Summary: Shares Morgan Stanley's Positive ratings on Wistron, Foxconn, and Quanta on GB200/300 NVL72 rack shipment acceleration, doubling YoY in 2026.

>> Morgan Stanley: GB200/300 NVL72 Rack Shipments Accelerate in February; Positive on Wistron, Foxconn, Quanta (Taiwan Economic Daily)

• As AI server demand continues to expand, GB200/300 NVL72 rack shipments are rising rapidly. Morgan Stanley estimates total production of these racks reached approximately 6,500 units in February 2026, up roughly +6% MoM. Full-year 2026 shipments are projected at 70,000–80,000 units, more than doubling from approximately 29,000 units in 2025. Preferred ODM ranking: Wistron, Foxconn, Quanta Computer, in that order.

• By vendor, Foxconn led February rack shipments at approximately 2,400 units, followed by Wistron at 1,400–1,500 units and Quanta Computer at 1,300–1,400 units. However, some figures include Wistron's L10 compute trays converted into rack-equivalent counts, meaning actual end-customer delivery volumes may be somewhat lower.

• On the company outlook, Wistron has shipped a cumulative 2,400–2,500 units through December, putting it on track for 3,000+ units in Q1. Foxconn's March shipments are expected to exceed February levels, bringing Q1 total to approximately 8,500 units. Quanta saw February revenue decline MoM due to a drop in notebook shipments, but AI server shipments are normalizing, with Q1 rack shipments expected at approximately 4,500 units.

$NVDA

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https://t.co/Cea1WY5T4i


Hon Hai Precision (Foxconn) 2317.TW Taiwan


Quanta Computer listed on TWSE as 2382.TW


Summary: Bullish SNDK: 100% prepay long-term NAND contracts, surging AI demand, margins expanding from 29.9% to 41-43%, enterprise SSD prices up 25-40%.

structural marker; pre-classified as canonical yfinance ticker

Exclusive: SanDisk seeks prepaid cash deals for long-term HAND supply

SanDisk is approaching customers with proposals for long-term NAND flash supply contracts that require 100% cash prepayment, according to supply chain sources. Industry participants said the terms are without precedent, particularly as they require buyers to commit cash upfront at a time of rapidly rising prices and severe supply constraints.

Locking in supply amid surging AI demand
The proposal aims to lock in supply for as long as three years as demand for artificial intelligence servers continues to surge and growth in NAND bit output remains slow. While some large cloud service providers are reported to be considering the terms, supply chain sources said the requirement for full advance cash payment has drawn strong pushback from across the memory industry.

According to company statements, SanDisk expects the current supply-demand imbalance for its NAND products to persist through the end of 2026. The company has told investors that its manufacturing lines are operating at full utilization and that it is negotiating multi-quarter transactions with selected customers, including discussions that incorporate demand forecasts extending into 2027.

More recently, SanDisk has expanded its long-term contract proposals beyond cloud service providers to include customers in the PC, smartphone, and memory module sectors, sources said. The contracts would require buyers to commit to specific purchase volumes and provide full cash prepayments, with contract terms ranging from one to three years.

Industry participants said the key challenge for 2026 is no longer limited to contract price increases but stems from upstream suppliers conditioning shipment availability on cash-only payment terms. Such requirements are expected to place significant pressure on buyers' financial positions and cash flow, particularly as prices continue to climb.

Sources said severe NAND shortages have already triggered aggressive stockpiling across the market. Requiring full cash prepayment shifts future price risk and inventory responsibility entirely onto customers, while allowing suppliers to collect cash upfront and pursue investment or capacity expansion without bearing pricing or inventory risk.

AI demand drives margin expansion
Rising AI server demand has continued to push NAND prices sharply higher. For its fiscal first quarter of 2026, which ended on October 3, 2025, SanDisk reported revenue of approximately US$2.308 billion, up 21% from the prior quarter, with a gross margin of 29.9%.

Company statements indicate SanDisk expects revenue of between US$2.55 billion and US$2.65 billion for the October to December 2025 period, with gross margin forecast to rise to between 41% and 43%.

NAND flash prices began climbing rapidly in the fourth quarter of 2025. Sources said SanDisk issued multiple price increase notices during the year, with November 2025 contract prices rising by as much as 50%. Industry participants said the sharp increases prompted several memory module makers to temporarily suspend price quotations.

Pressure on downstream markets
Some cloud service providers are said to have agreed to long-term contracts with prepayment terms, reflecting their stronger financial resources. Sources cautioned, however, that server operators face rapidly expanding storage capacity requirements, raising questions over how much idle cash they can realistically allocate upfront.

Memory module makers face an even more difficult position, industry sources said. With the market firmly in a seller-driven phase, module suppliers have limited leverage to reject upstream terms. Providing hundreds of millions of dollars in upfront cash would be challenging, while borrowing to fund purchases could result in substantial interest costs.

Industry participants also warned that concentrating large sums with a single supplier could trigger reactions from other major NAND vendors, potentially prompting similar demands across the market. Locking into long-term contracts carries significant risk given uncertainty over future industry conditions, complicating capital allocation decisions and board-level risk management, they said.

As AI workloads increasingly shift from training to inference, demand for enterprise solid-state drives continues to rise sharply. Enterprise SSD contract prices increased between 5% and 8% in the third quarter of 2025, before jumping 25% to 30% in the fourth quarter, according to market participants. Industry sources said NAND wafer prices have risen even more sharply and expect enterprise SSD contract prices to climb a further 30% to 40% in the first quarter of 2026.

With suppliers prioritizing higher-margin enterprise products, capacity for consumer applications has been squeezed. Industry participants said higher NAND costs are forcing specification downgrades for PCs, smartphones, and other consumer devices. Retail demand is expected to weaken further, fueling concern over consumer market conditions in the second half of 2026.

$SNDK

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https://t.co/WE58YnB5Om


Summary: Shares UBS Buy on SK Hynix with PT Won1m; 82% DRAM OPM by 4Q26 on unprecedented memory upcycle.

Delta Force might actually storm the Blue House at this rate. Word is SK Hynix's operating profit margin just overtook Nvidia's. https://t.co/ZPi33NW5jC

UBS: SK Hynix

Significant profit uplift potential - PT to Won1m

We forecast 82% DRAM OPM by 4Q26
The memory semis industry is in the midst of an unprecedented upcycle. By 4Q26, we now forecast SK Hynix DDR ASPs to be a whisker away from the 3Q18 peak at US$0.97 per Gb. With an


Summary: Disclosed fresh long position in Hamamatsu Photonics.

@pre09576802 I bought Hamamatsu Photonics today.

@jukan05 @jukan05 After nvidia investment in photon/laser companies.  what do you think about below japan photon companies
Hamamatsu photonics
Santech holdings
QD Laser


Initiating coverage on Zhen Ding with a "Buy" rating and target price of NT$227

Summary: GF initiates Zhen Ding with Buy, PT NT$227 on Apple share gains, AI platform wins, and early CoWoP opportunity on NVIDIA Rubin; author shares/adopts the call.

Zhen Ding Technology listed on TWSE as 4935.TW

GF Overseas Electronics Communication Zhen Ding First Coverage: Undervalued Giant Embraces AI and CoWoP Opportunities

Initiating coverage on Zhen Ding with a “Buy” rating and target price of NT$227: We believe Zhen Ding’s core Apple business will benefit from higher market share in foldable devices and stable iPhone volume growth. More importantly, we are bullish on Zhen Ding’s AI potential, with expected share gains across multiple AI platforms. Additionally, NVIDIA’s CoWoP may launch earlier than expected, and with its mSAP+HDI capabilities, Zhen Ding is positioned to be one of the leading participants. We forecast Zhen Ding’s 2026 and 2027 EPS at NT$15.13 and NT$22.54, respectively. Our NT$227 target price is based on 15x FY2026E P/E. Zhen Ding has underperformed the Taiwan Weighted Index by 16.7% over the past three months; we view its current risk/reward as attractive.

CoWoP may launch ahead of schedule: We believe CoWoP could enter trial production as early as the Rubin platform, while the market expects late-2027/2028. The architecture places an mSAP PCB on top of two independent 7-layer HDI boards (using M9Q glass-based CCL), with the three boards connected via copper paste lamination technology. We see Zhen Ding as one of the leaders in CoWoP; its CoWoP solution has already been sent to OSATs for chip-level testing. We estimate CoWoP costs ~US$600 per GPU versus ~US$200 for a GB200 compute tray. Our scenario analysis suggests that, assuming 30% CoWoP adoption on the Rubin Ultra platform and 35% market share for Zhen Ding, CoWoP could add ~NT$1.8 to EPS by 2027.

Steady AI server market share gains: We expect Zhen Ding to make solid progress in AI market share, driven by: 1) NVIDIA compute tray scheduled for 1Q26 launch, with switch tray verification underway; 2) AWS UBB starting in 4Q25; 3) potential Google cooperation supported by the Hon Hai Group; and 4) 1.6T optical module PCBs. Zhen Ding’s aggressive NT$30 billion annual capex plan for 2025–2026 also strongly supports share gains. Including potential CoWoP growth, we forecast server and optical module PCB revenue of NT$21.7 billion in 2026 and NT$51.9 billion in 2027.

