Summary: Samsung is the direct beneficiary of rising commodity DRAM prices given 70% of DRAM capacity there; SK Hynix faces margin pressure as HBM-focused strategy may be outpaced by commodity DRAM profitability in 2026.

Samsung puts more weight on expanding production of commodity memory than HBM… Aiming to maximize profitability

Samsung Electronics has set the core goal of next year’s DS (Device Solutions) semiconductor business as “maximizing profitability” and has begun to reorganize its strategy accordingly, with Han Jin-man, head of the Foundry Business Unit, being mentioned as a candidate to head the Memory Business Unit. Until Samsung’s high-bandwidth memory (HBM) technology improves and selling prices can be fully maximized, the company is sketching out a scenario in which it focuses more heavily on commodity DRAM, where profitability can improve more quickly.

Recently in the industry, Han Jin-man, who previously served as Head of Strategic Marketing Office in the Memory Business Unit, has been mentioned as a candidate for the Memory Business Unit chief, and this is being interpreted as part of the same trend. The view is that if Han, who comes from a “strategic marketing” background, takes over the Memory Business Unit and strengthens price-negotiation power for DRAM and NAND to maximize profitability, DS division operating profit could approach 100 trillion won next year and the year after.

According to a source familiar with the company’s situation, Samsung Electronics plans to keep its existing HBM production target for next year, while expanding production of commodity DRAM. To this end, it is preparing a plan to further increase capacity for 10-nanometer-class 5th-generation (1b) DRAM and allocate a significant portion of that capacity to commodity DRAM. Internally, it is also reviewing the option of partially utilizing NAND flash production lines.

A company official stated, “Next year, the absolute top priority is to maximize profitability,” adding, “We have recently been outperformed in technological competitiveness by SK hynix and have fallen behind, and at this point our competitiveness is not yet sufficient to aim for a rapid reversal through HBM alone.” The official went on, “Internally, the stance that we must demonstrate a clear advantage on the profitability front has become stronger,” and added, “The intention is to regain the number-one position in operating profit, overtake SK hynix, and project confidence to the market.”

The reason Samsung Electronics is seeking to boost profitability in commodity DRAM products such as DDR5, LPDDR5X, and GDDR7 is that their prices have been on a clearly rising trend recently. As the three memory players (Samsung Electronics, SK hynix, and Micron) have concentrated their DRAM capacity on HBM, supply of commodity DRAM has declined, creating strong upward pressure on prices. According to semiconductor distributor Fusion Worldwide, the November contract price of Samsung’s 32GB DDR5 memory chip module reached 239 dollars, up 60% from 149 dollars in September.

In contrast, Samsung Electronics’ HBM business is still viewed as lacking sufficient market position relative to competitors to expect high profitability. From next year, the price decline of the previous-generation HBM3E 12-high products is already taken as a given, and solid results in HBM4 will be essential to secure profitability. However, Samsung has yet to finalize an HBM4 supply agreement with Nvidia and still lacks sufficient market share. Even if Samsung were to receive the same price as SK hynix for HBM4, taking current yield and cost structures into account, profitability would still fall short of the level of commodity DRAM.

Accordingly, Samsung Electronics plans to maintain a strategy of gradually taking share from SK hynix in HBM through technological improvements, while preparing a separate plan to maximize profitability in DRAM and NAND, where it already has strengths in market dominance. For HBM, the idea is to prioritize market share even at the cost of profitability, and to offset the resulting losses with earnings from commodity DRAM.

A semiconductor industry source said, “Samsung Electronics manufactures the base die for HBM4 in-house, but compared with SK hynix, which outsources base-die production to TSMC, its cost structure is not that favorable.” The source added that while SK hynix has seen total HBM4 costs rise by around 30% compared with HBM3E, it has still managed to secure a similar level of price premium from Nvidia and defend its profitability. Samsung, meanwhile, is applying the 1c DRAM process to HBM4 core dies, but small-scale wafer test yields are reportedly only around 50%, meaning significant improvement is required before moving to mass production.

Against this backdrop, there is talk that in the upcoming Samsung executive reshuffle, Han Jin-man will be positioned as the next candidate for head of the Memory Business Unit. Han served as Vice President of the Strategic Marketing Office in the Memory Business Unit in 2020 and is evaluated as having strong capabilities in sales, including price negotiations. Even in the Foundry Business Unit, which had relatively few big-tech references, he proved his performance by successively securing Apple and Tesla as customers.

The aforementioned company official said, “The reason Han has recently emerged as a candidate for Memory Business Unit chief is also his price-negotiation capability,” and continued, “The strategy is to use Han’s negotiation skills to extract as much profit as possible by seizing the opportunity presented by the sharp price surge in commodity DRAM next year.”

In fact, during its recent third-quarter earnings conference call, Samsung Electronics stated that it was “internally reviewing the possibility of increasing HBM production,” but at the same time noted, “With the recent rise in commodity DRAM prices, profitability is improving steeply, so we will determine the scale of additional expansions at an appropriate level while monitoring market conditions, taking into account relative profitability between HBM and commodity DRAM.”

The plan to further expand 1b DRAM capacity is expected to take the form of conversion investments on existing production lines. The 10-nanometer-class DRAM process has evolved in the order of 1x (first generation) → 1y (second generation) → 1z (third generation) → 1a (fourth generation) → 1b (fifth generation) → 1c (sixth generation). Samsung Electronics is expected to carry out conversion investments on matured-node lines such as 1z, and allocate a large portion of the additional capacity secured to commodity DRAM.

The company is also reviewing a plan to convert part of its NAND capacity to commodity DRAM. Samsung has displayed a rather conservative attitude toward NAND capacity expansion, stating in its third-quarter conference call that it would “focus on converting existing lines to advanced nodes” in NAND. Internally, it is reportedly even discussing a plan to reduce NAND capacity.

A semiconductor industry official added, “Samsung Electronics has had many experiences in the past of suffering losses after being swayed by capacity-expansion demands from customers such as Apple, so it tends to be conservative about the NAND business,” and continued, “The company also believes the recent upward trend in NAND prices will not be sustainable for long, so it appears to be considering converting part of that capacity.”

Meanwhile, the securities industry currently estimates next year’s operating profit at about 76.2045 trillion won for Samsung Electronics and 70.2742 trillion won for SK hynix. Foreign securities firm Morgan Stanley, in a report titled “Memory – Maximum Pricing Power” published on the 10th (local time), projected Samsung Electronics’ operating profit for next year at 116.448 trillion won, with the semiconductor (DS) division accounting for 94.625 trillion won of that. For 2027, it forecast operating profit of 135.22 trillion won, with semiconductor operating profit of 109.896 trillion won.

By contrast, SK hynix plans to maintain its management stance of making profitability maximization through HBM its top priority next year as well. Some in the industry expect SK hynix’s HBM operating margin to reach as high as 70%. In the Q&A session of its third-quarter conference call, SK hynix said regarding the possibility of adjusting capacity mix, “There is a possibility that general DRAM margins could become similar to those of HBM, but we will not immediately adjust our capacity mix based solely on temporary changes in profitability,” thereby officially declaring its policy of focusing on HBM.

Kim Dong-won, an analyst at KB Securities, stated, “We expect DDR5 margins to surpass those of HBM in 2026, leading to a reversal in profitability,” and added, “Samsung Electronics, which operates about 70% of its total DRAM production capacity as commodity DRAM, will be the direct beneficiary.”

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https://t.co/APe7xxnb8v


Samsung has yet to finalize an HBM4 supply agreement with Nvidia and still lacks sufficient market share. Even if Samsung were to receive the same price as SK hynix for HBM4, taking current yield and cost structures into account, profitability would still fall short of the level of commodity DRAM

structural marker; pre-classified as canonical yfinance ticker


MediaTek significantly raises its ASIC business targets

Summary: Bullish MediaTek on significantly raised ASIC revenue targets ($1B CY26, multi-billions CY27+).

Reitarates ASIC revenue target of $1B in CY26 and multiple billions in CY27. More complex follow on project is expected to generate revenue from '28 and beyond.


Summary: Shares DA Davidson Underperform rating on CoreWeave PT $36, with detailed bearish thesis on negative return on capital, customer concentration risk, and heavy insider selling.

DA DAVIDSON) CoreWeave, Inc. Price Target $36, Underperform

Will the order backlog convert (into revenue)? Must it?
We understand we may not get a chance to ask questions today (perhaps we should have behaved more kindly). So for CoreWeave, which reports earnings this evening, we’ve listed several good questions others might consider asking. We fully expect the company to report better-than-expected revenue and profits, but we question how important that is in light of the answers to the questions below.

1. Where do you rank within OpenAI’s spending? Since your last earnings report, your key customer (OpenAI) has announced several other contracts—most notably $300 billion with Oracle, $250 billion with Microsoft, and $38 billion with Amazon. If, for any reason, OpenAI cannot fulfill all $1.4 trillion of its commitments, how could you get paid ahead of Microsoft, Amazon, and Oracle?

2. What is your return on capital? By our calculation, last quarter’s return was 5% (annualizing $200 million of adjusted EBIT on $16.6 billion of PP&E). Your contract terms are fixed up front and you have already achieved scale; how can you improve this return toward peers’ 15–20%?

3. What is your cost of capital? By our calculation, last quarter’s weighted average cost was 10% (annualizing $267 million of interest expense on $11.0 billion of debt). We can see you are gradually lowering this with additional sub-9% debt, but can you bring it down to Meta- or Oracle-like levels as the likelihood of your primary customer honoring its commitments appears increasingly uncertain?

4. If the answer to Question 3 (cost of capital) remains higher than Question 2 (return on capital), why would an investor want to buy the stock of a company generating negative returns?

5. Do you have sufficient capital to build out to the level promised to OpenAI? If, for any reason, you cannot, wouldn’t they be able to cancel the contract? Doesn’t your S-1 say so? If so, what happens next?

6. If you still believe in what you are doing, why are you selling so much (see pages 2–15)? In 25 years of doing this, we don’t recall seeing this many Form 4 (insider sale) filings over a three-month period.

$CRWV


Summary: Bullish Micron; solid profits expected even without HBM4, no reason to sell.

@DhaniSriram Micron will generate solid profits even without HBM4. Why sell?

@jukan05 Would you sell Micron or you’re still bullish because of the memory super cycle?


That's a negative development for Advantest.

Summary: Korean firms displacing Advantest in SK Hynix HBM4 test equipment supply chain; bearish for Advantest.

industry='Semiconductor Equipment & Materials'

According to Korean media reports, Korean companies are making a large-scale entry into SK hynix’s HBM4 test equipment supply chain.
That’s a negative development for Advantest.

SK hynix’s HBM4 Test Equipment Supply Chain Takes Shape… Korean Equipment Makers Gaining Ground

SK hynix is preparing investments in test equipment for full-scale HBM4 mass production next year. The company is expected to complete supply-chain build-out by the end of the year, https://t.co/3nubPrnMzA


Summary: Long Doosan as top CCL pick on M9-driven growth.

Doosan Electronics CCL supplier context 006280.KS

Drug Manufacturers - Specialty & Generic

Lately, I’ve been researching CCL (Copper Clad Laminate) companies.

