X user's screenshot allege that OpenAI's and Anthropic's recent cache price cuts came from adopting DeepSeek's cache optimization without acknowledgment. The Chinese outlet Huxiu's Kanjian Lab checked the figures and found the price cuts themselves are documented — Claude Opus 5.5's cache-read price fell from $0.50 to $0.20 per million tokens versus Opus 5, and GPT-6.1 Sol's cache input is $0.10 per million tokens — but pricing tables do not establish technical provenance, and the original author provided no code or company statement, with the percentage drop also shifting depending on the baseline used. DeepSeek's V4.1 Flash technical report says its global KV cache footprint is reduced roughly 437x versus early V1 at the same context length, about a quarter of the previous V4 Flash. The piece also notes that NVIDIA's Nemotron Nano 2 report explicitly credits DeepSeek's FP8 training recipe, while Anthropic in February accused DeepSeek, Moonshot and MiniMax of improperly obtaining Claude capabilities and acknowledged distillation is common industry practice.
It shows that cost and performance shifts are checkable, but claims about which techniques a closed model uses require evidence — open-source attribution norms are the crux of such disputes.