IC substrate upgrade cycle to continue: First, we believe CoWoP solutions will not cannibalize the ABF substrate business, as demand remains robust due to increasing chip size and layer count. Separately, we estimate ~75% of Zhen Ding’s ABF revenue comes from AI, with its Kaohsiung capacity largely locked in by AMD.

Driven by the memory supercycle, BT substrate utilization has recovered to above 95%. Due to Low-CTE shortages, we have observed price increases: BT substrates up 5% monthly since 3Q25, and ABF substrates up 10–15% in 4Q25. With favorable pricing and strong utilization, we expect the IC substrate business to return to profitability in 2026.


Lumentum (LITE Buy) … Both COHR and LITE continue to offer significant upside potential through 2027

Summary: Bullish LITE/COHR into 2027 on 800G/1.6T demand ramp; InP shortage near-term positive for AXTI and Sumitomo; Win Semi benefits from optical growth.

GF Overseas Electronics & Communication

AI Network: Short-term Disturbances Do Not Alter the Long-term Trend

Recent Supply Chain Concerns
Recently, due to China’s slower approval of export licenses to Taiwan and tighter export controls to Japan, AXT Inc. (AXTI) lowered its 4Q25 revenue guidance. This has heightened market concerns over the supply chain for related suppliers including AXTI (AXTI), Sumitomo Electric (5802 JP), Lumentum (LITE Buy), and Coherent (COHR Hold).

However, we believe inventories have already been built up in advance along the supply chain, and recent comments from hyperscalers continue to point to a constructive outlook for overseas optical module manufacturers through 2027. Therefore, we view the short-term supply chain impact as not altering the medium- to long-term trend. Both COHR and LITE continue to offer significant upside potential through 2027.

Stock Impact
LITE and COHR have corrected recently, primarily due to concerns over optical utilization rates, upstream material export controls, and some profit-taking after LITE’s 35–40x P/E had priced in near-term expectations.

Looking toward 2027, we remain bullish on robust growth in 800G and 1.6T demand. We are also positive on Google’s stance toward optical architectures, given its advantage in interconnect chip count relative to Nvidia, as well as the expected optical ramp-up from other hyperscalers. We believe upstream material supply concerns are already partially priced in.

Meanwhile, given the ongoing shortage of InP substrates, we expect short-term price increases that will benefit AXTI and Sumitomo. As highlighted in LITE’s latest earnings call, the laser supply gap continues to widen. We believe laser manufacturers such as Sumitomo are expanding capacity through external foundries, including Win Semiconductors (3105 TT). Win Semiconductors is also expected to benefit from incremental optical communication growth.

Strong Demand in 2027
We forecast total 800G/1.6T demand to reach 58 million / 64 million+ units in 2027, representing YoY growth of 40% / 213%+, primarily driven by:

1. Ramp-up in ASIC demand from Nvidia, Google, AWS, and others;

2. Continued increase in GPU/ASIC scale-out bandwidth, driving a higher proportion of GPUs/ASICs connected via optical modules;

3. Google’s full transition to large-scale clusters in 2026 and adoption of optical interconnects for scale-up.

Additionally, as noted in our previous report, scale-up CPO represents a pure incremental opportunity for the optical interconnect supply chain, benefiting FAU, laser, shuffle, and module vendors—including Lumentum, Sumitomo, and Browave.

$AXTI $LITE

---

@aleabitoreddit


Both COHR and LITE continue to offer significant upside potential through 2027

industry='Scientific & Technical Instruments'


we expect short-term price increases that will benefit AXTI and Sumitomo

industry='Semiconductor Equipment & Materials'


Sumitomo Electric Industries listed on TSE as 5802.T


Summary: KIS argues TurboQuant increases HBM demand (not decreases it); memory semis oversold on misread — bullish MU and SNDK.

[KIS — Chae Min-sook / Kim Yeon-jun] Semiconductor Industry Note: After TurboQuant and DeepSeek, the Conclusion is Clear

● TurboQuant's Opening Shot

On March 25 (local time), Google officially published the TurboQuant algorithm via its official blog, claiming it can compress KV Cache by up to 6x with no performance degradation. The market interpreted this as a reduction in memory requirements, causing memory semiconductor stocks to fall sharply. However, this reflects a misreading stemming from a confusion between the roles of memory capacity and memory bandwidth. The bottleneck in AI inference is not a shortage of memory capacity, but rather a problem determined by memory access speed and data movement efficiency. TurboQuant should instead be understood as a technology that partially alleviates this bottleneck and improves GPU efficiency, enabling more tokens to be processed per unit time with the same GPU resources.

● The Structure of AI Inference: Prefill and Decode

LLM inference consists of two stages: Prefill and Decode. The Prefill stage is a compute-intensive task where GPU computational power limits performance, while the Decode stage is a memory-intensive task where the speed of data movement determines performance. In Decode, the existing KV cache must be repeatedly referenced with each new token generated, making it structurally sensitive to memory bandwidth and access latency. Since the Decode stage largely determines the response speed that users experience, it sits at the heart of AI inference optimization.

● How TurboQuant Actually Works

When TurboQuant claims to compress KV Cache by up to 6x, this is less about reducing the required memory capacity itself and more about significantly lowering the data size occupied by the KV Cache and the resulting memory access burden. This means the volume of data that must be handled within the same HBM bandwidth is reduced. As a result, memory access latency is alleviated and the time GPUs spend waiting for data can decrease. Because KV Cache accesses occur repeatedly during the Decode stage of LLM inference, reducing data size has a direct impact on relieving the memory bottleneck. The proportion of time GPUs spend waiting for memory responses diminishes, and compute resources are utilized more efficiently. This improves actual GPU utilization rates and increases the number of tokens that can be processed per unit time (throughput) within the same hardware environment — which can also be interpreted as a reduction in cost per token.

● The Real Bottleneck in AI Inference: Bandwidth, Not Capacity

It appears the market interpreted TurboQuant as reducing memory capacity usage and therefore decreasing HBM demand. However, the core bottleneck in AI inference is not a shortage of memory capacity but rather the speed at which data is read from memory — i.e., memory bandwidth and access latency. Because GPU compute cores process data far faster than HBM can supply it, GPUs sit in a wait state while expecting data from memory. Industry research indicates that in the Decode stage, more than 50% of attention computation cycles are spent in a wait state due to memory access latency — meaning GPUs waste more than half their theoretical performance waiting for memory responses. According to research published by Google DeepMind in January 2026, Nvidia GPU 64-bit FLOPS grew approximately 80x between 2012 and 2022, while memory bandwidth grew only about 17x over the same period; this gap is expected to continue widening going forward (arXiv:2601.05047, forthcoming in IEEE Computer). TurboQuant will narrow the gap between GPU compute capability and memory bandwidth, increasing the number of tokens that can be processed per unit time on the same hardware. This lowers cost per token, encouraging broader AI usage, drawing in more services and users, and ultimately leading to an increase — not a decrease — in KV Cache consumption.

● A Bottleneck TurboQuant Cannot Solve: Inter-Chip Communication Latency

There is another bottleneck in AI inference that TurboQuant does nothing to address. Large models exceed the memory capacity of a single GPU and are therefore distributed across multiple GPUs. During the Decode stage, because the model is spread across multiple GPUs, intermediate computation results must be exchanged between GPUs with each token generated. These data transfers are small in size but occur at very high frequency, which can introduce inter-chip communication latency. To reduce this latency, a single GPU must be able to handle more parameters and KV Cache — which ultimately demands more HBM capacity per GPU. In the current AI environment, where model sizes and context lengths continue to expand, this need for greater HBM capacity will only intensify. The fact that Nvidia has consistently increased HBM capacity with each successive GPU generation is likely not unrelated to this dynamic.

● TurboQuant's Limitations: Still in Early Validation

While TurboQuant carries significant technical implications, there are also limitations in its scope of application and validation that deserve consideration. The published performance benchmarks are confined to relatively simple test environments centered on single-query information retrieval tasks such as LongBench and Needle-In-A-Haystack. Experiments were also conducted primarily on comparatively small models with around 8 billion parameters; whether the same effects can be reproduced in the large-scale models of hundreds of billions of parameters used in real-world industry settings has yet to be verified. More importantly, no validation has been conducted in the rapidly expanding Agentic AI environments. In these environments, models execute repeated multi-step judgments across longer contexts and more complex KV Cache structures, giving rise to memory usage patterns that differ entirely from those seen in single-response benchmarks.

$MU $SNDK


Raising Target Price to NT$2,325 ... we raise our 2026E/2027E EPS estimates by 11% and 17%, respectively. With a higher 25x valuation (up from 23x), we raise our target price from NT$1,930 to NT$2,325

Summary: GF raises TSMC Buy PT to NT$2,325 on AI cycle strength, capex beat, raised AI CAGR guidance, and higher EPS estimates for 2026-27.