M9 is going to drive tremendous growth.

My pick: Doosan. https://t.co/DzmlwgmTLH


GFHK believes Intel could win projects on 14A for Apple's non-Pro smartphone SoC, Nvidia and AMD's server projects, and a Tier-1 Ethernet switch vendor.

Summary: Bullish INTC on potential 14A foundry wins with Apple, Nvidia, AMD, and a Tier-1 Ethernet vendor.

Very interesting.
GFHK believes Intel could win projects on 14A for Apple’s non-Pro smartphone SoC, Nvidia and AMD’s server projects, and a Tier-1 Ethernet switch vendor.

$INTC

Turn out it's many things to shock the market but not negatively Lol

GFHK: We still expect Intel to ramp 18A and 18A-P at small scale in 2026 to ensure yield and quality. That said, the external customer is expected to start by end-2026. In addition to the aforementioned Apple


Summary: Samsung's 3Q25 call signals rising memory prices, HBM3E bit shipments up 80%+ QoQ, HBM4 in mass production prep, and improving foundry profitability — all pointing to continued earnings recovery.

Samsung Electronics 3Q25 Earnings Conference Call Key Q&A (1)

1. What drove the strong 3Q performance, and what is the outlook for 4Q?

• Data-center investments expanded far more than expected due to increasing inference demand, leading to strong server demand. Market prices are rising in mobile and PC as well. Our company also expanded sales mainly in AI-related products.

DRAM shipment volume grew by the mid-teens %, led by D5 and GD7, while server SSD shipments increased by around 10 %. Inventory decreased, and results exceeded guidance. DRAM prices rose by the mid-teens % thanks to a higher sales mix of HBM, and NAND prices increased by the mid-single digits.

• Demand remains solid, and inventory levels are expected to fall below normal levels, so we expect a wider increase in memory prices. We will continue to operate with a profitability-focused approach. We will expand 3E demand and respond to high-capacity server D5 and LPD5. Shipments are expected to increase by a single-digit %. NAND shipments are expected to decline by about 10 %, though SSD demand should remain strong.

2. Update on share buybacks?

• The program was fully completed at the end of September, earlier than the initially announced target and disclosure deadline. In addition to the annual KRW 9.8 trillion dividend, we successfully completed the share repurchase. We recognize investors’ interest in further shareholder-return plans and are considering ways to enhance long-term shareholder value. We plan to retire part of the repurchased shares as soon as possible.

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Samsung Electronics 3Q25 Earnings Conference Call Key Q&A (2)

3. Update on the HBM business?

• Demand is increasing faster than supply, and we are expanding mass production and sales of HBM3E to all customers. Compared to the previous quarter, bit shipments expanded by more than 80%. Development of HBM4 products has been completed, and samples have been shipped to customers. Mass production shipment preparation is complete. Recently, as performance competition among customers has intensified, we set and prepared performance targets that exceed customer requirements in advance.

AI performance enhancement requirements are increasing. We will continue to actively execute capacity investments for the 1c nanometer node.

Production plans for 2026 will be significantly expanded compared to this year, with customer demand already secured. However, as additional customer requests are being received, we are internally reviewing the possibility of further expansion. Profitability of conventional products is also improving, so we will expand while considering relative profitability and overall market conditions.

4. Outlook for the 2026 memory market?

• Memory growth momentum will continue next year. High-performance HBM4 will fully arrive, and server DRAM will continue to move toward higher capacities. Supply constraints will also persist. NAND demand will increase mainly for high-capacity products. As QLC demand strengthens, inventory will approach bottom levels earlier than expected. However, we are closely monitoring geopolitical issues. We will lead the market and respond proactively.

5. Stock compensation program

• Announced a program for creating long-term performance. The stock compensation system will be expanded from executives to all employees, with the aim of establishing a foundation for motivation and shared growth. The number of shares will be determined based on performance and future stock price increases, and distributed in installments over three years. Since January 2025, the stock grant system has been implemented to strengthen accountable management, and it is now being extended to all employees. Of the 8.4 trillion KRW in treasury shares, an appropriate portion will be retired at the right time, and the remainder will be used for the stock compensation program. The timing of additional share repurchases will be decided by the board of directors.

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Samsung Electronics 3Q25 Earnings Conference Call Key Q&A (3)

6. Background of reduced losses in the Foundry business?

• In the first half of this year, one-off costs such as provisions for unsellable products due to the impact of advanced chips were reflected. Performance was sluggish due to sales of high-cost products and low utilization rates. As these factors have disappeared and utilization rates have improved, the loss has been significantly reduced.

Going forward, with the full-scale mass production of the first-generation 2nm process and the expansion of HPC and automotive products for major U.S. and Chinese customers, sales are expected to increase. Further performance improvement is anticipated through continuous utilization rate improvement and cost-efficiency activities.

7. Profitability outlook for the smartphone division?

• Memory prices began to rebound in earnest from the third quarter, and the rate of increase will expand in the next quarter. Despite rising cost burdens, sales will increase centered on the foldable lineup. We will also expand the Tab and Watch series to strengthen our dominance in the premium market. Process optimization efforts are also underway.

8. Direction of memory investment?

• Over the past few years, we have consistently invested in cleanroom capacity. We will continue facility investments in line with demand. For DRAM, facility and construction investments based on 1b and 1c nodes will increase to some extent. For NAND, the proportion of advanced process nodes will be gradually expanded.

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Samsung Electronics 3Q25 Earnings Conference Call Key Q&A (4)

9. Background of reduced foundry investment this year?

• This year, although we invested in advanced processes, mass production lines mainly focused on supplementary investments for existing lines. In 2026, we will maintain a flexible investment stance while completing facility investments for the new Taylor fab in the U.S. We plan to expand investments to a level similar to 2024 while simultaneously preparing for the mass production of new processes such as the second-generation 2nm.

10. Future display strategy?

• OLED sales are expanding across various segments such as IT, automotive, and wearables. Demand for high-resolution displays is increasing and expected to continue. In 2026, we will expand production of competitive products using the new 8.6-generation line and strengthen our responsiveness to customers. For automotive displays, we will leverage competitiveness in rigid OLEDs to expand into volume zones and apply differentiated technologies. We will maintain a stable business portfolio.

11. Exynos

• We have a clear standard for customer experience in flagship products. This year, Exynos was adopted in the Flip7. It is difficult to confirm inclusion in the flagship S26 lineup for next year. Most device users this year are already utilizing Galaxy AI features, and we plan to continue expanding AI usage in the future.

12. TV market conditions and future strategy?

• Competition is intensifying. We will recover market share based on differentiated product competitiveness. We aim to secure technological leadership with Micro RGB and compete in the premium market. By expanding AI features and lineups, we will counter aggressive pricing from competitors and shift consumer focus toward value. We will launch an interactive AI platform and expand applicable lineups and countries next year. We also plan to target the mid- to low-end market and strengthen leadership in the ultra-large segment of 98 inches and above. The services business will continue to expand. TV Plus will implement a differentiation strategy through competitiveness in live broadcast content.


If you don't know which ASIC company will win, buy TSMC. All GPUs and ASICs are manufactured at TSMC.

Summary: Buy TSMC as the universal play on GPU/ASIC buildout regardless of which chip designer wins.

If you don’t know which ASIC company will win, buy TSMC.

All GPUs and ASICs are manufactured at TSMC. https://t.co/ntGduZoXU9


JPMorgan argued that Huang's forecast of explosive AI data center CapEx growth, while extremely aggressive, is entirely achievable from a financial standpoint

Summary: Shares JPMorgan report endorsing Jensen Huang's $3–4T AI CapEx forecast as financially feasible, implying sustained demand tailwind for NVDA.

Can Annual AI CapEx Grow from $600B to $3–4T? JPMorgan Says Jensen Huang’s “Boast” Is Financially Feasible

Recently, Jensen Huang predicted that global annual spending on AI data centers will soar from about $600 billion this year to $3–4 trillion by 2030. This implies an average annual growth rate of 42% over the next five years — prompting skepticism that Huang might be exaggerating.

However, JPMorgan, in a recent report, argued that Huang’s forecast of explosive AI data center CapEx growth, while extremely aggressive, is entirely achievable from a financial standpoint. The bank believes that through three major funding sources — internally generated cash flow, private equity/venture capital investment, and external financing through debt or equity issuance — the technology sector has sufficient capacity to support this unprecedented investment boom.

Facing a $1.6 Trillion Annual Funding Gap

JPMorgan’s calculations show that by 2030, the technology industry will face an annual funding gap of up to $1.6 trillion.

The analysis first focuses on the global technology industry (defined as companies in the MSCI Global Information Technology and Communication Services indices, plus Amazon and Tesla) and examines its cash flow and capital expenditure patterns. The report estimates that in 2025, the industry’s annual operating cash flow will be about $1.6 trillion, while CapEx, including R&D, will be around $1.3 trillion — leaving a $300 billion financial surplus.

Assuming AI data center investment reaches $3.5 trillion by 2030 (the midpoint of Huang’s projection), and that non-AI CapEx of $700 billion in 2025 grows at 11% annually (the three-year average), total non-AI CapEx would rise to $1.1 trillion by 2030. This would push total tech CapEx to $4.6 trillion by that year.

Even if operating cash flow grows 20% annually to reach $4 trillion, the sector would still face a $600 billion shortfall.

When shareholder returns are included, the pressure intensifies. JPMorgan assumes shareholder payouts (dividends + buybacks) will increase from $700 billion this year to about $1 trillion by 2030. Accounting for these payouts, the annual total funding gap would widen to $1.6 trillion by 2030.

Private Equity and Venture Capital: The Key to Filling the Gap

To bridge this trillion-dollar shortfall, private capital will be the first critical pillar. JPMorgan points out that PE, VC, and infrastructure funds are pouring into digital infrastructure and AI with unprecedented enthusiasm.

According to the report, annual fundraising for digital infrastructure currently totals about $70 billion, while PE/VC investments in AI and machine learning already reach an annualized $260 billion, according to PitchBook data. Together, private markets could provide roughly $330 billion in AI-related funding in 2025.

JPMorgan forecasts that if private capital grows at a conservative 10% annual rate, annual private investment could reach $531 billion by 2030 — narrowing the funding gap from $1.6 trillion to roughly $1.1 trillion.

Debt Financing: Controlled Leverage Expansion

The remaining $1.1 trillion gap will likely be covered primarily through debt financing. JPMorgan believes the tech industry is fully capable of taking on this level of leverage without triggering systemic risk.

Based on the structure of U.S. non-financial corporate financing, the report assumes 40% of new debt ($430 billion) will come from bank loans, and 60% ($640 billion) from bond issuance.

This raises the question of balance-sheet health. JPMorgan’s analysis indicates that even after this debt expansion, the sector’s net-debt-to-operating-cash-flow ratio would increase only from 0.7× today to 1.2× by 2030 — still far below the MSCI Global Index average of 2.2×. This suggests that tech companies maintain ample borrowing capacity to finance the future of AI.

