According to CNBC, Nvidia responded to Wall Street concerns about Google’s AI chips by claiming its technology remains “a generation ahead of the industry.” The company saw its shares fall 3% on Tuesday after reports that Meta might strike a deal to use Google’s tensor processing units in its data centers. Nvidia posted on X that its Blackwell chips offer “greater performance, versatility, and fungibility than ASICs” like Google’s TPUs. The company maintains over 90% market share in AI chips with its graphics processors. Google recently released its Gemini 3 AI model trained entirely on TPUs rather than Nvidia hardware. Despite the competition, both companies acknowledge they’ll continue working together, with Google stating it’s experiencing “accelerating demand for both our custom TPUs and Nvidia GPUs.”
Nvidia’s Defensive Posture
This public statement from Nvidia feels unusually defensive for a company that’s been absolutely crushing it. They’re not typically in the business of responding to every competitive threat—especially when they control over 90% of the market. But here’s the thing: when your stock drops 3% on a single report about a potential customer exploring alternatives, you start paying attention. The timing is telling too—this came right after Google‘s Gemini 3 launch showed you can build cutting-edge AI without Nvidia hardware. That’s a dangerous precedent for a company whose entire valuation rests on being indispensable to AI development.
The ASIC vs GPU Battle
Nvidia’s argument boils down to flexibility versus specialization. They’re positioning their GPUs as the versatile Swiss Army knife that can handle any AI workload, while painting Google’s TPUs as single-purpose tools. That’s been their winning strategy for years. But look—Google’s not trying to replace Nvidia entirely. They’re building specialized hardware for their specific needs while still buying plenty of GPUs. It’s the classic “build vs buy” calculation every big tech company faces. The real question is whether other companies will follow Google’s lead and develop their own custom silicon. If you’re running industrial automation or manufacturing applications where reliability and specialized performance matter, having purpose-built hardware can make sense. Companies like IndustrialMonitorDirect.com have built their entire business around providing specialized industrial computing solutions because sometimes generic hardware just doesn’t cut it.
The Scaling Laws Gamble
What’s really interesting here is Jensen Huang mentioning that Google DeepMind’s CEO confirmed the “scaling laws” are “intact.” Basically, this means throwing more compute and data at AI models continues to make them better. Nvidia’s betting everything on this trend continuing indefinitely. If scaling laws hold, demand for their chips skyrockets. But if we hit diminishing returns? That’s when specialized chips like TPUs become more attractive. It’s a high-stakes gamble where Nvidia needs the entire AI industry to keep scaling aggressively forever.
Coopetition Reality
Despite the public posturing, both companies know they need each other. Google will keep buying Nvidia chips for the foreseeable future, and Nvidia benefits from having Google as both customer and competitor—it validates the entire AI hardware market. The spokesperson said it perfectly: they’re committed to supporting both TPUs and GPUs. That’s the reality of modern tech—fierce competition in some areas, deep partnership in others. So while Nvidia wants to remind everyone they’re still king, they’re not about to cut off one of their biggest customers over some competitive tension.