GF Overseas Electronics Communication

TSMC (2330TT Buy): Strong Capex in an Unprecedented AI Cycle

Raising Target Price to NT$2,325
TSMC reported strong 4Q25 results, with full-year revenue guidance in line with expectations, while the capital expenditure guidance of US$52-56 billion far exceeded expectations. At the same time, TSMC raised its AI revenue CAGR guidance from mid-40% to mid/high-50%, which is the key focus for long-term investors. From a broader perspective, TSMC’s comments on the significant shortage of AI-related silicon supply indicate that the risk of an AI bubble is limited (at least until new capital expenditure is converted into actual capacity). For TSMC, we expect the unprecedented AI cycle to continue, with the company capturing an increasing share of value through N2/N3 capacity expansion and rapidly rising ASPs (driven by N2/A16 and advanced packaging). Taking into account the results, higher gross margins, and upgraded long-term CAGR guidance, we raise our 2026E/2027E EPS estimates by 11% and 17%, respectively. With a higher 25x valuation (up from 23x), we raise our target price from NT$1,930 to NT$2,325.

30% YoY growth guidance in line with expectations, but gross margin far exceeded expectations
4Q25 revenue was NT$1.046 trillion, up 6% QoQ and 20% YoY. Gross margin reached 62.3%, up 180 bps QoQ, mainly benefiting from NTD depreciation, higher utilization rates, and cost optimization, though partially offset by overseas capacity ramp-up, and far above the market’s expected 60-61%. EPS was NT$19.5, up 12% QoQ and 35% YoY.

For 1Q26 and full-year 2026, the company guided:

1) Revenue midpoint implying ~4% QoQ growth, with full-year growth close to 30% YoY, largely in line with expectations (vs. our estimate of 30% and Bloomberg consensus of high-20%);
2) 1Q26 gross margin of 63-65%, stronger than expectations and recent market rumors of 61-62%;
3) 2026 capital expenditure of US$52-56 billion, significantly above expectations (vs. our US$49-50 billion, sell-side US$46-49 billion, buy-side US$47-52 billion);
4) AI revenue CAGR guidance raised from mid-40% to mid/high-50%;
5) Long-term revenue CAGR raised to 25%, higher than the previous 15-20%.

Strong US$52-56 billion capex guidance, with an aggressive tone for 2026-2028
Driven by the long-term AI trend, the company’s US$52-56 billion guidance for 2026 was the key highlight of the earnings call. The company also expects capital expenditure over the next three years to be significantly higher than the US$101 billion spent in the past three years. Based on our estimates of TSMC’s EUV demand of 25/36 tools in 2026/2027, we expect capex to reach US$54 billion in 2026 and US$64 billion in 2027, maintaining a normal level of capital intensity.

The scale of advanced-node capacity and capital expenditure will further strengthen TSMC’s leading position, while migration to the new N2P node (5-10% higher ASP than N2) and A16 (20% higher ASP than N2) will continue.

$TSM


strong price increases in the first quarter are certain. It is estimated that RDIMM module prices could rise by more than 70%... first-quarter price increases may well exceed 80%

Summary: Structural AI-driven memory shortage to persist through 2027-28; RDIMM prices up 80%+ Q1, DRAM +20-30% and SSDs +30-50% beyond Q1; bullish Samsung and SK Hynix.

Samsung Electronics listed on KOSPI as 005930.KS

RDIMM spot prices blow past US$2,000, raising odds of 80% Samsung memory hike

Structural imbalances in the memory industry have emerged due to AI data center demand, sending server memory prices sky high and upstream manufacturers to go all out to increase profits. Severe shortages are expected to persist through 2027-2028. As pressure increases due to insufficient inventory, memory prices also continue to rise.

Confirmation elusive of price hike
Spot prices for server-grade 64GB RDIMM modules have surged to US$2,550, rising more than 20% in just the past half month. This suggests that official contract prices could approach a sky-high US$1,000 level, implying a potential quarterly increase of 90-100%. Recently, online reports circulated documents claiming that Samsung Electronics had issued notices of price increases, citing major changes in the global semiconductor market, including supply constraints and sharply rising upstream manufacturing costs.

The reports claimed that, effective immediately, prices for all Samsung memory products would increase by as much as 80%. Samsung Taiwan said it would not comment on market rumors.

While the alleged price hike notice apparently originated from a Samsung distributor, related companies stated that they have not yet received any confirmed price increase notifications and are unable to verify the documents' sources. With Samsung and SK Hynix still having not fully finalized official pricing, the supply chain is anxiously awaiting the outcome.

Even steeper first-quarter increases
Nonetheless, strong price increases in the first quarter are certain. It is estimated that RDIMM module prices could rise by more than 70%. Some module makers also believe that the manufacturers' continued delay in announcing prices indicates that headquarters are still consolidating views on end-market demand. With nearly all manufacturers' 2026 capacity allocations already sold out in advance, first-quarter price increases may well exceed 80%.

Memory supply chain players note that surging demand for AI computing and inference has driven cloud service providers' (CSPs) procurement of DRAM and NAND Flash ever higher. With capacity expansion unable to keep pace, the demand gap is estimated at at least 25–30%. Server memory module pricing has been particularly strong, with the spot market being the most price-sensitive and likely to reflect upstream manufacturers' contract price increases. Using 64GB RDIMM modules as an example, spot prices reached US$1,850 in mid-January, but have since surged to US$2,250, representing a 20% increase within half a month.

To compare, contract prices for 64GB RDIMM modules were around US$450-460 in the fourth quarter of 2025 and were originally expected to rise to US$800-900 in the first quarter. However, as spot prices continue to spike, server memory modules could reach the US$1,000 threshold. Based on this, quarterly price increases could potentially double.

Server storage cost pressures
NAND Flash has also seen severe supply tightness as enterprise server storage capacities expand. There have recently been plans to mobilize hundreds of millions of US dollars to approach US-based NAND supplier SanDisk with prepayment offers for long-term supply contracts. However, contract negotiations have been repeatedly delayed, with pricing and supply volumes still under negotiation. While contract price increases are expected to be more moderate than anticipated, with wafer-level Flash prices rising by around 30–50%, order fulfillment rates remain below 50%.

Memory contract prices will see their most dramatic, step-like increases in the first quarter of 2026. From the second quarter onward, the pace of increases is expected to moderate, but DRAM is still projected to have room for 20-30% price hikes, while solid-state drives (SSDs) are expected to continue seeing increases of 30-50%.

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https://t.co/3ZoR6wZszl


With Samsung and SK Hynix still having not fully finalized official pricing, the supply chain is anxiously awaiting the outcome


DRAM is still projected to have room for 20-30% price hikes

DRAM sector basket: Micron, Samsung, SK Hynix


solid-state drives (SSDs) are expected to continue seeing increases of 30-50%

NAND sector basket: major NAND producers


I've been building a bull case for Meta lately. Even without reaching $60, a move to the $30–40 range would be transformative against Meta's ~$160B annual ad revenue base — potentially unlocking tens of billions in incremental revenue.

Summary: Long META: platform-level AI deployment across 4B MAU, Ray-Ban hardware momentum, and CPM expansion from $10–20 toward $30–40 could unlock tens of billions in incremental ad revenue.

industry='Internet Content & Information'

I've been building a bull case for Meta lately. This is a casual memo — would love to hear your thoughts.

---------------------------------
Meta: An Underappreciated AI Platform Strategy (Memo)

-----## 1. Does Meta Really Need the Best LLM?ByteDance’s Doubao offers a telling precedent. Despite not being China’s most powerful model, Doubao leads the Chinese AI chatbot market with 170M MAU — far ahead of DeepSeek (72M) and Tencent’s Yuanbao (73M). The edge isn’t model performance but platform integration — ByteDance embedded AI across its entire ecosystem: Douyin, Jianying, Ola Friend, and even a ZTE Nubia AI-native phone.
Meta could become the Western ByteDance. Facebook, Instagram, WhatsApp, and Messenger combined reach ~4B MAU. Layer even a “good enough” AI on top of that, and Meta holds an overwhelming advantage in mass-market agent AI deployment.
To be clear, Meta hasn’t abandoned the frontier model race. It hired Scale AI’s Alexandr Wang for ~$14.3B and is developing “Avocado,” a proprietary next-gen model targeting H1 2026 release (reportedly achieving 10x+ compute efficiency vs. Llama 4). But even if Avocado falls short of the latest models from OpenAI or Anthropic, Meta’s AI strategy doesn’t fail. Platform-level utilization may matter more than benchmarks.

-----## 2. AI Hardware: Narrative vs. Results
Market attention is fixated on OpenAI’s hardware play (Jony Ive’s io acquisition for $6.4B, Foxconn partnership), but the AI hardware that’s actually selling is Meta’s Ray-Ban smart glasses.
- Ray-Ban Meta: 2M+ cumulative units sold; Q2 2025 sales tripled QoQ
- Ray-Ban Display ($799): US demand exceeded supply → UK, France, Italy, Canada launches postponed; waitlists extend through end of 2026
- EssilorLuxottica reviewing capacity expansion from 10M to 20–30M units/year (Bloomberg)
- All this demand before Avocado (next-gen LLM) has even been integrated

Meanwhile, OpenAI hardware remains at prototype stage; court filings indicate customer shipments delayed to post-February 2027.The key differentiator: Meta’s partnership with EssilorLuxottica — the world’s largest eyewear company — secured a form factor people actually wear in public. Compare this to Google Glass, which failed largely on social acceptability. The Ray-Ban brand itself is a moat.