Beyond Financing: The Next Bottleneck Lies in Energy

Although JPMorgan concludes that Huang’s AI CapEx projection is financially feasible, the report warns that other bottlenecks — particularly power generation and transmission capacity — will become the next critical challenge for sustaining this scale of growth.

$NVDA


Summary: Multiple packaging/testing names enter Google TPU supply chain with material revenue contributions expected in H2 2026: AMKR, ASE, KYEC, MPI, WinWay, Chroma ATE.

Google Weighs Amkor Participation to Address TPU CoWoS-S Bottlenecks

Google DeepMind's latest AI model, Gemini 3, has made a stunning debut, outperforming ChatGPT, Claude, and other competitors, signaling a new phase in the generative AI landscape. This has drawn attention to the Google-developed TPU chips that train this model, which have also attracted interest from other US-based cloud service providers (CSPs).

The seventh-generation TPU chip, Ironwood, is designed by Broadcom and manufactured using TSMC's 3nm advanced process, paired with CoWoS-S advanced packaging technology. Mass production began in the third quarter of 2025, and it is expected to become the main Google ASIC shipment in 2026.

Due to the continued tight supply of TSMC's CoWoS advanced packaging capacity in 2026, some orders are expected to overflow to US-based OSAT company Amkor, which will enter the Google TPU supply chain using a "CoWoS-S-like" technology.

Taiwanese OSAT firms join Google TPU testing
In Taiwan's packaging and testing supply chain, ASE Technology Holding and King Yuan Electronics (KYEC) are reported to begin handling Google TPU wafers outsourced to TSMC for chip probing, as well as final testing and system-level testing orders. ASE and KYEC will focus on front-end and back-end testing, respectively, and are expected to see significant revenue contributions in the second half of 2026.

To meet the demand for advanced testing of AI GPUs and AI ASICs, ASE and KYEC have increased their 2025 capital expenditures, continuing to purchase wafer testing machines from Japan's Advantest and US-based Teradyne. Taiwanese companies Hon Precision and Chroma ATE are key beneficiaries as suppliers of back-end product testing and system-level test equipment.

Probe cards and sockets gain traction
Regarding the testing interface, Google sources wafer test probe cards mainly from MPI Corporation and Italy's Technoprobe. MPI not only secured TPU orders but also entered the Axion CPU supply chain. MPI is Taiwan's leading probe card manufacturer, which uses microelectromechanical probe card technology to lead competitors in 3nm advanced testing. Through strong co-development with customers, it has surpassed Technoprobe and US-based FormFactor, becoming the main probe card supplier for CSPs' AI ASIC chips, with a market share of 60% to 80%.

WinWay Technology is the world's largest test socket supplier, and its high-end test socket products have reportedly been adopted in the Google TPU supply chain, with strong AI ASIC demand expected in 2026. For advanced nodes below 7nm, WinWay's revenue share has reached nearly 80%, with about 40% coming from AI GPU and AI ASIC contributions.

Leading load board manufacturer Chroma has also revealed that it is expected to enter the Google TPU supply chain. Analysis suggests that with MediaTek securing IC design service orders for 3nm v7e and 2nm v8e, Chroma is well-positioned to become a supplier of wafer and final product test load boards. The company has previously confirmed that its large-sized test load board products have achieved recognized technology and yield levels from major US-based CSP clients, indicating promising contributions in the second half of 2026.

Growing TPU demand
In addition to Google's original cloud service and Gemini computing demands, Anthropic will adopt TPU as a computing resource starting in 2026, and Apple recently announced plans to integrate the Gemini model into its Siri voice assistant, further boosting demand for Google TPU chips. DIGITIMES Research estimates that TPU shipments will reach 3.325 million units in 2026, nearly 1 million more than in 2025. Despite strong competition from AWS's Trainium camp, Google is expected to maintain its leading position in ASIC chip shipments.

$AMKR

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https://t.co/8pRKUqFMOW


ASE and KYEC will focus on front-end and back-end testing, respectively, and are expected to see significant revenue contributions in the second half of 2026

ASE Technology Holding US ADR ticker ASX


MPI not only secured TPU orders but also entered the Axion CPU supply chain

MPI Corporation 6670.TW Taiwan probe card/test


WinWay Technology listed on TWSE as 6515.TW


Chroma is well-positioned to become a supplier of wafer and final product test load boards... indicating promising contributions in the second half of 2026

industry='Scientific & Technical Instruments'


Summary: Broad-based DRAM shortage driving 30–50% price increases in Q4 2025–Q1 2026; bullish for Korean and US DRAM makers.

Korea DRAM sector: Samsung Electronics + SK Hynix

Due to shortages in legacy memory supply, Korean and U.S. DRAM manufacturers have decided to suspend new price quotations for enterprise customers for one week.
According to supply chain sources, DRAM prices in the fourth quarter are expected to rise by more than 30%, with some specifications likely to exceed a 50% increase, further accelerating the simultaneous price surge of DDR3.

Veteran analysts in the memory industry note that this rally is not limited to “specific specifications” but rather a broad-based shortage that has triggered an overall price adjustment.
Starting in the fourth quarter, DDR4 contract prices are expected to rise further by an average of 30–50%, with the most likely period of increase occurring between Q4 2025 and Q1 2026.

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https://t.co/6CQlGzZPXi


Korean and U.S. DRAM manufacturers have decided to suspend new price quotations for enterprise customers for one week


Summary: GE Vernova, Siemens Energy, MHI entering a golden era on AI-driven gas turbine demand; specialty alloy maker ATI also benefits from tight upstream supply.

AI-Driven Power Demand Surge in the U.S. Brings Gas Turbines to the Forefront: How GE Vernova, Siemens Energy, and Mitsubishi Heavy Industries Are Responding

The U.S. “power crunch” triggered by AI data centers has thrust the traditional industrial equipment — medium and large gas turbines (heavy gas turbines) — into the center of a new technological revolution.

Market demand is surging at a breakneck pace, and the three giants of gas turbine manufacturing — GE Vernova, Siemens Energy, and Mitsubishi Heavy Industries (MHI) — are entering a golden era, with orders and prices rising in tandem.

However, despite this overwhelming order volume, the three companies have not opted for full-scale capacity expansion.

The reason: the ghost of the early-2000s dot-com bubble collapse, which devastated the power industry, still lingers.

Balancing historical lessons with present profit opportunities, all three firms have chosen a strategy of “limited expansion.”

----------------------------------------------

1. From a “Compute Race” to a “Power Race”: Explosive Demand and Policy Catch-Up

The essence of the AI race is competition in computing power, which fundamentally depends on massive electricity supply.

As a result, power demand for AI data centers is skyrocketing at an unprecedented rate. Gas turbines have emerged as the backbone of the U.S. power grid, prized for their high efficiency, operational flexibility, and lower emissions compared with coal.

The market response has been swift and intense. According to research firm Oxcap, since mid-2023, the cost of building new gas power plants has more than doubled, primarily due to soaring gas turbine prices.

Power utilities and Big Tech firms have already booked orders through the late 2030s to secure future energy reliability.

Beyond AI, manufacturing reshoring, the expansion of electric vehicles, and the broad industrial electrification trend are all pushing electricity demand higher.

Policy support has reinforced this momentum. The Trump administration has designated gas turbines as a “bridge solution” to fill the power gap until next-generation nuclear plants come online.

At the same time, cuts to clean-energy subsidies have weakened the outlook for renewables, further increasing reliance on natural gas.

Media analyses show that following the passage of the “One Big Beautiful Bill Act,” forecasts for new wind, solar, and battery capacity over the next five years were revised down by 23%, which in turn stimulated demand for gas-fired generation.

2. Lessons from History: The “Ghost” of the 2000s Dot-Com Bubble

Despite the current boom, all three manufacturers are taking an extremely cautious approach to expansion.

The reason lies in the industry’s strong cyclicality and the trauma of the early-2000s gas turbine collapse.

Christian Bruch, CEO of Siemens Energy, stated:
“This industry is inherently cyclical. Even today’s boom will eventually end.”

In the early 2000s, the Internet boom led to overestimation of electricity demand, triggering a debt-fueled gas power plant construction frenzy.

After the bubble burst, major utilities such as Calpine went bankrupt, and turbine makers were left with severe overcapacity.

Bill Newsom, CEO of Mitsubishi Power Americas, summed up his company’s biggest concern:
“Our greatest challenge is distinguishing how much of the current demand is real — and how much is an illusion.”

According to Ryan Luther, Transition Director at Enverus,
“If everyone restrains expansion, prices will hold. But if even one player overbuilds, the entire market could collapse.”

3. The Strategy of “Limited Expansion”

Caught between historical caution and immediate opportunity, the three giants have chosen partial and gradual expansion:

• GE Vernova is investing over $300 million to increase its annual production of medium- and large-scale gas turbines from 55 to 80 units.

• Siemens Energy is pursuing a 30–40% capacity expansion but has explicitly ruled out making high-risk bets on the 2030s market.

• Mitsubishi Heavy Industries is committing hundreds of millions of dollars to expand production lines within the U.S.

Artem Abramov, Vice President at Rystad Energy, noted:
“Their ramp-up pace is dramatically slower than the surge in demand over the past two years. That shows just how determined they are to avoid overpromising.”
The bottleneck is no longer limited to assembly plants — it is now extending upstream.

The supply of special alloys, critical materials for gas turbine components, has become extremely tight.

Kimberly Fields, CEO of specialty alloy manufacturer ATI, commented:

“Last year, one major turbine maker agreed to co-invest with us in a new plant. It’s all about securing material supply. For these companies, the real risk isn’t price — it’s whether they can get the materials at all.”

Ultimately, as AI ignites a new “power race,” one of the oldest technologies in modern energy has stepped back into the spotlight.

But standing at the center of it all, GE Vernova, Siemens Energy, and Mitsubishi Heavy Industries are haunted by the lessons of two decades ago — and have made a cold, calculated choice:

“This time, we won’t overreach.”

---

https://t.co/lSaAcduzlE


Siemens Energy listed on Frankfurt exchange as ENR.DE


Mitsubishi Heavy Industries 7011.T Japan


one major turbine maker agreed to co-invest with us in a new plant. It's all about securing material supply


Summary: Citi raises NVDA FY2027 revenue estimate to $269B (+19%), lifts FY2027 GPU unit shipments to 10.2M on rising CoWoS supply for Blackwell/Rubin.

Citi AI GPU Model
As data points increasingly suggest rising CoWoS supply for Blackwell and Rubin, we revise our GPU unit sales estimates (see memo by Citi TSMC analyst Laura Chen).

1. Units: We maintain FY2026 unit shipments at 7.1 million, but raise FY2027 unit shipments to 10.2 million (up 44% YoY versus the prior 8.7 million forecast).

2. Blackwell & Rubin: Between calendar 2025 and 2026, we expect combined Blackwell and Rubin unit shipments to increase from 14.2 million to 16.2 million.

3. Revenue outlook: Supported by higher unit shipments and a favorable product mix, we estimate FY2027 revenue to reach USD 269 billion (a 19% upward revision from the prior USD 225 billion estimate).

