alt Hacker News> NVIDIA's control over the GPU compute ecosystem — particularly in AI, HPC
The two largest supercomputers in the world are powered by AMD. I don't think it's accurate to say Nvidia has monopoly on HPC
> NVIDIA's control over the GPU compute ecosystem — particularly in AI, HPC
The two largest supercomputers in the world are powered by AMD. I don't think it's accurate to say Nvidia has monopoly on HPC
It’s misleading to cite two government-funded supercomputers as evidence that NVIDIA lacks monopoly power in HPC and AI:
- Government-funded outliers don’t disprove monopoly behavior. The two AMD-powered systems on the TOP500 list—both U.S. government funded—are exceptions driven by procurement constraints, not market dynamics. NVIDIA’s pricing is often prohibitive, and its dominance gives it the power to walk away from bids that don’t meet its margins. That’s not competition—it’s monopoly leverage.
- Market power isn't disproven by isolated wins. Monopoly status isn’t defined by having every win, but by the lack of viable alternatives in most of the market. In commercial AI, research, and enterprise HPC workloads, NVIDIA owns an overwhelming share—often >90%. That kind of dominance is monopoly-level control.
- AMD’s affordability is a symptom, not a sign of strength. AMD's lower pricing reflects its underdog status in a market it struggles to compete in—largely because NVIDIA has cornered not just the hardware but the entire CUDA software stack, developer ecosystem, and AI model compatibility. You don't need 100% market share to be a monopoly—you need control. NVIDIA has it.
In short: pointing to a couple of symbolic exceptions doesn’t change the fact that NVIDIA’s grip on the GPU compute stack—from software to hardware to developer mindshare—is monopolistic in practice.