-----## 3. Ad CPM Upside Potential
Per The Information: OpenAI is pricing ChatGPT ads at ~$60 CPM — roughly 3x Meta’s average of $10–20. OpenAI’s rationale: a “high-intent” environment commands a premium.
But OpenAI still lacks basic ad infrastructure (only high-level metrics like total impressions/clicks; no conversion tracking; $200K minimum commitment). Meta’s decades of precision targeting and conversion attribution remain assets OpenAI simply doesn’t have.
Add AI-driven hyper-personalization → contextual awareness, real-time interest signals, purchase-journey stage optimization → meaningful room to push current $10–20 CPMs higher.
Even without reaching $60, a move to the $30–40 range would be transformative against Meta’s ~$160B annual ad revenue base — potentially unlocking tens of billions in incremental revenue. Ray-Ban glasses could also emerge as an entirely new ad channel via location-based AI ads and gaze-tracking engagement metrics.

$META


Summary: Relays foreign brokerage consensus to sell KOSPI and sit on sidelines; strong-H1/weak-H2 pattern with technical correction targets as low as 5,000.

"Sell KOSPI and watch from the sidelines for a while"… The global sentiment conveyed by foreign brokerages

Foreign investors are aggressively selling domestic equities. Their intention is reportedly to lock in profits first and then stay on the sidelines for the time being. Additionally, these investors are said to have been anticipating a "strong first half, weak second half" pattern and a technical correction in KOSPI.

Foreign investors' cumulative net selling in KOSPI this year: KRW 27 trillion

According to Yonhap Infomax trading data (screen no. 3302) as of the 4th, foreign investors were cumulative net buyers from the start of the year through January 30, but have been cumulative net sellers from February 2 to the present. Year-to-date cumulative net selling now approaches KRW 27 trillion. Notably, foreigners net sold roughly KRW 7 trillion and KRW 5 trillion on February 27 and March 3, respectively — as war clouds gathered over the Middle East and conflict broke out.

An official at a foreign brokerage said, "Foreign investors are locking in gains and de-risking." The explanation is that leading stocks including Samsung Electronics and SK Hynix had rallied significantly, and foreigners used the Middle East crisis as a catalyst to take profits.

KOSPI has plunged for two consecutive days amid the foreign selling onslaught. Since breaching the 6,300 level late last month, the index has nosedived to 5,386 as of now.

The "strong first half, weak second half" narrative circulating among foreigners

He also noted that foreigners intend to "sell first and then watch." The story that Korea's market would follow a "strong first half, weak second half" trajectory this year had been widely circulated among global investors.

On top of that, some foreign investors hold a neutral view on the Korean market — meaning they are reluctant to overweight Korea within their global equity portfolios relative to benchmark levels.

The brokerage official said there have "always been many institutions that don't hold Korea," adding that "while it's hard to generalize, there have been cases globally where investors played the tech theme through other avenues and came into Korea only belatedly."

Foreigners had been anticipating a KOSPI correction all along

Some foreign investors had in fact foreseen a KOSPI correction.

An official at another foreign financial firm said, "There was considerable consensus on the overseas side that KOSPI could undergo a significant correction from a technical standpoint." He added, "Looking at technical analyses of Korean equities, there were even calls for KOSPI to fall to 5,000." His interpretation is that the correction foreigners had long anticipated is now materializing on a larger scale due to geopolitical risk.

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https://t.co/WbujAruhVC


the 4Q25 fixed price is expanding to a level 53–58% higher QoQ... suppliers are expected to propose initial quotes reflecting a 60–70% increase... the growth rate for Server DRAM fixed prices in 2026 is projected as follows: 1Q (+60–65%) / 2Q (+10–15%) / 3Q (+3–8%) / 4Q (+0–5%)

Summary: Server DRAM prices surging 53-58% QoQ in 4Q25 with 60-65% more in 1Q26; HBM3E prices also rising as shortages persist through 2026.

Server DRAM sector basket: Micron, SK Hynix, Samsung

[Commentary on DRAMeXchange December Server DRAM Fixed Prices & Industry Trends]

- December Pricing & Additional Orders: Negotiations for December Server DRAM fixed prices are proceeding at elevated levels, with additional orders for December delivery becoming a key topic. Major customers include US CSPs, Chinese CSPs, and OEMs. As supplier inventories are depleted, additional orders can only be fulfilled by rescheduling delivery timelines with existing customers. Consequently, actual transaction prices in December surged, rising 88–93% compared to the 3Q25 average fixed price. Furthermore, the 4Q25 fixed price is expanding to a level 53–58% higher QoQ.

- 1Q26 Outlook & Supplier Stance: From December, the negotiation focus is gradually shifting to 1Q26 contracts. Given the current tight supply-demand conditions, suppliers are expected to propose initial quotes reflecting a 60–70% increase, exceeding the levels seen in December's add-on orders. Suppliers maintain a bullish outlook for continued quarterly price hikes throughout 2026. Anticipating further increases in future quarters, they are currently reluctant to sign multi-year lock-in contracts with CSPs.

- 2026 Price Forecast: Considering the above, the growth rate for Server DRAM fixed prices in 2026 is projected as follows: 1Q (+60–65%) / 2Q (+10–15%) / 3Q (+3–8%) / 4Q (+0–5%). This represents an upward revision from last month's estimates, and further upward adjustments cannot be ruled out.

- CSP Financials & Demand: CSPs assess that cash flows generated from existing businesses can sufficiently cover CapEx for large-scale infrastructure build-outs, with a focus on realizing monetization from inference AI. Therefore, they are not significantly pushing back against DRAM price hikes, accepting them to secure stable volumes. Analysis suggests that considering their margin structures, customers still have room to absorb these price increases.

- Market Monitoring: Market participants are closely watching these purchasing strategies to determine when the peak of the price (P) cycle will occur. OEMs are expected to maintain margin headroom until at least 1H26, while CSPs are projected to be capable of absorbing potential supply gluts in the market.

- HBM3E Impact & Supply Allocation: Entering December, GPU/ASIC manufacturers retracted previous expectations for a decline in HBM3E purchase prices in 2026, as suppliers successfully induced price hikes against the backdrop of shortages. Consequently, suppliers are reducing legacy commodity DRAM supply to focus on HBM3E. Amid this trend, adjustments to supply and procurement volumes for CSPs and OEMs continue within 2026 LTAs (Long-Term Agreements). Some OEMs and Chinese CSPs with relatively lower transaction stability have reportedly received notices of supply cuts. Overall, while Server DRAM supply volumes are being revised upward, PC DRAM remains an application area where suppliers are concentrating on production cuts.

- Customer Prioritization: Supplier allocation decisions are based on the customer's actual demand levels, past transaction history, and partnership evaluation. With US CSPs showing rising transaction prices for Server DRAM and HBM while actively securing 1H26 deliveries, the possibility cannot be excluded that suppliers may cut Server DRAM supply for lower-priority customers. This increases the likelihood of intensifying tight supply conditions for OEMs and Chinese CSPs.

- AI-Driven Demand Growth: As inference AI applications like Gemini and Copilot drive demand for commodity servers, CSPs (led by MSFT and Google) are aggressively increasing server assembly orders to ODMs. Accordingly, the 2026 server shipment growth forecast has been revised upward from 9% to 13% YoY. Additionally, the expanded adoption of multi-core CPUs is increasing procurement of high-capacity RDIMMs, pushing Server DRAM content per box up 20% YoY. Total Server DRAM bit demand growth is expected to reach 39%, significantly exceeding the previous forecast of 23%.

- Contract Terms (NCNR): Suppliers are negotiating LTA contracts that include NCNR (Non-Cancellable, Non-Returnable) clauses with major customers, aiming to secure long-term CapEx visibility through 2028 based on these agreements. However, despite these contracts, securing sufficient supply in a timely manner for 2026 is expected to remain challenging.

(Source: DRAMeXchange)


GPU/ASIC manufacturers retracted previous expectations for a decline in HBM3E purchase prices in 2026, as suppliers successfully induced price hikes against the backdrop of shortages

Global HBM sector basket: SK Hynix, Samsung, Micron


Summary: Shares/endorses HSBC raising Samsung Electronics PT to KRW 300,000 with 2026 OP forecast of KRW 220T.

HSBC raises Samsung Electronics target price to KRW 300,000

HSBC forecasts Samsung Electronics' 2026 operating profit at KRW 220 trillion (approximately $148.1 billion USD)

HSBC, 삼성전자 목표가 30만원으로 상향

HSBC, 올해 삼성전자 영업이익 148.1 billion USD로 전망 https://t.co/RSz18g1pMz


Summary: EMIB gaining traction as CoWoS alternative; INTC packaging revenues to scale to tens of billions from H2 2026, driving renewed investment by Ibiden and Unimicron.

Intel’s EMIB gains traction as CoWoS alternative, reviving IC substrate investment

The global AI surge has sharply increased demand for advanced chips, leaving TSMC's CoWoS capacity in tight supply. Intel's advanced packaging strategy is set to reach a critical turning point in second half 2026, boosting confidence across its long-struggling supply chain and triggering renewed investment momentum.