4. Rationale for the revision: The USD 44 billion upward adjustment to GPU revenue mainly reflects changes to our assumptions for total NVIDIA unit shipments, as well as the larger integrated scale of Blackwell and Rubin. For the 2025–2026 period, we update our combined Blackwell and Rubin revenue estimate from USD 358 billion to USD 417 billion (+16%).

5. Revenue mix: We expect AI GPU revenue to account for the high-80s to 90% of NVIDIA’s total data center revenue in FY2026–2027, with the remainder coming mainly from networking (Ethernet and InfiniBand), standalone CPUs, and software/services.

$NVDA


maintains its 'Buy' rating on SK hynix, raising the target price to KRW 590,000

Summary: UBS raises DRAM/NAND price forecasts; upgrades Samsung to Buy PT KRW 112K, maintains Buy on SK Hynix PT KRW 590K, reinstates Buy on Nanya PT TWD 110 on demand surge through H1 2026.

UBS: DDR and NAND Prices Significantly Raised, SK hynix and Samsung to Benefit the Most
UBS (T. Arcuri, Oct 20, 2025)

UBS raised its forecast for DDR and NAND contract prices, expecting DRAM prices to continue rising from Q4 2025 through the first half of 2026: DDR contract prices are projected to increase by +17% QoQ in Q4 2025, +15% in Q1 2026, and +7% in Q2 2026; NAND contract prices are expected to rise by +15%, +10%, and +5%, respectively.
According to institutional surveys, the top four U.S. cloud providers’ DDR demand in 2026 will double compared to 2025, while some smartphone customers’ demand is also expected to grow by about 20%. Supply and demand for enterprise SSDs are likewise tightening. UBS raised its forecast for 2026 server shipments to 18 million units (+5.7% YoY). DRAM end demand is expected to grow by 20.6% and 19.1% in 2025 and 2026, respectively—significantly outpacing supply growth—leading to an estimated supply-demand gap of around 3 percentage points.

Against this backdrop, UBS raised its capital expenditure forecasts for SK hynix to KRW 28/35/36 trillion for 2025/26/27 (previously 25/31/32 trillion) and believes DRAM makers will struggle to achieve over 20% capacity growth. The firm maintains its “Buy” rating on SK hynix, raising the target price to KRW 590,000; upgrades Samsung Electronics to “Buy” with a target price of KRW 112,000; and reinstates coverage on Nanya Technology with a “Buy” rating and a target price of TWD 110.


upgrades Samsung Electronics to 'Buy' with a target price of KRW 112,000


reinstates coverage on Nanya Technology with a 'Buy' rating and a target price of TWD 110

Nanya Technology Corp listed on TWSE as 2408.TW


Summary: Buy Oracle as a 3× levered play on OpenAI's dominance of the future.

This is an absolutely insane scale.

If you believe OpenAI will dominate the future, buy Oracle.

Oracle is essentially a 3× levered play on OpenAI. https://t.co/4EeKrPkIJs


Summary: BofA bullish on memory sector: DRAM/NAND price hikes continue into 2026, HBM4 ramp on track at Hynix, Samsung 1c node mostly for HBM4; spot price strength to persist into December.

Global DRAM memory basket: Micron, SK Hynix, Samsung

BofA Simon Woo) Global Memory Tech

What we learned this week: higher ASP but lower volume
We checked memory chipmakers’ pricing strategies vs OEMs’ reactions. Key takeaways: (1) conventional DRAM supply cut to OEM customers that do not accept double-digit% price hike (vs 3Q) QTD; (2) newly growing HBM orders with more favorable 2026 contract price (minimal price cut for HBM3e, 20%+ price premium for HBM4); (3) most Tier 1 OEMs still declined 30%+ DRAM contract price hike – broadly accepted 10-20% (vs 20- 30%+ among Tier 2/white-box OEMs); (4) commodity NAND contract price hike not yet as much as for DRAM – just 10-15% (high-end eSSD: still sub-10%) vs 3Q; and (5) minimal bit growth for most memory chipmakers (normal: 10%+/-) coupled with Tier 1 OEMs’ resistance to chip price hike. Overall, chipmakers are less interested in selling DRAM and NAND in 4Q assuming further price hike in 2026 and below-trend production volume increase (conventional DRAM: sub-10%; overall NAND: 15%+/-). That said, most OEMs seem to be asking for only high-single digit% contract price hike for 1Q. We now assume ex-HBM DRAM ASP at +22%/+7% QoQ for 4Q25/1Q26, to be conservative.

FAQs: Google TPU, Samsung, Hynix, China local memory
Some investors have raised concerns about Google’s more powerful TPU (consequently lower HBM demand from NVIDIA), Samsung Electronics’ more aggressive 1c node capacity expansion or HBM4 ramp-up (negative impact on SK Hynix), Hynix’s HBM4 redesign/ quality issue, and China’s local DRAM/NAND capacity expansion. Net-net, we do not see any negative implications (of Google, Samsung, Hynix, and even China memory) but assume positive impacts: Google’s new TPU v7 – HBM3e contents increased strongly from 64GB HBM3 (v6) to 192GB, even 9,216 units of v7 can be connected (like NVIDA’s NVL 144/192), Google continues using NVIDIA’s GPUs (mainly for high-end training) besides in-house TPUs (inferencing or also training); Samsung – 1c node DRAM ramp-up is mostly for HBM4 (minimal for conventional DRAM); this presents potential shortage of high-end LPDDR5 or GDDR7 (mostly 1b node for Samsung); Hynix – HBM4 actual sales already recorded (4Q) and production ramp-up on track; and China memory capacity – already large accounting for 10%+ of global DRAM and NAND, but actual chip production volume still low due to yield/quality issues (just low-single-digit% of global total, in our view).

December spot price outlook
Almost all memory chipmakers and OEMs said current DRAM spot prices for 16Gb DDR4 (US$42; up again 10%+ this week, or 13x up YTD) and 16Gb DDR5 (US$27; also up 10% WoW) are abnormally high vs sub-US$10 contract prices on average (even 16Gb-equivalent HBM ASP is still sub-US$30). We also believe current DRAM spot price is based on speculative trading (buying the chip expecting higher selling price for the following month). Since all DRAM makers allude to near-term supply cut expecting higher 2026 contract price, at least spot-price strength will likely continue into Dec.


Hynix – HBM4 actual sales already recorded (4Q) and production ramp-up on track


Samsung – 1c node DRAM ramp-up is mostly for HBM4 (minimal for conventional DRAM); this presents potential shortage of high-end LPDDR5 or GDDR7


AI chip demand remains far stronger than expected three months ago, and the overall demand momentum continues. The outlook for 2026 is positive, with AI and high-performance computing demand expected to be the key growth drivers.

Summary: TSMC CEO: AI demand stronger than expected, 2nm mass production Q4, CoWoS capacity expansion 2026, positive 2026 outlook — bullish read for TSMC.

TSMC CEO remarks

• Mass production of the 2nm process is scheduled to begin in the latter part of Q4.

• The A16 node will enter mass production in the second half of next year.

• AI chip demand remains far stronger than expected three months ago, and the overall demand momentum continues.

• Regarding CAPEX, he stated that “it’s unlikely to suddenly decrease in any given year,” reaffirming TSMC’s commitment to maintaining a high level of investment for the coming years.

• The company is making full-scale efforts to expand CoWoS advanced packaging capacity by 2026.

• Current AI-related packaging and production capacity remains extremely tight, and the supply shortage persists.

• The outlook for 2026 is positive, with AI and high-performance computing demand expected to be the key growth drivers.

$TSM $NVDA


Summary: Memory supercycle imminent; bullish on the sector based on tightening fab discipline analogous to 2017 peak cycle.

Memory sector basket: Micron, SK Hynix, Samsung

Let’s look back at the peak of the memory cycle in 2017.

At that time, engineers at Samsung and SK Hynix had to write formal reports to their superiors if they made even a single mistake on a wafer that resulted in a defect or scrap. Every single chip immediately translated into money once it reached the market.

Today, things aren’t quite as strict about each wafer as they were back then. But, as some say, “it might soon return to that state.”

The memory supercycle is coming…


저는 중국 테크 하나만 보유하라면 알리바바 ADR 선호합니다

Summary: Long Alibaba ADR as top China tech pick: strongest domestic AI model (Qwen), multiple AI-monetizable platforms, in-house chip biz, growing Western adoption of Qwen.

1. 중국내에서 가장 강력한 AI모델 보유 (저는 이게 일시적인게 아니라 Qwen이 앞으로도 꽤 발전할 것 같다는 생각이 들어요.)

2. AI로 수익을 내기 좋은 플랫폼 다수 보유 (배달, 이커머스 등)

3. 자체 칩 비즈니스 보유해 추론용 칩 대응 가능

4. 점점 더 서방 소프트웨어 회사에서 알리바바 Qwen 모델 채택 늘어남.

등등...저는 중국 테크 하나만 보유하라면 알리바바 ADR 선호합니다.

@jukan05 알리바바... 저번에 QnA에서 홍콩증시 기업 중 제일 좋게 본다고 하셨던 걸로 기억하는데...

매력 포인트 몇 개 알려주실 수 있나요? 경청할게요! https://t.co/3F8EgHrAOY


Summary: BofA raises SK Hynix PT to 700,000 KRW; author shares/adopts the bullish call.

Bank of America raises its target price for SK Hynix to 700,000 KRW.


if customer demand proves accurate, TSMC's CoWoS capacity will be in short supply next year... capacity could expand further to 110–120k wafers per month

Summary: Shares bullish CoWoS supply-demand analysis: TSMC capacity tight into 2026, NVIDIA demand exceeds even expanded supply.

AI Supply Chain Tracking Report:

A major U.S. investment bank believes that if customer demand proves accurate, TSMC’s CoWoS capacity will be in short supply next year.
Last month, the bank already raised its estimate of 2026 capacity to 100k wafers per month. Observations show that the cleanroom space for Phase 1 of the P8A fab is already ready; if demand is confirmed, capacity could expand further to 110–120k wafers per month.

Regarding NVIDIA, even if TSMC allocates 50% of its CoWoS-L capacity to them next year, it would still fall short of NVIDIA’s total demand by about 20%.
The Rubin CPK (single-chip packaging with silicon capacitor, excluding HBM) will use CoWoS-S; Rubin CPX will also use CoWoS-S and will replace the B40.
Overall, NVIDIA’s CoWoS demand for next year is estimated at 590k CoWoS-L and 15k CoWoS-S units.

For other ASICs, it is reaffirmed that AWS T3 will see mass shipments in 3Q next year.
As for Meta’s M1A ASIC, the probability of MediaTek being the supplier has dropped to 25%, due to the higher technical difficulty of the new packaging design.

早安！10/9 外電綜合整理

- AI供應鏈追蹤報導：
美系大行認為如果客戶需求屬實，明年台積電CoWoS產能將呈現供不應求狀況。
上個月大行已上修明年產能至100k/月，現觀察P8A 廠第一期clean room 空間已準備好，若需求確定，將可擴增至 110～120k/月。

關於Nvidia，就算明年台積電提供 5成的CoWoS-L


NVIDIA's CoWoS demand for next year is estimated at 590k CoWoS-L and 15k CoWoS-S units


As long as Nvidia continues its stride forward, it is actually not easy for competitors to keep up. supply consistently falling short of demand, there is no reason for margins to come down.

