Nvidia reportedly tightens grip on AI inference market despite growing competition - digitimes

NVIDIA's dominance in AI is expanding beyond model training into the rapidly growing inference market, which handles deployed AI models and revenue generation. Despite increasing competition, NVIDIA m... Read original →

NVIDIA’s leverage of TSMC’s 3nm EUV process isn’t just a node shrink—it’s a strategic extension of its CUDA-dominated ecosystem from training into inference, where real revenue flows. This forces competitors to overhaul not only logic design but memory hierarchy and interconnects to match software-hardware co-optimization. Geopolitically, U.S. export controls inflate compliance overhead globally; non-U.S. clients adopt redundant sourcing, inadvertently reinforcing NVIDIA’s pricing power. In response, AMD and Google’s TPU teams will likely double down on chiplet architectures paired with open-source compilers to bypass CUDA lock-in. Over the next 18 months, the inference market will bifurcate: 3nm-class GPUs dominate premium segments, while 5nm custom ASICs erode volume tiers—making TSMC’s wafer allocation the silent arbiter of competitive outcomes.