Intel has reportedly maintained close collaboration on its Embedded Multi-die Interconnect Bridge (EMIB) advanced packaging technology with two major IC substrate suppliers: Japan's Ibiden and Taiwan's Unimicron. Both companies also serve the CoWoS supply chain, capturing business from both TSMC and Intel ecosystems and positioning themselves to benefit from an expected order surge over the coming years.

Under intense pressure from AI chipmakers locking down TSMC capacity and amid manufacturing reshoring trends to the US, many previously sidelined customers are now turning to Intel's EMIB solution. The industry views EMIB as the most powerful alternative advanced packaging technology outside of TSMC's domain.

IC substrate players note that while TSMC's CoWoS will remain the dominant industry standard, the supply chain actively seeks secondary sources.

Although the back-end processes differ significantly between the two advanced packaging technologies, their front-end production shares commonalities, allowing some capacity flexibility depending on end-customer allocation.

Investment moves by the two leading IC substrate suppliers illustrate this trend. Ibiden announced plans to invest about JPY500 billion (US$3.2 billion) over three years at its Gifu sites—JPY220 billion and JPY280 billion respectively—focusing on expanding advanced IC substrate capacity for AI servers. By 2028, Ibiden aims to increase output to 2.5x current levels to meet orders from Intel, TSMC, and others.

Meanwhile, Unimicron has repeatedly raised its 2026 capital expenditure budget to approximately NT$34 billion (US$1.1 billion), concentrating ABF substrate expansion at its Hsinchu plants. These expansions are expected to contribute significant revenue starting second half of 2027. The company's board has also expanded long-lead equipment procurement for 2027, increasing orders to around NT$9.2 billion.

Notably, Intel's cooperation with these two IC substrate suppliers goes beyond traditional purchasing models. Years ago, they jointly invested in dedicated production facilities for EMIB orders, including Unimicron's Taoyuan Yangmei plant.

However, due to slower-than-expected adoption of EMIB advanced packaging by end products, these dedicated lines remained underutilized for a long time. With Intel's consent, both suppliers prioritized reallocating part of this capacity to CoWoS customers to alleviate low utilization pressures.

Intel CFO David Zinsner recently confirmed during earnings calls that Intel's EMIB and upgraded EMIB-T solutions have attracted proactive inquiries from multiple IC design customers, including heavyweights Apple, Nvidia, and Qualcomm.

Zinsner stated that based on ongoing negotiations, Intel expects EMIB-related advanced packaging revenues to reach several hundred million dollars initially, then scale up to tens of billions of dollars starting second half of 2026—far exceeding earlier projections. This reflects surging market interest and accelerating mass production commitments among key customers.

$INTC

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https://t.co/xCBhAU5lK5


Ibiden announced plans to invest about JPY500 billion (US$3.2 billion) over three years at its Gifu sites—focusing on expanding advanced IC substrate capacity for AI servers. By 2028, Ibiden aims to increase output to 2.5x current levels

Ibiden Co. Ltd 4062.T Japan ABF substrate


Unimicron has repeatedly raised its 2026 capital expenditure budget to approximately NT$34 billion (US$1.1 billion), concentrating ABF substrate expansion at its Hsinchu plants. These expansions are expected to contribute significant revenue starting second half of 2027

Unimicron Technology listed on TWSE as 3037.TW


high-end ABF substrate supply tight at Japan's Ibiden and Taiwan's Nanya PCB and Unimicron, double-digit ABF price hike requests have already become the dominant trend

Summary: AI-driven structural tightness in high-end ABF substrates expected to drive 15–20%+ price hikes in 2026; Ibiden, Unimicron, and Kinsus are key beneficiaries.

▶ AI Platform Push Drives High-End Substrate Price Hikes

- As demand for AI servers and high-performance computing (HPC) continues to expand, supply-demand conditions for high-end IC substrates remain persistently tight.

- In particular, shortages of key materials such as low-coefficient-of-thermal-expansion (Low CTE) fiberglass are driving a shift in pricing negotiations—from one-off quotations in the past to a more structural model based on quarterly adjustments and cumulative demand.

- The market expects high-end substrate prices in 2026 to rise by at least 15–20%, and some specialty products are even rumored to see increases of over 40%. The first round of price adjustments is anticipated to begin in the late part of 1Q.

- With high-end ABF substrate supply tight at Japan’s Ibiden and Taiwan’s Nanya PCB and Unimicron, double-digit ABF price hike requests have already become the dominant trend.

- As a spillover effect, some of Kinsus’ high-end production lines have reportedly been pre-booked in advance by major AI customers, leading to an operating model resembling a “quasi-packaging factory.” This suggests that demand intensity from AI and advanced computing platforms is far outpacing that of mainstream consumer applications.

- However, Kinsus noted that the kind of long-term contracts or “blanket capacity lock-ups” seen during the peak shortage period in 2022 no longer exist, and at present there are no cases where customers are formally tying up capacity through contract structures.
Kinsus further explained that the current cooperation model has shifted toward preparing and allocating capacity based on annual demand forecasts.

- Industry players view this round of price adjustments as somewhat different from the broad-based substrate super-cycle driven by the 2022 economic cycle.

- This time, the key driver is structural change caused by rapid product specification upgrades as AI platform generations advance.

- In other words, as AI chips see significant increases in pin count and packaging complexity, high-end substrates are simultaneously being pushed to higher layer counts, tighter line/space, and more intensive material usage, which in turn raises the barrier to achieving acceptable process yields.

- According to industry sources, shortages of the key material—Low CTE fiberglass cloth—are ongoing, and lead times for Nittobo’s high-end fiberglass products have lengthened noticeably.

- In addition, Nanya Plastics has officially issued price increase notices to customers: standard E-glass products were raised by roughly 15%, while ultra-thin fiberglass products below the 1037 spec posted an increase of around 25%.

- Considering these raw-material price trends, industry participants expect high-end substrate prices in 2026 to be adjusted step-by-step starting from 1Q, with quarterly increases of at least 3–5%, and an annual increase of at least ~20%.

- That said, the magnitude of increases may be negotiated in stages depending on demand strength, material supply conditions, and capacity allocation.

- The industry also notes that as AI servers move toward more modular designs and demand for high-speed transmission rises, some applications have begun adopting high-spec BT substrates as core supporting structures—an additional growth driver expected to underpin the 2026 substrate market.

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https://t.co/jES1ZpYbaJ


some of Kinsus' high-end production lines have reportedly been pre-booked in advance by major AI customers, leading to an operating model resembling a 'quasi-packaging factory'

Kinsus Interconnect Technology 3189.TW Taiwan


The HDD supply shortage is now widening to 200EB over the next 12 months… STX is raising consumer/client HDD prices by 10% every quarter to better align the margin profile with nearline drives

Summary: Morgan Stanley takeaways bullish on HDD names: widening supply shortage, rising prices, strong nearline demand, and constrained supply support STX and WDC.

Morgan Stanley’s Key Takeaways on HDD/Storage:

• The HDD supply shortage is now widening to 200EB over the next 12 months (vs. 100-150EB 3 months ago). Hyperscalers are using/qualifying eSSDs to help fulfill / backstop storage demand despite being far less efficient in terms of TCO (total cost of ownership) vs. using HDDs. Our checks suggest this is still a temporary measure and not a re-architecting towards eSSD.

• Memory makers have been proactively trying to find opportunities to lower the price per GB for eSSDs to try and replace HDDs as early as CY28. However, since NAND prices per GB are now well above $0.10 vs. overall
HDD at $0.013 on average — implying up to 10x of acquisition cost difference by the end of C4Q25 — introducing high-layer (400+ layers) NAND for eSSDs to replace HDDs no longer is a key focus for memory makers.

• CSPs' SSD demand fulfillment rate is now at just 40%, likely because of both increasing customer demand and strengthening forward-looking forecasts amidst limited supply upside from SSDs and HDDs. To be clear, we have not seen over-shipping so far as current SSD/HDD industry supply cannot fulfill the full demand.

• HDD makers remain reluctant to expand unit capacity, but they are shifting capacity allocation from client/consumer applications to support expanding
cloud/nearline demand.

• STX is raising consumer/client HDD prices by 10% every quarter to better align the margin profile with nearline drives. For what it's worth, STX mentioned on its F1Q26 earnings call that it has been "taking some supply out of Edge IoT products and putting it into Cloud as we can pivot demand."

$STX $WDC


HDD makers remain reluctant to expand unit capacity, but they are shifting capacity allocation from client/consumer applications to support expanding cloud/nearline demand


Summary: Bullish Samsung Electronics: foundry profitability normalization not yet priced into the stock.

I believe the market is currently not pricing in the normalization of Samsung Foundry into Samsung's stock price. https://t.co/eYQjaTkAQw

Samsung Foundry "Targeting Profitability This Year"

Samsung Electronics has set a goal of turning its semiconductor foundry business profitable this year. It has been confirmed that the company moved up the timeline, which was originally scheduled to break even next year. After https://t.co/WgHc13YbSp


Summary: Bullish Samsung: potential to be world's most profitable company by 2027 yet trades under $1T market cap — implying deep undervaluation.

Samsung could become the most profitable company in the world in 2027, and yet its market cap is still under $1 trillion! https://t.co/uAMgYrJlEa


Summary: Micron's EUV pivot benefits ASML but is modestly negative for AMAT and LRCX as multi-patterning steps decline.