Summary: Bullish semis through 2030 on AI-driven profit reallocation; NVDA structurally dominant, SK Hynix HBM winner, AMD CPU resurgence from agentic AI, Apple beneficiary of memory cost advantage.

Looking back at the semiconductor market in 2025, there were truly too many fascinating stories. The overarching theme was:

AI demand-driven valuation restructuring of semiconductor infrastructure + The rewriting of value distribution across the supply chain.

Starting in 2024, semiconductor infrastructure began rapidly devouring the profits of the entire IT industry. The share of semiconductor net profit (EPS) within the IT sector of the S&P 500 rose from less than 20% to 40% in just two years, and it is still in a state of accelerated ascent.

The overall forward-looking profit margin for semiconductors has risen from 25% in 2023 to 43% by November 2025, significantly surpassing the average profit margins of several internet giants. This confirms that semiconductor margins exceeding those of the internet sector will be the "New Normal." The profit distribution of the entire IT industry is flowing increasingly toward semiconductors.

It is worth noting that even during the semiconductor chip shortage of 2020–2022, when shortages were severe, semiconductor profit margins and their share of total IT profit distribution did not see such significant growth.

This is the first half of the story: The valuation system of semiconductor infrastructure is being reconstructed by AI demand; it no longer holds the subordinate infrastructure status it did during the Internet era.

The logic behind this phenomenon is the transformation of business models alongside technological characteristics:

In the Internet era, the network and compute costs for each request had extremely low marginal costs. Scaling effects were excellent, and the marginal cost of distribution was almost zero.

In the AI era, this "near-zero marginal distribution cost" characteristic favorable to scalability has encountered a fundamental and major challenge: Not only is training cost no longer a one-time expense but rather one that grows annually, but even for client-side AI inference requests, costs do not drop in sync with hardware compute deflation. This is because "inference scaling" has become a consensus, and vertical domains still require larger-scale flagship models to maintain competitiveness.

Previously, the biggest cost for internet companies was OPEX, specifically SDE labor costs. Now, for the first time in history, internet companies are burdened with balance sheets full of high depreciation costs, similar to semiconductor foundries. The business model is practically itching to shift slowly from "Traffic × Conversion Rate" to "Gross Profit per Token."

Simply put, the cost distribution shift from the Internet era to the AI era has added heavy hardware/compute CAPEX (MSFT 33%, Meta 38% in earnings reports) on top of the OPEX base. The winners of the previous era were Internet companies + CSPs + SaaS (the "rent-collecting" industries). In the AI era, compute (semiconductor/chip depreciation) has become the new rent-collecting industry. The profit distribution of the entire IT industry has undergone a drastic reallocation (EPS flow to semiconductors rising from 20% to 40% and climbing). This is the most important reason for the restructuring of the semiconductor infrastructure valuation system.

--------------- How long can the "New Normal" of high semiconductor margins last?

The current high premiums come from an excessive backlog of semiconductor orders caused by an earlier "cost-is-no-object" arms race. However, obviously, hyperscalers do not want to be taken for a ride; they are all attempting to build in-house ASICs to lower costs. We can look at this problem from the perspective of the long-term compute distribution in 2030.

In the long run, OpenAI has already revealed the "standard answer": 10GW Nvidia, 10GW ASIC, 6GW AMD. Other hyperscalers have similar considerations for their split.

For example, on the inference side, they hope for ASIC >50%. Within the GPU segment, a 50/50 split between AMD and NV (legacy). For training, NV will still hold the lion's share (60%+), with the rest split between in-house ASICs and AMD.

Calculated based on a 2030 split of 60% inference and 40% training, the market share comes out to NV 38%, ASIC 39%, and AMD 23%. This is almost entirely consistent with OpenAI’s ratios and can be considered a standard reference value.

Of course, for Microsoft, Amazon, Google, and Anthropic, the AMD ratio will be noticeably lower than this standard answer/reference value, while xAI has no ASICs and uses only Nvidia + a small amount of AMD.

AMD's risk lies in the ultra-long term (post-2030). As CSP in-house ASICs become more mature (except for Microsoft), the proportion of ASICs in inference may grow higher, making it hard to find incentives to buy large quantities of new GPUs unless they are sold cheaply enough.

What about the recently hyped TPU? Is Meta shifting to TPUs? Will it significantly impact Nvidia’s margins?

Actually, Meta’s CAPEX is $72B this year, $110B next year, and the average annual CAPEX over the next six years may reach around $160B. Meanwhile, Meta’s 6-year $10B TPU order amounts to only $1.6B per year on average—and they are purchasing TPU cloud services, not bare TPUs.

In other words, this TPU order accounts for only 1% of Meta’s future 6-year CAPEX. They are not seriously considering large-scale deployment; it is likely just a means to bargain with Nvidia.

Furthermore, looking at Meta’s recruitment ads over the recent months, we don’t see any hiring for TPU engineers, unlike Anthropic, which was hiring a bunch of TPU kernel engineers back in May before announcing large-scale TPU procurement for training in October.

So, whether the reason is diversifying suppliers, creating a fallback for delayed in-house ASICs, or delays with AMD’s MI350X, Meta’s purchase of TPUs basically has one consideration: increasing bargaining power when buying Nvidia GPUs. However, they can essentially only bargain on the inference share; the actual effect is very limited, as is the impact on Nvidia’s profit margins.

Keep in mind that during the crypto bear market crash of 2022, NVDA inventory rose to 198 days, yet margins only retreated from 65% to 56%. Even with the "double kill" of PE and macroeconomics, the stock price only went from 300 to 100. Now, with supply consistently falling short of demand, there is no reason for margins to come down.

Additionally, the TPU v8 design is too conservative (it didn't use HBM4), and the TCO (Total Cost of Ownership) of the Kyber rack Rubin solution will be better than TPU v8. In the end, they will still have to rely on Nvidia, making it hard to bargain. As long as Nvidia continues its stride forward, it is actually not easy for competitors to keep up.

In summary, on one hand, bottlenecks across the entire supply chain (e.g., CoWoS expansion) are cautious, so the state of demand exceeding supply can last for many years.

On the other hand, there is a "temporal mismatch" between the profit curve of AI monetization and the hardware investment curve. The growth curve of the application side will lag by a few years. As long as this time lag between the application side and infrastructure side growth curves exists, semiconductors will continue to dominate profit distribution in the IT industry.

Looking at OpenAI’s investment curve through 2030, this mismatch will last until around 2030. This means the dominant position in IT industry profit distribution brought about by the semiconductor industry’s super-expansion phase will last at least until 2030 based on current views.

And high semiconductor margins might be sustained even longer, because the attribute has changed from "one-time infrastructure" in the internet era to "rent-collecting infrastructure" now.

AI has not only fed the GPU; it has used the compute budget to lift every link in the chain that "turns electricity into tokens"—from memory, storage, interconnects, and fiber optics, to electricity, energy storage, and so on.

The first half covered "Semiconductors swallowing IT profits." The second half covers how the "AI Compute Value Spillover Effect" reshapes the internal landscape of semiconductors: GPU Compute Growth -> Memory/Storage/Interconnect/CPU Bottlenecks -> Spillover Effect -> Structural Opportunities.

The more interesting story in 2025 is how huge industry dividends are creating structural new opportunities within the semiconductor sector. For instance, a super cluster requires several data center interconnects; fiber optic interconnect lengths reach the level of millions of miles. This is a new opportunity.

The most typical examples of new opportunities brought by structural trends in the semiconductor supply chain are Memory (DRAM/HBM) and Storage (SSD). The growth in HBM demand is so exaggerated that it is squeezing DDR4/5 capacity, leading the memory industry—historically known for its cyclical nature—to shout that "the cycle no longer exists." SK Hynix, leading in HBM, is even envisioning annual profits of $100 billion a few years from now, firmly becoming a trillion-dollar market cap company.

Behind these two sectors is a shift in structural trends: AI workloads are gradually extending from training to inference, and the proportion of inference is getting larger.

Inference is a purely memory-bound task; one could say bandwidth speed = tokens/s. As model sizes get larger and context lengths increase, the requirements for memory size also grow accordingly, leading to a surge in memory demand: Inference is Memory.

The memory on next-generation GPUs/ASICs has become an aesthetic of brute force. The sheer size of equipped memory is something unimaginable three years ago. Looking back, the 80GB of the H100 in 2022 looks like a toy; it has grown tenfold in just a few years:

- Nvidia Ultra Rubin - 1024GB HBM

- Qualcomm AI200 - 768GB LPDDR

- AMD MI400x - 432GB HBM

Another potential explosion point for memory is on the Edge, namely edge LLMs for phones/PCs/cars/robots. In the last two years, mainstream flagship phones have upgraded from 6GB to 8GB/12GB/16GB, preparing in advance for a possible edge LLM ecosystem. After all, next-gen phone compute will reach the 150 TOPS level—solidly desktop class and very powerful. In terms of potential, the edge memory upgrade is a larger market than the cloud memory increment. The number of edge terminal devices is staggering—billions annually. Once the edge LLM ecosystem thrives, doubling memory usage will be easy, and various designs for edge low-power memory/processing-in-memory will follow.
However, the software ecosystem for edge GenAI seems to lag significantly, progressing much slower than I imagined. This is likely because this area is still in a groping phase and does not have the clearly defined ROI of the cloud. Manufacturers are cautious with investments. When I was bullish on 2027 back in '23–'24, I may have been too optimistic.
Internet -> Mobile Internet took 10–15 years. Edge GenAI/LLM might also need 7–10 years. It may be that we have to wait until the cloud ROI is mostly exploited and marginal returns diminish before edge GenAI/LLM gets the development resources to validate the edge ROI.

Another story of internal structural shifts in semiconductors in 2025 is NAND storage, specifically enterprise eSSD.

The source of the structural trend is the same: the growing demand for AI inference workloads. The memory dividend has also spilled over into SSD storage, and even HDD storage, because when memory isn't enough, high-speed SSDs are used as multi-level caches. The main logic is KV cache offloading to the next layer of SSD storage during AI inference memory overflow, as well as vector database search/indexing—all increasing the demand for SSD storage.

Micron's earnings report put it precisely and bluntly: "AI inference use cases such as KV cache tiering and vector database search and indexing, are driving demand for performance storage."

As for why storage prices only exploded in the fourth quarter, one needs to distinguish between contract prices and spot prices. Contract price increases are milder; even for the scarcest enterprise eSSDs, contracts rose about 25% in Q4. But as NAND capacity was slowly eaten up by contracts in 2025, spot prices created a strong visual shock, rising over 50% in a single month.

Another unverified logic is the explosion of multimodal AI, especially the demand for AI images and AI video, which would exacerbate storage shortages. I feel this storyline is "promising for the future," but the current precision of video/images is perhaps not even at the GPT-3 level yet; achieving a breakout effect will still take some time.

------------------------ So, what are the next semiconductor structural opportunities brought by trend shifts?

