China's TPU path gains traction with low-cost AI inference challenging GPU economics

China's TPU momentum isn't just a hardware shift—it's a direct assault on GPU economics. As generative AI inference scales, purpose-built tensor accelerators with superior TOPS/Watt ratios are forcing a full-stack rethink, eroding CUDA’s software moat from compiler layers upward. U.S. export controls on high-end GPUs ironically accelerated domestic substitution, yet supply chain vulnerabilities in IP cores and EDA tools remain acute. NVIDIA may counter with Grace-Hopper integration or tactical price cuts, while AMD and Intel push open ecosystems like ROCm and oneAPI to court neutral developers. Within 18 months, low-power TPU modules will dominate edge deployments, and cloud providers’ in-house silicon could capture over 40% of inference workloads—permanently resetting the cost baseline for AI infrastructure.