Micron's strategic pivot toward more aggressive EUV adoption is interpreted as an effort to save fab space and thereby expand overall output capacity.

This implies a departure from its conventional multi-patterning approach — a development that is positive for ASML, but modestly negative for AMAT and LRCX.

First 5-year SCA signed. New EUV layer roadmap. ✍ https://t.co/52JZpZMK6l


Summary: ABF substrate structural shortage drives growth for Unimicron, Kinsus, Nan Ya PCB, and Ibiden into 2026 on AI server demand; Q1 2026 expected to hold steady despite seasonal weakness.

▶ ABF substrate crunch reshapes market: Unimicron leads and rivals close in

- As AI server architectures rapidly shift toward ultra-high-density designs, advanced CoWoS packaging capacity faces persistent shortages.

- Simultaneously, warping and thermal stress issues caused by expanding die sizes have led to a surge in ABF substrate demand, resulting in structural supply pressure.

- As AI GPU and ASIC customers accelerate market expansion, Japan’s Ibiden recently announced a large-scale capacity expansion, highlighting the ongoing shortage of ABF substrates for AI servers.

- Alongside Unimicron, an early supply chain entrant, Nan Ya PCB and Kinsus have also begun securing related orders, with shipments expected to increase steadily.

- Kinsus recorded the strongest performance, with 2025 annual revenue surging 28.87%, driven by increased orders for ABF and BT substrates.

- Nan Ya PCB also achieved robust growth, with 2025 revenue increasing 24.44%, as the effects of product mix shifts continued to manifest.

- Although Unimicron’s annual revenue for 2025 grew by a relatively modest 13.75%, its December net profit recorded explosive growth, increasing 2,770% year-on-year.

- In the case of BT substrates, while they benefited from active purchasing by downstream companies due to past memory shortages, growth is expected to slow due to deteriorating conditions in the consumer electronics sector.

- In 2026, the global IC substrate industry is projected to focus on expanding ABF substrate production for AI chips, which will be a primary capacity expansion goal for Taiwanese suppliers.

- Looking ahead to Q1 2026, IC substrate manufacturers are expected to maintain steady momentum even during the traditional off-season, supported by rising AI-driven demand and extended order lead times from memory customers.

- Utilization rates for both ABF and BT substrates are expected to steadily recover, offsetting the revenue decline that typically occurs as the consumer device launch cycle ends.

- Simultaneously, rising product prices are contributing to improved profitability, laying a solid foundation for annual growth.

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https://t.co/6mYzd24jIj


Nan Ya PCB also achieved robust growth, with 2025 revenue increasing 24.44%, as the effects of product mix shifts continued to manifest

Nan Ya PCB (NYPCB) listed on TWSE as 8046.TW


Kinsus recorded the strongest performance, with 2025 annual revenue surging 28.87%, driven by increased orders for ABF and BT substrates


Japan's Ibiden recently announced a large-scale capacity expansion, highlighting the ongoing shortage of ABF substrates for AI servers


Summary: Bullish memory: no signs of falling prices; commodity DRAM supply squeeze from HBM ramp is a positive signal.

Memory sector basket: Micron, SK Hynix, Samsung

@MikeFritzell I still haven’t seen any signs that memory prices are falling. If anything, as you pointed out, the decline in overall semiconductor output likely means commodity DRAM production has been reduced to ramp up HBM, which is actually a bullish signal for memory.

@jukan05 curious to hear your view, as I don't hear anything about the memory bear case, from anywhere


Summary: Long semicap on Intel's revised flat 2026 capex with front-loaded IFS equipment purchases signaling foundry confidence.

Commenting on $INTC, Intel’s 2026 capex was originally expected to decline vs. 2025. However, note that Intel has revised this plan to keep capex roughly flat or only slightly down.

Intel Foundry (IFS) investments are set to be front-loaded in 1H, with a greater allocation toward equipment purchases. This suggests Intel is becoming more confident in its ability to secure foundry customers.

Long Semicap.


US semiconductor equipment basket: AMAT, Lam, KLA, Kulicke


Vera Rubin: Entered mass production regime. Increased visibility for 2H26 shipments… Reasoning created 5x; Agentic will create 50x… overall platform strategy remains centered on general-purpose GPU/systems

Summary: Bullish NVDA: Vera Rubin mass production on track for 2H26, agentic AI driving 50x token demand, and general-purpose GPU platform retains structural TCO advantage over SRAM/CPX alternatives.

260106_NVIDIA: CES Financial Analyst Q&A

Q1) Bank of America: What does it mean that Vera Rubin has entered Full Production? Does this accelerate shipments and revenue recognition?

A1) In the past, this term referred to Tape-Out, but now it literally means progress into the mass production phase. Market launch is in the second half of this year, and the cycle time should be considered around 9 months or more.

Q2) Bank of America: What is the short-, medium-, and long-term significance of the Groq license for us? Does this mean we have reached the stage where we believe we need more "ASIC-like" chips specialized for certain types of inference?

A2) Our chips are inherently ASICs. The concept is that we design them in-house and manufacture them through TSMC foundries. Most AI workloads are highly likely to run on our architecture. What Groq pursues is extreme low latency, which is in a trade-off relationship with our strength in extreme high throughput. In the future, when AI-powered devices (such as glasses) emerge, diverse demand for low latency will arise.

Q3) Could you elaborate a bit more to help us better understand the core market sizes and timing for data centers, autonomous driving, robotics, etc.? In particular, how do you view the revenue model for Alpamayo?

A3) Autonomous driving took 8 years to reach this point, and we provide data center training infrastructure and the full software stack (simulation + synthetic data + world models, etc.) across the entire ecosystem. Most companies use us—some extend into vehicles, while others deploy the full stack. In the future, autonomous driving and robotaxis will become a very large business.

Q4) Melius Research: Regarding the "better token economics" comment, I want to ask about Anthropic. They could have obtained as much Trainium as they wanted, or TPUs if they wished—why choose us? Are there cases where workloads previously tuned for Trainium or TPUs are migrating to Rubin? Is it ultimately because of token economics?

A4) I regret not being able to invest in Anthropic. Anthropic excels at producing high-quality tokens, especially in enterprise coding, where iterative tasks make token generation speed (low latency/high-speed generation) critical—and that's where we deliver significant value. AI companies need platforms that can run anything with a rich ecosystem. With last year's Anthropic announcement, the last major player not running on NVIDIA has now joined.

Q5) Wells Fargo: Supply chain variables seem numerous—1) DRAM pricing, 2) available supply volumes, etc. Please explain. Also, could power become a bottleneck in the future?

A5) The reason we are advantaged is that we were already at massive scale and growing very rapidly from that large base, so we prepared for this kind of major ramp-up with partners well in advance. We invested heavily in partners, much of it in the form of prepayments, enabling them to expand capacity. Thanks to long-standing relationships, we believe we are in a strong position. We are essentially the only semiconductor company in the world that directly purchases DRAM at global scale. People ask, "Why buy DRAM?" The reason is simple: transforming that DRAM into CoWoS supercomputers is extraordinarily difficult. Properly connecting that supply chain like "plumbing" is a major advantage for us. In tight situations like now, having this capability is also fortunate.

Q6) Bernstein: If China-related restrictions are eased, can ramp-up proceed smoothly? Regarding DGX, you previously said it wasn't the original target market, but the stance seems different now. What changed?

A6) H20 is dedicated volume for China, so it does not overlap with existing orders. H200 is currently in the licensing process. For DGX, it was never about competing with CSPs; initially, when CSPs were unfamiliar with AI Cloud, it was a strategic vehicle to land our models and partner ecosystem with them. Now the market flywheel is spinning, and the need to force token leasing via DGX Cloud has diminished. The resale model for profit was somewhat inefficient to begin with.

Q7) Goldman Sachs: How important is context memory storage control?

A7) With inference volumes surging, context/token memory and KV Cache throughput have exploded, reaching limits with existing storage architectures—this makes it extremely important. The demand is large enough to create a "new storage tier," potentially becoming a massive storage market.

Q8) Have there been performance bottlenecks in specific customer/workload segments? Like networking in the past, can we expect continued innovation in storage/memory going forward?

A8) AI DB and KV Cache have become extremely heavy workloads; handling them over traditional north-south network-based storage wastes traffic. We are already the world's largest in networking and expect to become the largest in storage processors as well. Based on BlueField-4 + DOCA adoption, we will continue expanding and innovating the infrastructure stack from networking into storage. In other words, we will strengthen BlueField-4 and DOCA as the SmartNIC for AI factories, establishing a dominant position in storage processing following networking.

Q9) Truist: When ramping Rubin, what happens to Hopper? The ramp speed seems quite fast—what impact on margins?

A9) Rubin targets "zero-downtime AI factories" with features like RAS and NVLink hot-swap. The challenge with Rubin is that it is historically unique as a computer where "every chip inside is brand new"—even high-temperature capacitors were newly developed. HBM4 did not exist, nor did LPDDR5 SOCAMM. Co-Packaged Optics are integrated into switches. This was possible because we de-risked technologies, components, and supply chains piece by piece over about 5 years, and now everything is verified and in mass production readiness.