We must look at what the trend for AI inference demand is next. Undoubtedly, the proportion of agentic flow will get larger and larger. 2025 is not just the "year of the agent," but the start of the "decade of the agent."

Viewing agentic workloads from a CPU perspective: routing and tool processing happen on the CPU. If you profile common agentic frameworks like SWE-Agent, LangChain, or Toolformer, the CPU can account for up to 90% of end-to-end latency. Throughput bottlenecks are also stuck more on the CPU, and CPU energy consumption can even exceed 40% of the total.

Agentic AI is currently more of a CPU bottleneck issue. In agentic frameworks, the CPU is the "Orchestrator" that is always busy. This will likely drive a new wave of recovery in CPU demand.

In AMD's Q2 2025 earnings report (August 5), Lisa Su explicitly stated this phenomenon: "In particular, adoption of agentic AI is creating additional demand for general-purpose compute infrastructure, as customers quickly realize that each token generated by a GPU triggers multiple CPU-intensive tasks."

In the Q3 report, Lisa played her hand again regarding CPU TAM increasing due to Gen AI: "Many customers are now planning substantially larger CPU build outs over the coming quarters to support increased demands from AI, serving as a powerful new catalyst for our server business."

Nvidia also views agent flow as a CPU demand. The CPU ratio in the GB200/300 architecture configurations is much larger than before—36 Grace CPUs : 72 Blackwell GPUs, reaching a 1:2 level. AMD's route involves using 1~4 256-core EPYCs to serve the MI400 series. Future hardware architectures for 72~128 GPUs will definitely develop towards optimizing agent workloads, such as agent task graph scheduling, load balancing, and CPU/GPU cooperative micro-batching.

Comparisons in compute power might eventually move away from the current pure GPU token rate comparison toward a whole-system full-stack agentic benchmark comparison.

-------------------------- While semiconductor structural shifts bring opportunities, the next steps may also bring unexpected secondary effects.

The explosion in cloud AI data center demand has caused memory and storage prices to skyrocket, putting immense pressure on costs for consumer electronics. In 2026, this may evolve into a potential Black Swan event for the consumer electronics industry.

The recent plunge in PC manufacturer stocks is due to this reason. HP has already stated it will reduce memory configurations, implying a return to the era of 8GB RAM + 256GB storage for PCs.

If DRAM memory and storage prices continue to rise like this, we might see a ridiculous situation: spot prices for memory/storage becoming more expensive than CPUs and GPUs. The awkward part is that this could directly delay the progress of AI PCs that consumer electronics hopes for, as large memory is more favorable for AI PC performance.

To exaggerate a bit: every employee of PC and mobile phone manufacturers, and even employees of consumer electronics manufacturers, should buy storage and memory stocks as a career risk hedge.

Starting early next year, memory and storage costs for the Android camp will become uncontainable. If Samsung and Xiaomi raise phone prices (prices in the US market have already risen significantly), the biggest beneficiary will be Apple.

Apple's memory and NAND capacities are locked in via exclusive long-term contracts at fixed prices. Incidentally, they also trapped Kioxia for a lot of non-increasing price capacity. This leads to Apple's cost advantage expanding further. Apple's growth in global mobile phone market share could be very significant; the coming period might be a glorious time for the iPhone.

The 2025 semiconductor market is truly full of wonderful stories. The grudges and relationships between Nvidia/AMD/TPU and various hyperscalers have caused the moods of onlookers placing their bets to fluctuate wildly.

HBM/Memory manufacturers ate the "memory-bound" dividends; NAND manufacturers unexpectedly harvested the spillover effects of KV cache; and CPUs, after nearly a decade of silence, may return to the center of the growth narrative due to agent orchestration.

It is no longer just Nvidia/Broadcom and a few compute vendors dominating. Rather, every evolution following the value spillover of AI workloads—from training to inference, from text to multimodal, from single model calls to agentic flow—is rewriting the value distribution of the industry chain.

The boom in Cloud AI is squeezing the living space of consumer electronics—while PC manufacturers are forced to discuss returning to the "8GB era," Apple sits back and reaps the benefits due to supply chain advantages. The secondary effects of this compute arms race may reshape the entire consumer electronics landscape in 2026 in unexpected ways.

The story of semiconductors is no longer a single thread, but a web that continuously reconstructs itself. And 2025 is likely just the first round of these alliances and rivalries.

回顾2025年半导体市场，真的是有太多太多精彩的故事，最大的主题就是:

AI需求驱动导致半导体基建的估值体系重构 + 产业链的价值分配重写

从2024年开始，半导体基建正在飞速吞噬整个IT产业利润，SP500里半导体净利润EPS在IT行业里占比，在两年时间从不到20%上升了到了40%，而且还在呈加速上升姿态 https://t.co/OAFOULgBFX


SK Hynix, leading in HBM, is even envisioning annual profits of $100 billion a few years from now, firmly becoming a trillion-dollar market cap company.


AMD's Q2 2025 earnings report (August 5), Lisa Su explicitly stated this phenomenon: adoption of agentic AI is creating additional demand for general-purpose compute infrastructure


Apple's memory and NAND capacities are locked in via exclusive long-term contracts at fixed prices. This leads to Apple's cost advantage expanding further. Apple's growth in global mobile phone market share could be very significant; the coming period might be a glorious time for the iPhone.


the dominant position in IT industry profit distribution brought about by the semiconductor industry's super-expansion phase will last at least until 2030 based on current views

US semiconductor sector proxied by SMH ETF


Summary: JPMorgan prefers SKH, Samsung, Tokyo Electron, Micron, KLA into 2026 on sustained memory up-cycle, HBM demand raised +15-21%, DRAM price upside risk, and disciplined CAPEX.

251114_Global Memory Market: Key considerations heading into 2026 and picturing bull/bear case scenarios - JPMorgan

[Key Takeaways]

(1) Whether the cycle can be sustained: We remain positive that the memory up-cycle will stay strong, supported by Token Economics
■ Every +1% increase in ASP adds an additional KRW 0.17–0.23 tn in operating profit

(2) Valuation: Given high margins and a long up-cycle, peak P/B of [2.6x] or higher is possible
■ However, a full transition into a P/E-driven regime will take some time

(3) HBM demand revision: We raise our 2026–2027 demand outlook by +15–21%
■ Rubin Ultra Pro, scheduled for launch in 2H27, will feature 4x the HBM content versus existing products

(4) SKH vs. SEC: SEC in the near term, SKH in the mid- to long-term
■ SKH is expected to maintain its NVIDIA-centric Tier 1 status with 50%+ wallet share

[Contents]

(1) We remain positive on a stronger and longer memory up-cycle driven by AI inference-based Token Economics in an environment where memory supply remains constrained

(2) Within Asian semiconductors, we prefer SK hynix / Samsung Electronics [memory] and Tokyo Electron [SPE]. In the U.S., we prefer Micron [memory] and KLA [SPE]

(3) In the near term, DRAM price momentum leans more towards upside risk

(4) D5 spot prices have surged +177% over the past month, with the spread widening to as much as 263%

(5) This implies further upside risk to our near-term DRAM contract price forecasts of +20% in 4Q25(F) and +10% in 1Q26(F)

(6) Increasing SSD-based purchasing demand and supply disruptions [yield deterioration related to QLC migration, longer lead times until utilization levels fully recover] are also making the NAND price outlook stronger

(7) We estimate that for every +1% ASP increase, the impact on SK hynix’s / Samsung’s earnings is roughly as follows:
■ DRAM OP: +KRW 0.17–0.26 tn
■ NAND OP: +KRW 0.07–0.09 tn

(8) Margins are returning to historical peak levels, and narrowing the demand-supply gap will be the key topic going forward

(9) For legacy DRAM in particular, the likelihood of reaching 70% OPM by 4Q25(F) is gradually increasing

(10) If additional margin expansion continues into 1Q26(F), the memory industry will enter a new margin phase

(11) Investor reactions are likely to be very mixed

(12) Some will positively view high margins as evidence of a strong up-cycle, while others will question the sustainability of margins and the slowing pace of EPS upgrades

(13) SK Group Chairman Chey Tae-won mentioned at the SK AI Summit that the top priority for memory makers going forward is to resolve supply-demand imbalances without causing oversupply

(14) We judge that the sustainability of the up-cycle itself is more important for share prices than the exact peak level of margins or absolute earnings size

(15) While memory makers’ CAPEX is increasing, we confirm that “discipline” is being maintained from several angles

(16) Versus the combined SKH+SEC CAPEX growth of +50% in 2017, we expect 2026 CAPEX growth to be around +20%

(17) We also believe most of this will be focused on advanced node shrink and on building new fabs scheduled to start operations in 2027
■ SEC: Pyeongtaek P4-2 / P4-4 → ±200k wpm on a 1znm basis, 120k wpm on a 1cnm basis
■ SKH: First phase of Yongin → Equivalent to six M15X-class fabs, 360k+ wpm on a 1cnm basis

(18) Meanwhile, under Token Economics, the role of memory continues to be highlighted

(19) As LLM parameter counts keep expanding from billions to trillions, higher-bandwidth HBM is required to load the models into systems

(20) The AI inference process itself demands high-speed read/write operations and higher memory usage in the pre-fill and decode stages

(21) Since GPUs are extremely expensive resources, they cannot be allowed to process only a single user query at a time

(22) Therefore, improving efficiency — especially by off-loading some operations to other types of memory — is essential, and this has become even more important now that AI has entered an inference-centric era

(23) As a result, hardware architects are allocating more compute resources to test-time compute, and the share of conventional DRAM consumption versus HBM is rising significantly

(24) In particular, the Vera Rubin architecture has 2.4–6.0x higher dependence on conventional DRAM compared with Grace Blackwell

(25) Most CSPs simultaneously run various AI inference and AI agent workloads and operate their businesses based on token pricing models

(26) In this context, resolving data transfer bottlenecks — which are key to token generation — is of utmost importance

(27) Even though memory TCO has more than doubled, CSPs continue to invest in these computing architectures, which is the fundamental reason server memory demand remains structurally strong

(28) We also revise up our HBM demand outlook

(29) Since our CoWoS outlook update, we have raised our 2026–2027 HBM bit demand forecast by +15–21%

(30) This is because we believe HBM supply shortages will deepen over the next two years

(31) This is inevitable given the increase in HBM content on GPUs such as Rubin and the significant upward revision in ASIC shipment forecasts
■ Rubin Ultra Pro, scheduled for launch in mid-2027 → 4x HBM content versus existing products

(32) Accordingly, we also see room for HBM3E discounts to narrow

(33) GPU vs. ASIC: ASIC mix rising on stronger TPU volumes
■ NVIDIA GPU shipments: ’26 6.3 mn → 7.2 mn / ’27 6.3 mn → 7.3 mn
■ ASIC cnfgkfid: ’26 6.0 mn → 6.5 mn / ’27 6.8 mn → 8.7 mn

(34) As TPU volumes are revised up significantly, ASIC bit-demand mix is projected to rise from 22% in 25(F) to 32–33% in 26–27(F)

(35) However, since most ASICs adopt HBM3E rather than HBM4/HBM4E, we expect the ASIC share to fall again in 2028

