저자: 미상 · 외국인
요약 보기
엔비디아는 AI 칩 독점적 위치(CUDA 생태계, NVLink)를 갖고 있으나, TSMC CoWoS-L 패키징 병목, 빅테크 자체 ASIC(TPU, Trainium 등)의 추격, 금리·무역규제·전력 제약이 성장 한계로 작용한다고 주장. 임원 대량 매도, RSI 과매수(83), 데이터센터 매출 비중(89/96.2B) 및 공급·용량 약정 증가($119B→$279B), 지급보증·재매입 의무 등을 리스크로 지적. 반면 매출 106% 성장, 75% 매출총이익률, 기관 지분 확대를 근거로 강세 논리도 제시. 전반적으로 '인프라 하드웨어 사이클의 정점'과 '구조적 독점 지속' 사이에서 양측을 다루며 명확한 단기 방향 결론은 제시하지 않음.
다듬은 글
Here is a limitation that the market overlooked. Nvidia's estimate is based on TSMC CoWoS-L technology and a large amount of HBM3e with a memory bandwidth of 8 terabytes per second. Blackwell contains a large amount of HBM3e ( high- bandwidth memory, third- generation), enabling DRAM stack data transfer rates of over 8 terabytes per second.
The question is whether this position will hold. Business security score — 78 out of 100, high resilience. If we analyze the AI stack, Nvidia occupies a first-level bottleneck position, controlling GPU accelerators and the CUDA software environment. The protective barrier here is the software ecosystem, and it must be durable.
The Blackwell architecture is in full production with high demand, but there are supply issues due to TSMC CoWoS-L packaging limitations. Hyperscaler capital expenditures will remain high through the end of 2025. The only force that can shake this is the hyperscalers' own ASICs: Google TPU, Amazon Trainium, Meta MTI, and AMD ROCm, which closes the 18-month gap.
Here is a limitation that the market overlooked. Nvidia's estimate is based on TSMC CoWoS-L technology and a large amount of HBM3e at a speed of 8 terabytes per second. But thermal stress during packaging creates a risk of microcracks that the market ignores. This episode looks at how physical limitations, not hype cycles, define the real limit.
Institutional investors confirm this. Vanguard increased its stake by 9% , Morgan Stanley by 4%. Wall Street sees this as confirmation of undisputed dominance in data centers as enterprise software becomes a mass product. The market has embraced Nvidia as a machine of endless growth, valuing long-standing corporate demand as a permanent monopoly.
But traders ignore the laws of physics. Silicon performance is governed by the laws of thermodynamics, not by estimation models. Nvidia's entire assessment rests on a single physical packaging constraint: TSMC CoWoS-L—a "chip on substrate" using silicon vias to connect compute dies to high- bandwidth memory.
This heat density forces the use of liquid cooling and pushes thermal design to the limits of infrastructure capabilities. In terms of bandwidth , Blackwell features a large amount of HBM3E, a third- generation memory, delivering DRAM stack speeds of over 8 terabytes per second. The complexity of packaging creates a serious risk of microcracks during thermal expansion.
This is a limitation that limits growth potential. AMD ROCm, AMD's open source development platform, lags behind in compilation efficiency, but its own hyperscaler developments have changed the battlefield. Google TPU v5p and Amazon Trainium 2 completely avoid the markup on third-party chips for high-load tasks.
Nvidia's quarterly financial reports show only moderate revenue growth. Here's what the data reveals. Nvidia is not limited by the demand for AI computing. It is limited by the cost of capital to create them. Monetary policy acts as an economic brake on hyperscaler investment, directly impacting the multi-billion dollar budgets that drive Nvidia's revenue.
Institutional capital is currently going through a distinct late-stage accumulation cycle. Large institutional managers like Vanguard and Morgan Stanley have been adding to their positions in previous quarters , but the macroeconomic environment is shifting from liquidity expansion to capital rationing.
The Federal Reserve keeps the benchmark interest rate at 3.75% with consumer price inflation at 3.4% annually. The 10-year Treasury yield remains elevated at 5.24%, maintaining serious pressure on long-term corporate borrowing costs. Even with a normalized yield curve with a spread of 0.46%, high long-term rates force cloud providers to carefully evaluate the return on invested capital.
Kalshi Forecast Markets estimates a recession probability of 4.2%, based on a spread between 10-year and 3-month bonds of 1.09%. This low probability of recession restrains immediate panic, but capital spending cannot remain indefinitely detached from the cost of borrowing. The cost of capital is now a real constraint when it remains above 5%.
Enterprise clients must demonstrate rapid profit from implementing AI, not from speculative model training. Macro-placement is the transition from unlimited expansion to structural constraints . High interest rates are putting pressure on the margins of software customers who purchase accelerated computing resources.