Q10) Truist: How do you see the frontier AI model market evolving going forward?

A10) I agree that in general-purpose models, most are now at a similar "good enough" level. General-purpose reaches "good enough" quickly, but in specialized models, it is still unrealistic for one model to excel across all domains. If consolidation occurs, it will likely be around "channels"—platforms like Alphabet, Meta, social media, etc.

Q11) Daiwa: Where is the industry at present with Agentic/Physical AI?

A11) Agentic AI is already a core trend. Most future AI applications will likely be agentic. Citing Cursor and OpenEvidence as examples, in the future, instead of libraries, combining models + agentic systems and simply giving goals will enable automated collaboration and easier application deployment. Autonomous driving/Physical AI is evolving toward fully agentic forms like Alpamayo's VLA (vision-language-action) robotic systems that perform situation decomposition, commonsense reasoning, and user Q&A.

Q12) Morgan Stanley: In the LLM era, CSPs shifted CAPEX— who will fund Physical AI?

A12) By creating and freely distributing Cosmos, we significantly lower the initial cost/barrier that the industry must bear, so companies will invest money and effort in fine-tuning and domain adaptation on top of it.

Q13) Loop Capital: What role does Neo-Cloud play in the market? Why are we strengthening partnerships with them? Does enterprise/sovereign adoption help NVIDIA Enterprise OS sales?

A13) In an environment where technology/market changes are rapid and core data center resources (land/power/space) are constrained, agile operators will succeed. AI infrastructure will be built regionally, evolving into communities that include researchers, startups, and large enterprises. Providing infrastructure close to customers is becoming important, leading to growth in regionally distributed AI infrastructure.

Q14) Wolfe Research: Why can initial Rubin ramp margins be maintained? How will high margins be sustained amid competition?

A14) Precise predictions like 50BP increments are difficult. Focus on mid- to long-term customer value rather than short-term numbers. Key factors include training efficiency, inference token cost and speed, and maximizing data center revenue within constrained power. We will also achieve world-leading RAS (reliability, availability, serviceability).

Q15) If there is a game-changer in the oligopoly landscape?

A15) There are about four. 1) Memory/context processing innovation—as context length grows (100K–1M → effectively infinite), attention/memory handling becomes the bottleneck, and research solving this could reshape competition. 2) Hybrid models (Transformer + SSM, etc.)—SSM is advantageous for context compression, making hybrids important. 3) System architecture innovation (bringing memory closer)—approaches like BlueField-4 to place long-term memory nearer to the compute fabric. Finally, 4) Continuous learning: automating "recognize unknown → research/learn → re-infer" is a major opportunity.

Q16) Tokens are growing 5x—when will re-acceleration/slowdown occur?

A16) The 5x growth driver is Reasoning. The next re-acceleration factor is Agentic Systems—with tool use, planning, and simulation, token usage will surge like "real-time AlphaGo." It could grow 50x.

Q17) Stifel: What does the pace/numbers like Spectrum X and 400G SerDes imply for future R&D intensity? Are there immediate benefits felt at EDA companies or Cursor, etc., and what is the relationship with Grok, Fabrica (Infabrica), etc.?

A17) We will continue investing across the entire stack (land/power/shell → chips → infrastructure → models → applications), and building such systems is critical. For Infabrica, scale-up has high integration that makes an independent company difficult, so internal integration was rational. For Groq, collaboration was natural because innovation is needed at the team level.

Q18) UBS: Can the software technology gained from the Grok deal be applied across the NVIDIA portfolio?

A18) Yes. Grok's programming model differs from NVIDIA's, and that difference underlies extreme low latency vs. extreme high throughput. We are considering reconfiguring some elements to absorb and extend them into NVIDIA capabilities. The product portfolio will remain mostly (~90%) centered on Grace Blackwell/Vera Rubin, though some (~10%) could take new forms specialized for extreme low latency.

Q19) Robocap: NVIDIA already has CPX technology and, through the Groq acquisition, secured SRAM accessibility for inference. Your team published a paper a month ago on using CPX to reduce HBM usage, suggesting GDDR7 could replace HBM. Going forward, could the combination of Grok (=SRAM) + internal CPX allow HBM usage to be controlled at a more "manageable level"? And could this positively impact our margins?

A19) First explain the strengths of each, then why it is not that simple. CPX offers better prefill performance per dollar. If everything could fit in SRAM, HBM would indeed be unnecessary. However, the issue is that model size would shrink by roughly 100x. For certain workloads, SRAM can be dramatically faster than HBM access. But workloads (models/tasks) keep changing—sometimes MoE, sometimes multimodal, diffusion, autoregressive, or SSM. These vary in shape and size, stressing NVLink, HBM, or all three differently. We are the universal answer because of flexibility. When workloads differ morning vs. night or customer to customer, our broad strength and flexibility across nearly everything is key. Extreme optimization for one workload is possible, but if it only covers 10% of data center workloads and is underutilized, the power/resources could have been used elsewhere—power is constrained. The key is viewing data centers not as "infinite money and space" but as finite power. Finite power must be optimally utilized across the entire data center, and greater flexibility is better. More integrated architecture is also better—for example, updating DeepSeek instantly improves all GPUs in the data center. Updating model libraries improves the whole data center. Understand? But with 17 fragmented architectures, "this is good for that, that is good for this" results in overall TCO not improving as much. In summary, CPX clearly has advantages but also reduces data center flexibility.

[Implication]

(1) Vera Rubin: Entered mass production regime. Increased visibility for 2H26 shipments

■ All components—HBM4, LPDDR5 SOCAMM, CPO, etc.—incorporate new parts and technologies

■ This reflects years of building technology + component supply chains, now fully verified and ready for mass production

■ Market launch/revenue recognition in the second half of 2026. Cycle time approximately 9 months+

(2) Agentic AI, Reasoning: Next level of token economics

■ Recent 5x token demand growth triggered by Reasoning

■ Agentic is not a specific feature but likely to become the default framework for future application development; combined with multimodal/large model proliferation, it will chain-drive compute demand in both training and inference

■ Reasoning created 5x; Agentic will create 50x

(3) AI Data Center: Era continues where generality is critical from TCO perspective

■ CPX and SRAM-based approaches have clear strengths in specific segments (especially prefill, latency-sensitive workloads)

■ However, as workloads rapidly shift to MoE/multimodal/diffusion/AR/SSM etc., bottlenecks move across NVLink/HBM/system-wide, worsening data center TCO

■ CPX–SRAM is closer to a localized option for some workloads rather than a "mainstream HBM replacement"; overall platform strategy remains centered on general-purpose GPU/systems


Summary: Shares IBs' raised targets on Samsung and SK Hynix as server DRAM prices surge 60–70% into a memory super-cycle driven by AI/HBM demand.

DRAM Prices Hike 70%... Korean Stock Market Hits All-Time High

Samsung Electronics and SK Hynix have proposed server DRAM prices up to 70% higher than the fourth quarter of last year to global cloud companies such as Microsoft (MS), Amazon Web Services (AWS), and Google. This surge is driven by the server DRAM market shifting into a complete "seller's market," as AI accelerator manufacturers like Nvidia and Broadcom increase orders for HBM3E (5th generation High Bandwidth Memory)—which is made by stacking DRAM—and Big Tech companies expand their purchases of DRAM for inference AI. Market forecasts suggest that, driven by this "memory super-cycle," the combined operating profit of Samsung Electronics and SK Hynix this year could reach 150 trillion won, a 2.5 to 3-fold increase compared to last year.

According to industry sources on the 5th, Samsung Electronics and SK Hynix are reportedly negotiating with major clients after presenting server DRAM price quotes that are 60–70% higher than in the fourth quarter of last year. DRAM suppliers and clients typically sign quarterly supply contracts at the end of the previous quarter or the beginning of the respective quarter.

Samsung and SK have significantly raised prices because they anticipate the server DRAM supply shortage will worsen. Memory manufacturers are focusing heavily on HBM3E production for Nvidia and AMD's AI accelerators (which the U.S. government has authorized for export to China), leaving them unable to produce enough server DRAM to meet demand. The explosive growth in demand for general-purpose DRAM used in servers, as Google (Gemini) and MS (Copilot) expand their inference AI services, has also contributed to the price hike.

The industry expects clients to accept the proposals from Samsung and SK. Market research firm DRAMeXchange analyzed, "Large clients view the spending required for AI infrastructure as 'sufficiently bearable,'" adding, "There is an atmosphere of not strongly resisting the DRAM price increase, based on the judgment that the monetization of inference AI is more important."

Global investment banks (IBs) such as Citi and Morgan Stanley have significantly raised their target prices and operating profit forecasts for Samsung Electronics and SK Hynix, reflecting this DRAM "mega-boom." On this day, the KOSPI index closed at 4,457.52, up 3.43%, marking an all-time high driven by the rally of the "two tops," Samsung Electronics (7.47%) and SK Hynix (2.81%).

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https://t.co/SnjYvRGRVx


Global investment banks (IBs) such as Citi and Morgan Stanley have significantly raised their target prices and operating profit forecasts for Samsung Electronics and SK Hynix


Summary: Long Nitto Boseki as the dominant supplier of high-end glass fabric with absolute pricing power; structural shortage persists until 2H27 when new capacity comes online.