(36) Meanwhile, Samsung Electronics is aggressively expanding 1cnm HBM production capacity at P4-1/P4-2 based on HBM4 demand from AMD and some NVIDIA products. As a result, Samsung’s market share is projected to rise from 25% this year to 30% next year

(37) Nevertheless, SK hynix is expected to maintain its Tier-1 vendor status in HBM with 50%+ wallet share, based on its strong partnership with NVIDIA

(38) The following is the recent P/E vs. P/B valuation framework

(39) The top three memory makers are currently trading at 2.6x P/B, near historical peak levels, with AI proliferation and expectations for an extended up-cycle raising the risk premium

(40) Considering high margins and a long cycle, applying a valuation above peak P/B can be justified

(41) However, for the valuation framework to shift firmly to a P/E-driven regime, industry-wide structural changes are needed, such as longer-term supply contracts, expansion of customized memory, and more stable margin structures

(42) There is still a gap between share-price expectations and fundamentals, so we judge it is premature to move to a P/E-centric valuation logic

(43) Lastly, on SEC vs. SKH, we prefer SKH from a mid- to long-term perspective

(44) After risk-off phases, SKH has shown stronger share-price elasticity, driven by the expansion of high-margin products built on its technological competitiveness

(45) From a short-term perspective into early 2026, however, SEC could outperform SKH on expectations of HBM share gains and narrowing margin gaps between the two

(46) From a mid-term perspective, SK hynix is better positioned. This is because it has robust technological leadership in HBM and is the furthest ahead in MR-MUF-based 16-high products


we prefer SK hynix / Samsung Electronics [memory]


we prefer SK hynix / Samsung Electronics [memory] and Tokyo Electron [SPE]


In the U.S., we prefer Micron [memory] and KLA [SPE]


The final tranche will only be issued once AMD's stock reaches $600. Based on projected quarterly earnings, this deal adds approximately $4.5 billion per quarter

Summary: Barclays raises AMD PT to $300; deal with OpenAI adds ~$4.5B/quarter by end-2026, warrant structure targets $600 stock price, +$1.30 EPS/quarter from 6GW deployment by 2030.

Barclays) Raises AMD Target Price to $300

This agreement is structured to be mutually beneficial for both OpenAI and AMD, but more directly, it aims to boost AMD’s share price. The unique aspect of this deal is that warrants (stock options) are issued in tranches tied both to stock price milestones and 1GW (gigawatt) deployment intervals. The final tranche will only be issued once AMD’s stock reaches $600.

Based on projected quarterly earnings, this deal adds approximately $4.5 billion per quarter to the previously expected $3 billion by the end of 2026. Assuming 6GW is gradually deployed by the end of 2030 (when the warrants expire), the incremental impact on EPS (Earnings Per Share) is about +$1.30 per quarter, bringing AMD’s total quarterly EPS to around $3.00.

We assume an annual deployment rate of about 1.2GW (6GW over 5 years), translating to roughly $18 billion in annual revenue (each GW corresponds to low double-digit billions in revenue, assumed at $15 billion per GW). We also estimate an additional 27 million diluted shares per year due to warrant issuance.

Finally, we expect 1GW to be deployed in H2 2026, potentially adding around $15 billion in incremental revenue next year.

$AMD


Summary: Samsung benefits from DDR5 shift; SK Hynix and Micron benefit from Samsung's HBM retreat; Winbond benefits from structural DRAM shortages and rising prices.

Samsung shifts focus from HBM to DDR5 modules for higher profits

Samsung Electronics has shifted its internal strategy in response to intensified HBM market competition, reallocating capacity toward DDR5 RDIMM modules and freeing up around 80,000 DRAM wafers monthly to yield stronger profits.

Soaring DDR5 prices outpace HBM margins
The official price of a 64GB RDIMM has risen from about US$265 in the third quarter of 2025 to US$450 in the fourth, nearly a 70% jump. DDR5 is now contributing more profit to Samsung than HBM3E, and future quarterly price increases could push modules toward US$500.

Samsung has been struggling to catch up to SK Hynix and Micron in HBM3E. Although its HBM3E finally passed Nvidia and US CSP certifications in the second half of 2025, market sources say Samsung has been slashing prices to expand HBM share. Its HBM3E ASP is roughly 30% lower than SK Hynix's, and further price cuts of up to 30% are expected starting in 2026.

Process migration frees capacity
Additionally, Samsung has reportedly decided to shift 30–40% of its DRAM capacity from the 1a process to next-generation 1b or 1c nodes, with 1c set to become the primary focus. Through this process transition, Samsung is expected to free up roughly 80,000 wafers per month and redirect them into general-purpose DRAM, including DDR5, LPDDR5X, LPDDR6, and GDDR7.

According to sources, Samsung's HBM3/HBM3E margins have fallen to around 30%, while prices for general DRAM have surged far beyond HBM profitability. Based on Samsung's fourth quarter 2025 price of US$450 for a 64GB RDIMM, gross margins exceed 75%. Prices are expected to rise to around US$480 in the first quarter of 2026. Although the pace of increase is slowing, spot market prices have already reached US$780, meaning Samsung could soon surpass US$500 per module.

However, Samsung has not secured a dominant position in HBM3E, leading to insufficient capacity utilization. This indicates that its cost structure and competitiveness still need improvement. While major DRAM makers are preparing for competition in 2026 regarding sixth-generation HBM4, HBM3E will remain the mainstream in terms of annual shipments, with HBM4 volume ramping only in the second half of 2026. Samsung's early capacity shift allows it to earn more from DDR5 without the yield loss associated with HBM production, benefiting overall operations.

This also means Samsung will concentrate resources on HBM4 and DDR5 RDIMMs in 2026, slowing its push to expand HBM market share. SK Hynix and Micron are expected to benefit, and other server customers seeking HBM may have to pay premiums to secure supply from those two vendors.

SK Hynix expands capacity as tight supply persists
On the other hand, SK Hynix has announced plans to expand general DRAM capacity. Unlike Samsung, which uses 1c for HBM3E, SK Hynix plans to use its 1c node mainly for DDR5, LPDDR5X, and GDDR7. Though the company has not revealed the scale of the expansion, market estimates indicate that capacity will grow from 20,000 wafers to 190,000 wafers by the end of 2026.

Even with new DRAM capacity, most of it will be absorbed immediately by the AI sector. Only server DDR5 supply may see minor relief, while PC and smartphone DRAM will remain tight through 2026. Electronics system makers without a server business will be effectively excluded from priority supplier lists, leading to rising PC and smartphone costs and likely weakening end-market demand.

Taiwanese memory suppliers see strong revenue growth
Taiwanese suppliers continue to benefit from structural shortages and price increases. Winbond's November 2025 consolidated revenue reached NT$8.629 billion (US$276.3 million). This was the highest in 41 months, up 4.9% month-on-month and 38.7% year-on-year. Cumulative revenue for the first eleven months of 2025 reached NT$79.635 billion, up about 5.85% from the same period in 2024.

Furthermore, memory module maker Team Group posted November 2025 revenue of NT$1.617 billion, up 46.76% from the previous month and 78.63% year-on-year. The company said its long-term cooperation with upstream suppliers has ensured sufficient future supply and safety stock, enabling timely deliveries. It will continue adjusting strategies and turnover efficiency based on market price trends.

---

https://t.co/7KlAPJ8Zo4


SK Hynix and Micron are expected to benefit, and other server customers seeking HBM may have to pay premiums to secure supply from those two vendors


Taiwanese suppliers continue to benefit from structural shortages and price increases

Winbond Electronics listed on TWSE as 2344.TW


I expect Korea to benefit from this trend. After all, we're already the world's second-largest battery producer, and we were manufacturing LCDs until just a few years ago.

Summary: Bullish Korean battery and LCD equipment sector as China restricts tech exports, driving Indian/Vietnamese buyers to Korean suppliers.

Korea battery/LCD equipment basket: Samsung SDI, LG Chem, LG Energy

Here’s one trend you probably don’t know about:

China is now heavily restricting the export of its own companies’ battery manufacturing and LCD display equipment to countries like Vietnam and India.

Beijing is deeply worried that its advanced industrial technologies could leak abroad.

As a result, many Indian and Vietnamese companies have recently been visiting South Korea.

In fact, not long ago, Tata Group, one of India’s largest conglomerates, came to Korea to conduct an on-site inspection to purchase Korean battery manufacturing equipment — reportedly worth several billion dollars.

I expect Korea to benefit from this trend. After all, we’re already the world’s second-largest battery producer, and we were manufacturing LCDs until just a few years ago.


Summary: Long Fujikura: 50%+ share in optical fiber fusion splicers makes it a major beneficiary of surging optical fiber demand; still attractive despite 255% run.

Fujikura Ltd 5803.T Japan cables/connectivity

I’ve been personally researching this company lately.
Given the surge in optical fiber demand, I believe Fujikura, which holds over 50% market share in the optical fiber fusion splicer market, will also benefit significantly.

---

It’s gone up 255% over the past six months, but I still think it’s an attractive stock. https://t.co/oQswwlw3fN


Summary: DRAM shortage intensifying; Samsung and SK Hynix expected to enjoy a supercycle in earnings through at least 2027 as long-term contracts lock in rising prices.

DRAM Shortage Worsens… Companies Shift from Monthly Contracts to “Bulk Purchases for Six Months”

As the global boom in artificial intelligence (AI) investment deepens the shortage of DRAM semiconductors, pricing negotiations that used to be conducted on a monthly or quarterly basis are being reorganized around long-term supply contracts of six months or more. With the severe DRAM supply shortage expected to drive price increases again next year, demand-side companies are actively agreeing to these semiannual contracts. As it has become difficult to secure even next year’s volumes, the market is now seeing discussions extend to supply contracts running through 2027.

An industry insider said on the 17th, “The DRAM market has shifted into a long-term contract-driven market,” adding, “We’re seeing buying demand that is even stronger than during the 2017 supercycle.” DRAM temporarily stores data so that central processing units (CPUs) or graphics processing units (GPUs) can process information quickly.

With the rise of large language model (LLM) AIs such as ChatGPT, the role of GPUs has grown, and to support them, memory semiconductors such as high bandwidth memory (HBM), which stacks DRAM in multiple layers, are facing chronic supply shortages. A representative example is the practice of global AI semiconductor leader Nvidia and other U.S. big tech companies pre-purchasing HBM from SK Hynix and Samsung Electronics through annual long-term contracts.

Recently, however, the shortage has spread beyond HBM to general-purpose DRAM as well. OpenAI, Meta, and others have announced AI infrastructure investment plans measured in hundreds of trillions of won, and as major corporations and governments worldwide build data centers for their own AI development, demand for general-purpose DRAM such as double data rate (DDR), graphics (G) DDR, and low-power (LP) DDR has surged. Although general-purpose DRAM delivers lower performance than HBM, it is nonetheless indispensable for AI inference and computation.

According to the industry, DRAM demand is rising sharply, particularly among companies in the United States and China. In particular, Samsung Electronics and SK Hynix are understood to be signing supply contracts for next year with major customers on a semiannual basis.

