Stephen Manning
Founder of Cash Flow University, Options Education, Public Setup/Risk/Exit Reviews
No serious AI customer runs on a single chip vendor, so the choice was never Google's TPUs or Nvidia, but both. Per @StockSavvyShay, Anthropic contracted 2.6 GW of Nvidia infrastructure through 2028 despite leaning heavily on Google TPUs and Amazon Trainium. Per @wallstengine, Nvidia says revenue per gigawatt rises from $25B for Blackwell to $40B for Rubin, but that only works if the gigawatts can be found. x.com x.comÂ
Nvidia has delivered its first Vera Rubin systems, which carry 25 times the AI compute of the H100. The first batch shipped to Anthropic, OpenAI, xAI and Oracle, and frontier models such as GPT-5 and Opus will be upgraded on them; a separate version is reportedly built for outer space. Anyone underweight Nvidia is making a directional bet, knowingly or not. x.comÂ
AI infrastructure bottlenecks could give eight stocks as much as 18x upside. Nvidia supplies frontier-model GPUs; Broadcom and Marvell supply custom silicon and networking; TSMC makes advanced chips; Micron supplies sold-out HBM; Vertiv provides power and cooling; Palantir monetizes enterprise AI; Alphabet spans TPUs, research, cloud and apps. The list tracks where AI infrastructure spending is flowing. x.com x.comÂ
AI software and hardware advances make GPUs and power more valuable, creating huge long-term tailwinds for compute providers and AI model and app businesses. Each new software generation increases a GPU's value; each hardware generation increases the value of a gigawatt of power. That favors Nvidia, Broadcom, Intel and AppLovin. x.comÂ
Low Anthropic spending relative to customer expenses points to an enterprise AI adoption gap that leaves Nvidia reliant on intermediaries able to build their own chips. Anthropic's S-1 says over half the Fortune 500 were $100k+ annual customers as of September, yet spending among its publicly traded customers averaged under 0.1% of expenses in Q3 2026. That measures one provider and cannot show whether AI deployments succeed; Nvidia needs more enterprises buying its compute directly. x.comÂ
Nvidia retains pricing power if its full system keeps reducing customers' cost per effective AI task. Strong AI demand alone does not ensure profits across the chain: rising chip, memory and optical costs burden buyers, while tighter financing and slow collections threaten operators. Large customers developing their own chips could pressure Nvidia's margins even as the market grows. x.comÂ
Nvidia gets paid for AI infrastructure while the companies funding AI buildouts bear the spending. Alongside Apple's edge hardware business, Nvidia's position as a supplier distinguishes it from the AI spenders that are losing to companies collecting the cash. x.comÂ
Nvidia's AI profits are real, but its compute demand depends heavily on fragile venture funding. Per Chamath, 1% of firms account for 90% of AI spending, and 72 cents of each dollar comes from unprofitable VC-backed firms. Venture money passes through startups to Nvidia and cloud suppliers; if the next raises fail, concentrated orders could contract together. x.com x.com x.comÂ
Google's allocation of massive TPU capacity to Anthropic strains its own AI effort while its researchers face compute constraints. CNBC reported internal tension; Anthropic competes with Gemini. Google should keep more TPUs for its own AI and buy more NVIDIA GPUs to rent to cloud customers, serving CUDA developers alongside Gemini. Selling TPU systems changes the equation, but Alphabet does not disclose TPU margins, so NVIDIA-like economics cannot be assumed. x.comÂ
More AI tokens mean more compute demand for Nvidia even as pricing power starts to slip. OpenRouter data via the FT show weekly token use up ~250-fold since January 2025; the FT links the surge to agents' long call chains. Bloomberg's breakdown of a 1 GW AI campus that could cost roughly $30B puts well over half the bill in chips and servers, most landing at Nvidia as GPU racks. Servers wear out in 5-6 years, making AI capex a recurring chip refresh. x.com x.com x.com x.com x.com x.com x.comÂ
Nvidia's funding of future customers in Germany further blurs how much chip demand it paid for itself. Jensen Huang said Nvidia invested almost $1B there in the last year and is investing in four more companies this week; German taxpayers are helping too. Finding buyers beyond Big Tech is smart, but the more sales come back from Nvidia's own checks, the harder genuine demand is to gauge. x.comÂ
Nvidia's CUDA retains developers, putting it among 12 stocks that could dominate the decade ahead. Nebius's GPU rental price rise signals demand; Fabrinet and Credo supply AI connectivity. DraftKings has betting scale; Microsoft has Azure and an OpenAI partnership; Figma anchors design work; Shopify powers stores. TeraWulf pivots power sites to AI leases; Constellation, the largest US nuclear operator, signs big-tech power deals; Meta spends on AI; Uber has autonomous-vehicle partnerships. x.com … Show more