If monetization slows in the final stages , the rate of capital inflow into data center equipment drops sharply. Implementations should generate revenue now. In addition to monetary policy, regulatory and trade interventions fragment global semiconductor markets. Export restrictions imposed by the US government prevent the delivery of advanced computing architectures to strategic regions.
These trade rules force Nvidia to develop simplified regional processors like the H20. These modified chips have a lower average selling price and lower gross margin. Sandwiched between federal trade barriers and high corporate profitability, the costs of scaling modern computing clusters are rising in every geographic region.
Trade walls squeeze margins. Geopolitical bottlenecks pose a serious physical risk to Nvidia's multi-trillion dollar supply chain. TSMC's revenue grew 53.3% year-on-year to NT$514.8 billion, indicating insatiable demand for accelerators in the near term. However, each advanced wafer depends on deep ultraviolet lithography systems manufactured by ASML in the Netherlands, assembled in Taiwan, and routed through narrow trans-Pacific logistics corridors.
Any escalation in the Taiwan Strait threatens to halt global production of AI hardware overnight, as alternative foundry facilities with similar CoWoS capabilities do not exist. Meanwhile, Jon Peddie and Mercury Research report that Nvidia has approximately 92% of the discrete graphics card market. However, this figure represents a slight retreat from the previous level, while AMD advanced to the low single-digit percentage level, securing 0.8 percentage points of market share.
While Nvidia still monopolizes the data center accelerator market, states prioritize domestic independence in the semiconductor industry through government subsidies and regional antitrust regulation. Global dependence on one manufacturer. At the same time, political sentiment regarding the huge energy consumption of big technology companies is becoming increasingly acute.
Large-scale data center clusters require hundreds of megawatts of power from local power grids, prompting regulatory oversight from municipal commissions and environmental agencies . Public opposition to industrial energy consumption limits permits for data centers in critical indoor locations. Physics now limits scaling.
The rotation of capital in markets demonstrates that government policies and limited physical resources are becoming real obstacles. While institutions accumulated stocks during previous phases of liquidity , the concept of sovereign AI now faces the reality of grid congestion and geopolitical vulnerability.
Nvidia operates in a macro environment where government governance, regulatory constraints, and energy bottlenecks define the limit of accelerated hardware deployment. Hyperscalers channeled $110.8 billion in capital expenditures in the second quarter: GCP spent $44.9 billion, Azure $ 35.8 billion, and Meta allocated $30.1 billion.
In our lab, we track this capital flow directly into demand for silicon chips. Nvidia turned this infrastructure development into $96.2 billion in quarterly revenue, up 106% year over year. Despite consistent reductions in capital expenditures, corporate and government demand is ensuring full utilization of Blackwell and Vera Rubin's production capacities.
Nvidia reported earnings per share of $2.22. , exceeding Wall Street's estimate of $2.14. by 3.8%. Nvidia is on a streak of four consecutive quarters of better-than-expected results, with average earnings per share above expectations by 3.4%. In the second quarter of fiscal 2027, the company beat the consensus estimate by 3.8%, with a figure of $2.22 .
per share after previous increases of 4.3%, 3.6% and 2%. In the lab, we see that management consistently sets achievable targets, but the margin of exceeding expectations remains tightly concentrated in the range of 2% to 4.3%. With revenue up 106% year- over-year to $96.2 billion and a third-quarter forecast of $108 billion, execution remains consistent, but the narrow range of deviations confirms that the market has accurately tuned to their baseline.
Nvidia's computing power is trending upwards with a price of $233.95. AI has reached its tipping point. He does useful work. Its tokens are productive and profitable. Now the calculation is income. Jensen Huang, Founder and CEO , Q2 FY27 earnings report . This is the main message of the leadership. Four words define the entire corporate pitch.
Calculation is income. Sounds visionary. This is a calculated PR move designed to rebrand cyclical semiconductor equipment into a perpetual utility similar to software. If computing is revenue, customers don't buy a graphics processing unit ( GPU), a parallel processor for modern AI workloads, as a capital expense.
They buy it as a money printing machine. to stop Wall Street from questioning whether hyperscalers are generating real cash flow from their massive infrastructure spending. Now forget about prepared speeches and look at trading terminals. When executives liquidate over 4 million shares during a supposedly generational turning point, watch their hands, not their mouths.
Historically , significant insider selling of shares after another good report indicates that management knows that peak equipment profits cannot grow forever. Meanwhile, retail investor sentiment on StockTwits remains bullish at 88%. The crowd demands price targets of $500, convinced that equipment costs will rise indefinitely .
