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Memory scarcity is now the bottleneck of the whole AI buildout, which is bullish for memory sellers such as Micron, SK hynix and Samsung. Nvidia reported revenue of $96.2B, up 106%, guided Q3 to $108B and gave a first look at roughly 70% growth next fiscal year, about $100B above Street models, while calling itself supply constrained. The tell is its margin: 74% next quarter, troughing at 71-72% by Q4 as memory costs bite. x.comÂ
SK hynix, Samsung and Micron hold the pricing power in AI hardware. DRAM contract prices rose 90-95% in one quarter, DDR5 went from under $7 to over $27 per GB in three months, and lead times stretched from 10 to 24 weeks as memory makers tore up long-term contracts for quarterly pricing. HBM has no substitute, qualification takes 12-18 months, and SK hynix removed price caps from long-term contracts. Per Bloomberg, AI server prices are rising 15%+ for systems shipping early next year. x.com 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
Micron and SK hynix pricing in a memory shortage past 2030 extends the memory-cycle case beyond the Street's 2028 expectation. SK hynix's record quarter adds evidence: per Wall St Engine, revenue rose 328% to $78.9B, operating profit rose 632% to $62.8B, and operating margin hit 80%. Agentic and physical AI could add demand as they roll out. x.com x.comÂ
Financing risk makes AI-linked growth stocks unattractive to add here. Much of the money reaching suppliers such as Nvidia and Micron is financed, so harder funding would limit spending on chips, compute and memory. The buildout is not over, but stock prices could remain suppressed until it slows. A significant drawdown would make adding appealing; for many high-beta names with weak fundamentals and balance sheets, the highs look to be in. x.comÂ
AI's physical buildout looks set to last to 2030 and beyond because financing, memory supply and hyperscaler spending still point to sustained demand. Nebius has $3.5B in financing, IREN $2.4B at 9% and SPCX $40B for GPU equipment. SK hynix expects shortages through at least 2030 and Samsung says HBM4 is sold out; memory companies are making money with no sign of slowing. Google expects 2027 capex to rise significantly. Pullbacks can happen; be cautious and buy quality. x.comÂ
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.comÂ
Memory's high margins are less durable than those of Nvidia or AMD because memory is a perfect substitute across suppliers and their chips are not. Memory margins have also risen far more than those names', so while chipmakers may eventually see some compression too, it should be smaller than in memory. x.comÂ
Nvidia's across-the-board beat shows AI capex has not hit the brakes, which keeps upstream memory demand rising and supports SK hynix. Q2 revenue rose 106% to $96.22B and data-center revenue 117% to $89B, and Q3 revenue guidance of $108B also beat expectations; Vera Rubin should make up about 20% of Q3 data-center revenue. Rising memory and other component costs are starting to pressure Nvidia's gross margin, a new point to watch in coming quarters. x.comÂ
A memory-chip shortage lasting until 2030 is good for Nvidia. SK hynix expects that shortage and reports a 632% profit jump. x.comÂ
Inflation, rising rates, Chinese competition and rising AI-related financial costs are pressuring the memory market. Micron, Samsung and SK hynix look exposed; waiting for the cycle to turn. x.com x.comÂ
Agentic AI's repeated context favors cache memory and storage demand for Micron, SK hynix and Sandisk over fresh GPU computation. Per @demian_ai, about 95% of input tokens for DeepSeek V4.1 Flash on OpenRouter were cache hits; storage matters unless routing and caching keep almost everything in GPU memory. New products such as 3D DRAM and HBM-on-logic could be the final trigger for a full memory-stock re-rating. x.com x.comÂ