Typically, DRAM is supplied under monthly contracts in which the product is delivered at a fixed monthly price, and then adjusted later to reflect market prices. However, as DRAM demand has surged since the second half of this year, contract periods have been extended beyond quarterly to semiannual or longer-term supply agreements. This is because demand-side companies are not only offering prices above the prevailing market level but also seeking contracts that guarantee supply for more than half a year.

In reality, DRAM inventories in the market are diminishing rapidly. As of the end of the third quarter, finished goods inventories (“products and merchandise”) at Samsung Electronics’ Device Solutions (DS) division stood at 3.4043 trillion won, down 14.6% (580.4 billion won) from the previous quarter. SK Hynix’s inventories are also falling. In the third quarter, its “products and merchandise” inventories totaled 2.1522 trillion won, down 368.9 billion won compared with the end of last year.

Amid the DRAM shortage, the market is now seeing discussions around supply contracts extending out to 2027. SK Hynix has already completed its DRAM supply contracts for next year and is now negotiating supply for 2027. As SK Hynix’s DRAM has effectively sold out, global big tech companies and other customers are flocking to Samsung Electronics. However, most of the DRAM that Samsung plans to produce next year is also already under contract. With demand soaring, Samsung is even discussing plans to raise DRAM supply prices by more than 40%.

The industry expects that as the DRAM market shifts toward long-term supply contracts, Samsung Electronics and SK Hynix will enjoy a supercycle in earnings that lasts at least through 2027. When the proportion of long-term supply contracts increases, manufacturers find it easier to plan production, including unit costs and distribution, which in turn improves profitability. An industry official said, “As semiconductor contracts that used to be monthly or quarterly are renewed on a semiannual basis, prices are rising again,” adding, “Because long-term supply contracts through 2027 are being signed at prices higher than today, profitability will improve even further.”

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https://t.co/hcNZI3UCUB


Summary: Bearish Vertiv: market share loss or margin compression ahead despite staying in NVIDIA supply chain.

@kermankohli No, Vertiv will definitely remain in NVIDIA’s supply chain.
But I believe their market share will decline, or their margins will come under pressure.

@Jukanlosreve i guess it's good for a while but with this update does it mean that vertiv won't be able to cool nvidia's next gen gpus?


Top Picks: NVDA > AVGO > CRDO > AMD. Maintains an optimistic outlook on NVDA, AVGO, AMD, CRDO

Summary: Shares BofA bullish thesis: NVDA>AVGO>CRDO>AMD top picks; overweight AI compute, networking, optical, semicap; AI cycle structural not bubble.

Resilient Semiconductor Growth Cycle Amid ‘AI Infrastructure Bubble’ Debate (BofA)

⸻

1. Industry and Market Diagnosis
    • While the AI infrastructure buildout carries overinvestment risks, the current momentum remains fundamentally positive.
    • BofA identifies four indicators for a potential “AI bubble”:
① AI server utilization,
② Cloud CapEx plans,
③ Valuations of AI leaders,
④ Interest rate environment.
    • Maintains an optimistic outlook on NVDA, AVGO, AMD, CRDO, as well as semiconductor equipment, memory, optical communication, and foundry-related names.

⸻

2. Four Key Differences from the Dot-Com Bubble

1. No “Dark Fiber” effect – Unlike the IT bubble era’s overinvestment leading to low utilization, AI GPUs are running at full capacity, and OpenAI is projected to reach 1 billion users within three years.

2. Healthy CapEx funding – Based on operating cash flow, not debt-financed (CapEx/OCF ≈ 25% vs. >30% debt ratio in the past).

3. Interest rate trajectory – Unlike in 2000 or 2008, the U.S. Fed is more likely to enter a rate-cutting cycle.

4. Valuation levels – NVDA’s 2026E PER of 29× is reasonable compared with Cisco/Nortel’s 100×+ during the bubble era.

    • AI infrastructure expansion is naturally constrained by physical limits such as power, space, and cooling water, reducing overinvestment risks.
    • Of NVDA’s projected $3–4 trillion data center TAM by 2030, only 10–20% is expected to translate into actual revenue.
    • OpenAI’s 250 GW target by 2033 is viewed as unrealistically large, with power, space, and labor competition acting as growth limiters.

⸻

3. Geopolitical Risks
    • Despite renewed U.S.–China trade tensions, perceived risks are easing.
    • Rare earth supply: Taiwan’s non-China sourcing structure limits potential impact.
    • The threat of 100% tariffs is considered unlikely to materialize.

⸻

4. Conclusion and Implications
    • AI infrastructure investment remains structural expansion over speculative overheating.
    • Supply constraints (power, space) serve as natural stabilizers.
    • Valuations are reasonable, and interest rate / cash flow conditions are favorable.
    • Top Picks: NVDA > AVGO > CRDO > AMD.
    • Strategic Focus: Maintain overweight in AI Compute + Networking + Optical + Semicap-linked sectors.

$NVDA $AVGO $CRDO $AMD


Strategic Focus: Maintain overweight in AI Compute + Networking + Optical + Semicap-linked sectors

US semiconductor equipment sub-sector basket


The 2026 NVIDIA Rubin GPU unit forecast has been revised up to 3 million units (NVIDIA's total 2026 GPU procurement volume has been revised up to 7.5 million units)

Summary: UBS raises NVDA/AMD GPU forecasts, names SK Hynix biggest HBM beneficiary at 60-70% share with 13% ASP growth; Micron 24% and Samsung 15% NVIDIA HBM share.

UBS’s latest semiconductor supply chain update:

• The 2026 NVIDIA Rubin GPU unit forecast has been revised up to 3 million units (NVIDIA’s total 2026 GPU procurement volume has been revised up to 7.5 million units).

• The AMD MI450 unit forecast has been revised up.

• The AWS ASIC unit forecast has been slightly revised down.

• There is a possibility that Rubin’s initial ramp could be pulled forward.

 • The OpenAI ASIC forecast has been revised down (from 700,000 units to 500,000 units).

• Instead, the assumption for HBM3E has been revised from 8-Hi to 12-Hi.

• SK Hynix is expected to be the biggest beneficiary.

• Hynix has effectively passed qualification for NVIDIA Rubin’s HBMA4 and is expected to begin full-scale shipments from 2Q26.

• SK Hynix’s HBM4 share for NVIDIA in 2026 is projected to be around 70%, with its overall HBM market share expected to be around 60–70%.

• There is a possibility that HBM4 prices will carry about a 30% premium to HBM3E 12-Hi, and based on this, SK Hynix’s HBM ASP (average selling price) in 2026 is expected to grow about 13% YoY.

• Micron’s and Samsung’s 2026 HBM share for NVIDIA are projected at 24% and 15%, respectively.


The AMD MI450 unit forecast has been revised up


SK Hynix is expected to be the biggest beneficiary... SK Hynix's HBM4 share for NVIDIA in 2026 is projected to be around 70%, with its overall HBM market share expected to be around 60–70%


Micron's and Samsung's 2026 HBM share for NVIDIA are projected at 24% and 15%, respectively


Samsung's 2026 HBM share for NVIDIA are projected at... 15%


Morgan Stanley previously believed that the DRAM price rebound through summer 2025 was merely temporary… We now observe double-digit QoQ DRAM price increases occurring without meaningful demand recovery… we now see Micron's quarterly EPS reaching as high as $5 in the near term… raising our price target accordingly

Summary: Shares/endorses Morgan Stanley upgrade of MU to Overweight, PT $220, on structural DRAM supply tightness, revised HBM view, DDR5-HBM pricing linkage, and AI-premium re-rating.

Why We Changed Our View

⸻

1. Revising Our Underestimation of the DRAM Cycle

(1) Previous View

Morgan Stanley previously believed that the DRAM price rebound through summer 2025 was merely temporary and not a sign of structural strength, given weak demand across PCs, mobile, and servers.
Accordingly, we maintained a cautiously neutral (Equal-weight) stance on Micron, expecting only a limited recovery in industry conditions.

(2) What Changed

We now observe double-digit QoQ DRAM price increases occurring without meaningful demand recovery, driven purely by supply tightness.
This suggests a structural supply constraint, not a simple “inventory normalization” phase.

In short, the current price strength cannot be explained by traditional demand models — we recognize that we underestimated the impact of coordinated shipment control among suppliers.

⸻

2. Withdrawing Our Bearish View on HBM (Especially HBM4)

(1) Previous View

We believed Micron was technologically behind in meeting NVIDIA’s HBM4 speed requirement (>9.6Gbps), implying inevitable market share loss and margin pressure in the HBM segment.

(2) What Changed

We now correct that — Micron’s disadvantage has been overstated.

Although its HBM shipments are roughly one quarter behind SK hynix, technical maturity remains strong, and Micron is expected to maintain a low-20% market share in CY26.

While some yield loss may occur as Micron aligns with NVIDIA’s spec demands, this could actually tighten overall HBM supply, helping support industry-wide ASPs.

Moreover, the transition to TSMC base dies for HBM4E may serve as a structural advantage for Micron rather than a risk.

⸻

3. Newly Recognizing the Pricing Leverage Between DDR5 and HBM

In the past, we treated DRAM and HBM as separate markets.
Now, we emphasize that DDR5 price increases serve as direct leverage in HBM price negotiations.

This interlinkage — previously excluded from our models — limits potential downside in HBM pricing and supports gross margin stability.

In other words, the old narrative that “HBM cannibalizes DRAM” has been replaced with a new one: “DRAM sustains HBM.”

⸻

4. Acknowledging Upward Pressure on Earnings Estimates — “The Start of an EPS Revision Cycle”

Driven by recent sharp DDR5/DRAM price hikes and inventory drawdowns, we now see Micron’s quarterly EPS reaching as high as $5 in the near term.

Morgan Stanley noted, “We thought just last week…”, implying that even their own estimates from one week ago were overly conservative.
In short, we are correcting an underestimation of both the speed and magnitude of the price uptrend.

⸻

5. Reassessing Valuation — From “Conservative 10x” to “AI Premium 22x”

We have abandoned the previous framework that applied a 10x PER, based on the 2021 peak.
Instead, we now reflect structural growth drivers tied to AI, applying a through-cycle EPS of $10 × 22x multiple, raising our price target accordingly.

This is not a simple re-rating — it represents a fundamental paradigm shift, acknowledging that “AI memory deserves a valuation premium.”

⸻

6. Key Misjudgments We Corrected
    1. Viewed DRAM strength as temporary → Underestimated supply tightness and structural inventory drawdown.
    2. Overstated HBM4 competitiveness concerns → Misjudged Micron’s technological maturity and yield improvement pace.
    3. Ignored DRAM–HBM price interdependence → In reality, rising DDR5 prices strengthen HBM pricing power.
    4. Underestimated EPS elasticity → Micron’s profit ramp-up potential is much higher, even in the near term.

$MU

Micron: Rating Upgraded from Equal-weight → Overweight, Price Target Raised from $160 → $220 (Morgan Stanley)

    • DRAM and NAND prices are improving faster than expected, with buyers increasing inventories amid concerns over supply shortages through CY26.
    • Concerns