But let's look at where the " smart money" really stands. Source: 13F reports, mandatory quarterly documents detailing institutional shareholdings. The data shows targeted institutional accumulation. Vanguard Information Technology Index Fund increased its holdings by 9%. Morgan Stanley added 4%. Invesco QQQ Trust added 4%, and FMR LLC also increased its stake.
Katie Wood's ARK Invest holds a $509 million position in its actively managed exchange-traded funds (ETFs). What do the “smart money” see that retail investors don’t understand at all? Institutions do not buy a permanent monopoly on software. They are on the very crest of the component shortage wave , well aware that institutions control 71.4% of the shares.
They know that when the queues for equipment supply finally disappear, there will be a compression of multipliers. Daily short volume, according to FINRA, was 46.5%, consistent with normal underlying activity with no signs of a short squeeze. Management says: computing power is profit. The lab hears: lock in customer commitments before capital expenditure budgets are cut.
Financial indicators look perfect on paper . In the second quarter of fiscal 2027, Nvidia beat EPS expectations by 3.8%, reaching $2.22 per share. Revenue grew 106% year- over-year to $96.2 billion. Look at R&D— research and development, the capital invested in developing next- generation silicon. Nvidia has significantly increased its R&D spending over the past year.
However, as a percentage of revenue, R&D spending fell to only 8.6%. This is a structural signal. When revenue doubles and the share of research in revenue decreases, the company moves according to the inertia of previous architectural solutions , rather than building new technical barriers. The real vulnerability lies in the 10-Q report—the latest quarterly operating report to the Securities and Exchange Commission.
Prepared speeches from management place a strong emphasis on diversification: robotics, driverless cars, and digital twins. However, strict accounting paints a completely different picture. Data centers generated $89.0 billion of the company's total revenue of $96.2 billion. Worse, management hid staggering liabilities in the risk factors section.
Nvidia's multi-year supply and capacity commitments have increased from $119 billion to $279 billion. Read the disclosure carefully. Nvidia provided credit guarantees to SB Energy covering 4.25 gigawatts of IT load in Ohio for OpenAI, with commitments capped at $105 billion. Moreover, Nvidia admitted that it had entered into agreements with cloud AI providers under which, if these clouds were unable to sell their capacity, Nvidia was legally obligated to buy it back.
Nvidia doesn't just sell commercial semiconductors. The company is actively supporting debt, guaranteeing customer leasing, and absorbing unsold cloud capacity to maintain the illusion of demand. This is financing from a provider under a different name. Please note Note 10 in the next 10K report. If supply and capacity commitments increase and gross margin (non-GAAP) falls below 74%, the bullish thesis will collapse.
When a chipmaker has to maintain huge data center leases to keep up with its order book, you see the absolute peak of the hardware cycle. Nvidia Momentum Analysis: RSI at 83 indicates an overbought zone, signaling caution on new positions. MACD is currently bullish, the histogram has crossed the zero mark.
Nvidia's dominance isn't just in chips. This is a data center-level computing infrastructure: NVLink hardware intertwined with CUDA libraries that binds customers to a single system. The company designs data center-scale computing fabrics, not individual crystals. NVLink, a proprietary interconnect hardware that connects processors with microsecond latency, delivers 1.8 terabytes per second of bidirectional bandwidth .
This eliminates standard network bottlenecks. Competitors selling individual chips cannot match this cluster density. Opponents cannot replicate this architecture. 15 years of deeply tuned CUDA libraries protect this runtime . Enterprise workloads compiled on CUDA cannot be moved to different silicon without a complete code rewrite.
Software-based computing is stronger than hardware-based, but this computing monopoly faces pressing threats. Hyperscalers, with a $300 billion infrastructure pool, are actively funding domestic alternatives. Specialized ASICs, chips built for specific tasks, provide lower operating costs. Google TPU, Amazon Trainium, and Meta MTI already handle large volumes of internal inference.
AMD ROCm closes the historical software performance gap with CUDA. The wall is collapsing. Physical production also limits growth. CoWoS SL packaging, TSMC's advanced multi-chip method , remains a major limitation. GB200 racks generate thermal power exceeding 120 kilowatts. Cooling requirements create strict limitations.
Physics sets a real limit. Institutional capital flows tell a different story than the Wall Street consensus. Reports show broad index accumulation. The smart money recognizes a tipping point that ignores the consensus. What Wall Street says: “ Support margin expansion through infinite clusters.” What the lab hears: " Final phase of hardware deployment before the output moves to cheaper silicon." Wall Street views current deliveries as a steady cash flow from software.
