Enes Uludağ
US Equity & Global Macro Analysis, Financial Statements & Sector Research
Nvidia's demand no longer rests only on the big cloud companies, so it is too early to say AI spending is ending. Hyperscale revenue was $48.7 billion, up 13% quarter over quarter, while the ACIE segment reached $40.3 billion, up 25% sequentially and 138% year over year. Demand from neoclouds, enterprises and governments is growing fast. x.com
Nvidia is moving into energy, which could become the limit on AI growth, and that could strengthen its grip on the AI ecosystem long term. It is reportedly in talks to invest hundreds of millions of dollars in power developer Cloverleaf Infrastructure, which has over 10 GW of projects in its pipeline. More AI capacity needs more GPUs, data centers and electricity, so securing power matters as much as strong chips. Nvidia is building positions across GPUs, networking, data centers and energy. x.com
Enterprise and neocloud demand is creating a second wave of AI infrastructure spending, with tailwinds for Nvidia and Super Micro. Dell forecasts 200 GW of AI data center growth through 2030, half driven by these customers, and estimates a $1 trillion AI infrastructure opportunity over the next four years. AI servers could enter a new growth phase in 2027, with higher shipment volumes and more revenue per deployment. x.com
Anthropic's customer spending and compute buildout show AI monetizing at scale, a bullish read-through for Nvidia, Broadcom, Alphabet, Amazon, Microsoft, Nebius, CoreWeave and Hut 8. Its IPO filing reports H1 revenue up 14-fold to $16.3B, 11,900+ customers spending $100K+ annually and 1,900+ spending $1M+, alongside $9B in H1 infrastructure spending and about $430B in future compute commitments. x.com
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.com
Anthropic's customer growth gives AI compute suppliers firmer demand evidence than capacity plans. Its S-1 reports $16.3B in H1 2026 revenue and about 900% net retention as of September 30, the strongest evidence yet of adoption. Over $500B in commitments include a roughly $125B five-year Broadcom equipment lease plus Amazon, Google and Microsoft arrangements; Nvidia GPUs are in its mix. Long-term obligations could outlast usage revenue. x.com
Nvidia's capacity commitments argue against AI orders drying up soon. Its filings show mostly memory and manufacturing commitments rising from $119 billion to $279 billion in one quarter, with about $175 billion covering 2027-28. Fewer new data-center projects could reflect power, land and building bottlenecks rather than weaker demand; a mid-teens multiple still reflects a fair worry that profits may not last. x.com
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.com
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.com
Nvidia's Q2 shows the $1 trillion AI infrastructure cycle is not slowing. Data Center revenue hit $89.0B, up 117% year over year, as hyperscaler and neocloud cluster buildouts accelerate. Revenue reached $96.2B, up 106%, and non-GAAP EPS $2.39 versus $2.09 expected. Margins held near 75%, showing intact full-stack pricing power as generative AI, reasoning and agentic workflows flow into the CUDA moat. x.com
NVIDIA faces a market-wide selloff once a slowdown or halt in hyperscaler capex growth is confirmed. Whether non-hyperscalers absorb some of the excess supply, despite 52-week GPU wait times raised in a reply, is immaterial to that reaction. x.com
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.com
