The GPU Wars: How NVIDIA Built a Monopoly and Why Everyone Is Trying to Break It

01 The CUDA Moat

NVIDIA's dominance isn't about hardware — it's about software. CUDA, NVIDIA's parallel computing platform, has been under development since 2007. Every AI framework (PyTorch, TensorFlow, JAX) is optimized for CUDA. Every AI researcher learned on CUDA. Switching to a different chip means rewriting code, retraining engineers, and accepting lower performance during the transition. This software moat is worth more than any hardware advantage.

02 The Challengers

AMD has good hardware (MI300X) but weak software (ROCm). Google's TPUs are excellent but only available on Google Cloud. Intel's Gaudi is a distant fourth. The most serious challenge comes from custom silicon — Amazon's Trainium, Microsoft's Maia, Meta's MTIA. These chips are designed for specific workloads and eliminate NVIDIA's margin. But they only serve their owners, not the broader market.

03 Can the Monopoly Be Broken?

NVIDIA's 92% share is the highest in any tech market since Microsoft's Windows dominance in the 1990s. But monopolies in tech don't last. Microsoft was broken not by a competitor but by a paradigm shift (mobile). The question for NVIDIA is whether the next paradigm (inference at the edge, custom silicon, or a new computing architecture) makes GPUs obsolete the way mobile made desktops less relevant. Until then, NVIDIA is taxing the entire AI industry.