The smart money views this deployment as a limited hardware cycle. Inference prioritizes cost per token, energy efficiency, and memory bandwidth over flexible architecture. The CUDA binding disappears when inference is performed in standardized environments. Hyperscalers will run repetitive workloads on cheaper internal ASICs.
Nvidia will dominate complex clusters for learning. Output volumes will inevitably flow to cheaper domestic silicon . The learning remains, the conclusion goes. At $233.95, the stock is trading in the upper third of its 52- week range. The RSI is 83.0, elevated momentum. MACD is showing a bullish crossover.
Open interest in call options is 889,757 versus 660,354 put options. The resulting put- to-call ratio of 0.74 reflects neutral sentiment with an expected volatility of 23.4%. The stock is trading at a multiple of 29.6 to current earnings and 14.9 to forecast earnings. Market data indicates overbought conditions, but no panic.
This price reflects long-term competitive sustainability, not short-term attractiveness. If TSMC addresses the limitations of CoWoS and data center revenue continues to grow consistently through fiscal 2027 , Nvidia will prove that its commercial rack architecture remains indispensable for generative deployments.
The argument against this thesis: the consistent reduction in data center gross margins over the next two fiscal quarters suggests that the inference load for hyperscalers has already shifted to cheaper custom silicon. Here's the macroeconomic picture shaping Nvidia. Rates and Inflation: The Fed's federal funds rate is 3.75%.
Consumer prices increased by 3.4% year-on-year . The yield on 10-year Treasury bonds is 5.24%. Nvidia's own forecast, according to the 8K form dated August 26, 2026: expected revenue will be $108.0 billion plus or minus 2%. AI Supply Chain Pulse: TSMC's monthly revenue in 2026 reached NT$514.8 billion, up 53.3% from a year earlier.
Nvidia completely dominates its peers in the semiconductor industry thanks to pricing power with an unmatched gross margin of 75%. Advanced Micro Devices has captured the market momentum with a 216.6% gain this year. The market is currently paying 161.3 times earnings for AMD shares . However, AMD is showing revenue growth of 50.1%, which is less than half of Nvidia's figure.
Nvidia accelerates revenue growth to 105.9%. AMD also shows a gross margin of 56%, lagging behind Nvidia by a whopping 19 percentage points. AMD has the advantage in pure price momentum, but Nvidia beats it in the underlying economics of the hardware. Intel Corporation is showing a significantly weakened operating profile in the enterprise computing space.
Intel achieved revenue growth of 25.4%, while having an anemic gross margin of 39%. Investors are still paying 57.9 times earnings for Intel shares, despite these structural manufacturing difficulties. Intel's gross margin lags Nvidia's 75% by 36 percentage points. Intel retains the advantage in scale of internal production, but Nvidia is translating architectural efficiency into significantly higher margins.
Qualcomm is trading at a heavily discounted valuation with a forward earnings multiple of just 21.2. This low multiplier gives Qualcomm an advantage over all peers in terms of valuation affordability. However, Qualcomm is actively shrinking, showing negative revenue growth of 4.0%. Its gross margin of 54% is 21 percentage points lower than Nvidia's benchmark.
Compression of multipliers is quite rational when income is actively declining. Wall Street often focuses on price/ earnings ratios, but Nvidia's official multiple is not disclosed here. The laboratory never guesses at missing numbers or relies on unverified financial estimates. Instead, we focus on proven capital efficiency and operating leverage.
We weigh pricing resilience against valuation pressure to identify a true market leader. AMD carries an aggressive valuation burden of 161.3 times earnings. The company is bearing this burden with lower revenue growth and lower profits from silicon products. Nvidia combines 105.9% growth with a gross margin of 75%.
This unique combination provides Nvidia with the highest operational stability in the entire semiconductor universe. Qualcomm offers security assessment without operational expansion. Intel has high overhead costs and a compressed margin of 39%. AMD demonstrates confident execution, but is unable to match the profitability of top- tier packaging.
Nvidia earns 75 cents of gross profit on every dollar of revenue. This creates an unrivaled cash reserve for ongoing research and the launch of modern technological processes. No competitor in silicon chip development today can replicate this ability to generate money. Nvidia's operating " moat" is confidently ahead of all competitors, and only a prolonged erosion of margins below 55% could change this reality.
The NVDA Persistence Index at 78 indicates strong and viable momentum in the market. Which argument is stronger for Nvidia: optimistic or pessimistic? Express your opinion in the comments. This video is for educational purposes only and is not financial advice. You should do your own due diligence and remember that past performance does not guarantee future success.
Markets can change quickly, and individual risk tolerance varies greatly. So adapt any solutions to your personal situation. If you want to see our full AMD analysis, the link is in the description. Subscribe now for deeper insights into chips you can't miss. Be vigilant. See you later .
Comments 0