AI Stock Face-Off: Is Nvidia or AMD the Smarter Long-Term Buy? - Yahoo Finance

In the AI boom, NVIDIA and AMD have emerged as two leading semiconductor players, both achieving remarkable growth. NVIDIA has dominated the initial phase of AI, leveraging its CUDA software platform ... Read original →

NVIDIA’s CUDA moat has effectively locked down AI training, with Mellanox integration boosting interconnect dominance and the Groq acquisition targeting ultra-low-latency inference. Yet as global AI shifts from massive model training to distributed inference—where memory bandwidth trumps raw FLOPS—AMD’s MI300 architecture gains traction among hyperscalers. Technically, broader ROCm support for PyTorch/TensorFlow could erode CUDA lock-in. Geopolitically, tightening U.S. export controls compel both firms to diversify assembly/test capacity across Singapore, Malaysia, and Taiwan, China, inflating costs. Over the next 12–24 months, inference workloads may exceed 70% of data center AI ops, favoring AMD’s power-efficient, memory-optimized designs. However, NVIDIA’s full-stack advantage—NVLink + BlueField DPUs—remains formidable. The long-term winner won’t be decided by GPU specs alone, but by ecosystem stickiness and supply chain resilience under regulatory fragmentation.