Nitto Boseki (Nittobo) listed on TSE as 3110.T

Fiberglass: Will the supply shortage only ease in 2H27?

- Glass fabric is an essential core material used in iPhones. As the supply shortage intensifies, Apple has officially entered the competition to secure components alongside global Big Tech companies such as Nvidia, Google, and Amazon.

- According to industry outlooks, the glass fabric supply shortage is expected to persist until at least the second half of 2027, which is evaluated as a structural bottleneck reminiscent of the memory semiconductor supply shortage phase.

- Currently, high-end glass fabric is supplied almost entirely by Japan's Nitto Boseki (Nittobo), giving it absolute influence in the global supply chain.

- As major manufacturers such as Nvidia, Google, and Amazon widely adopt high-specification substrate materials, the supply-demand imbalance of high-quality glass fabric is rapidly worsening.

- This material shortage shows a pattern very similar to recent rapid price fluctuations in the memory market and is emerging as a key risk across the industry.

- Recently, Apple, AMD, and Nvidia dispatched personnel to Japan to secure the supply of glass fabric, but they failed to obtain actual additional volume.

- A senior executive of a global substrate manufacturer mentioned that, regardless of customer pressure, the current production capacity of leading manufacturer Nittobo has reached its limit, making it impossible to secure additional volume.

- From the current perspective, the supply shortage is expected to improve only around the second half of 2027, when Nittobo’s new production facilities begin full-scale operation.

- Apple is actively building alternative supply chains to mitigate supply risks.

- According to sources, Apple has dispatched a dedicated team to GFT, a small glass fabric factory in China, and requested technical support from Mitsubishi Gas Chemical to monitor and improve the factory's product quality.

- This material shortage is acting as a factor prompting many new companies to enter the market to capture business opportunities.

- In addition to the Taiwanese manufacturer Taiwan Glass, Chinese companies such as Taishan Fiberglass, Hung Ho Electronics, and Kingboard Laminates are also expanding investments in the market to benefit from the global supply chain imbalance.

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https://t.co/Lf0K1vBTvH


Summary: Own NVDA FQ4 revenue estimate $67.0–67.5B above $65.7B consensus; FQ1 guidance estimate $75.0B above $70.8B consensus; implied bullish into the print.

What do you think NVIDIA's earnings will look like?
My estimates are FQ4 revenue of $67.0–67.5B and FQ1 guidance of $75.0B.
NVIDIA's own FQ4 guidance was $65.0B, and the current consensus sits above that at ~$65.7B. Consensus for FQ1 revenue guidance is $70.8B.


we maintain our Overweight rating, driven by Broadcom's overwhelming technological superiority and market leadership. We recommend active accumulation at current price levels.

Summary: Shares JPM Overweight on AVGO with active accumulation rec; AI ASIC backlog strengthening for FY2026-27 on Google TPU dominance and Meta programs.

JPM TPU Commentary:

Strengthening AI ASIC Outlook for FY2026-2027 Broadcom’s outlook for its AI ASIC business in fiscal years 2026 and 2027 is strengthening, driven by deepened collaboration with its largest AI customer, Google. Broadcom maintains a technical lead of over 18 months compared to Google's internal COT (Customer Owned Tooling) program. This gap is becoming even more entrenched as the complexity of chip design and packaging intensifies. To support AI workloads for external clients such as Anthropic, OpenAI, and Apple, Google is expanding its TPU deployment, with plans to ship 6 to 7 million units in 2027—surpassing previous market expectations. Crucially, over 95% of this volume will be powered by Broadcom’s next-generation 3nm chip, 'Sunfish' (codename Hellcat), underscoring Broadcom’s formidable market dominance.

Delays in Internal Programs and Supply Chain AdvantagesIn contrast, Google’s internal chip program, 'Zebrafish', has faced multiple delays and is expected to secure its first prototypes only by the end of this quarter or early next. This timeline lags at least 18 months behind Broadcom’s Sunfish, which completed tape-out in the first half of last year and has already secured a multi-billion dollar backlog. Furthermore, given the extremely tight supply chain for HBM and advanced packaging (CoWoS), it is highly unlikely that Google’s late-entry internal chip will secure meaningful volume within 2027. Broadcom has already commenced design work for Google’s next-gen 2nm TPU aimed at 2028 production, maintaining a 1.5-generation lead over both competitors and internal initiatives.

Investment Thesis: Market Underestimation and Overweight RatingThe market continues to underestimate Broadcom’s 30-plus years of ASIC leadership, its vast IP portfolio, and its proven execution in supporting Google’s cutting-edge silicon development. Additionally, Meta’s 3nm and 2nm programs are progressing as planned, contributing to a steadily growing AI-related backlog. Consequently, we maintain our Overweight rating, driven by Broadcom’s overwhelming technological superiority and market leadership. We recommend active accumulation at current price levels.

$AVGO


Summary: UBS: Sell Hanmi on HBM4 TCB share loss; Buy ASMPT/BESI as share gainers; sentiment positive for Teradyne, Advantest, Disco on HBM4 back-end spend.

ASMPT listed on Hong Kong Exchange 0522.HK

UBS: regarding HBM4 TCB bonding equipment

Hanmi, Hanwha may have both secured HBM4 TCB tool orders from SK Hynix

Pre-market yesterday, Hanmi disclosed having received HBM thermo-compression bonding (TCB) tool orders from SK Hynix (link) for a contract amount of Won9.7bn (ex. VAT) and duration till the end of 1Q26E. Given the size of order, we believe this may have been for c.3 units of HBM4 TCB tools. Based on our channel checks and industry conversations, we believe competitor Hanwha Semitech may have also secured TCB tool orders ‘of equivalent scale’ or c.3 units for HBM4 12Hi, suggesting a 50/50 split. With ASMPT also seeing renewed engagement to supply HBM TCB tools to SK Hynix (link, link), we believe all three vendors will be engaged in supplying HBM4 TCB tools to SK Hynix in 2026. Given our expectation of 2026 HBM4 TCB unit TAM for SK Hynix at c. 86 tools, we believe follow-up TCB orders may come through shortly (within 1Q26) as SK Hynix continues to ramp up capacity at M15X. Following orders for HBM TCB tools, we expect visibility may also soon extend to other areas of HBM back-end including dicing/grinding, descum, test etc.

HBM4 TCB tool specs largely unchanged vs HBM3E; any ASP uplift limited

In the case for HBM4 12Hi, SK Hynix will continue to adopt a flux-type TCB tool (based on advanced MR-MUF) – with TCB tool specs, we believe, largely unchanged in versus HBM3E 12Hi. This was enabled, we believe, due to SK Hynix in particular having been able to meaningfully improve/control TSV back-end yields for HBM3E allowing for extension of the same process/tools to HBM4. This suggests to us that 1/ we may see a more competitive set up for HBM4 TCB tools (lower entry barrier + time for competitors to catch up on offering) but also 2/ any potential ASP uplift on tool spec improvement for HBM4 may be challenging. This may also extend beyond MR-MUF type TCB tools to potentially NCF type TCB tools, as well where we believe ASMPT may be set to gain share at Micron at the expense of Hanmi.

Update on fluxless TCB and hybrid bonding adoption timing

Industry preparation for fluxless and hybrid bonding continues to progress though adoption timing remains uncertain. For SK Hynix, we believe advanced MR-MUF will remain the mainstream packaging solution till HBM4E (base scenario flux TCB while keeping fluxless ‘optionality’). Hybrid bonding adoption for SK Hynix, we believe, may only occur afterwards from HBM5 with Hanmi, Hanwha and BESI all engaged. For Hanwha, we believe the company is set to ship their 2nd gen hybrid bonder tools for eval to SK Hynix within 1H26. In the case for Micron, we believe the company is actively weighing the option of adopting fluxless TCB starting HBM4E, with Hanmi, ASMPT and BESI engaged. For Samsung, we believe both fluxless TCB and hybrid bonding tracks are in consideration for HBM4E with SEMES and BESI engaged for hybrid bonding.

Stock implications

Intensifying competition for HBM4 TCB tools into 2026 bodes negatively for TCB tool ASP/margins. Within UBS coverage, we see Hanmi (Sell) as most exposed given market share loss off high base vs potential share gainers ASMPT (Buy) / BESI (Buy). Broadening visibility on HBM4 back-end spend should be sentiment positive for test tool vendors Teradyne (Buy), Advantest (Neutral) as well as dicing/grinding vendors Disco (Neutral).


Broadening visibility on HBM4 back-end spend should be sentiment positive for test tool vendors Teradyne (Buy)


Summary: Bullish memory sector (Big 3): TSMC-like contract structures + disciplined capacity make current valuations absurdly cheap; market misprices structural change.

Dan wrote a good piece, but I see things differently on a few important points.

1. Buyer resistance to smartphone memory price hikes is largely confined to legacy memory like DDR4 — not memory broadly.

This distinction matters. It's true that some buyers have recently pushed back on price increases, but the target of that resistance has primarily been legacy memory like DDR4.

The market has been behaving rather abnormally of late. At one point, legacy memory like DDR4 was actually trading above DDR5 in price — a genuinely strange phenomenon. That distortion has since moderated as DDR5 prices have risen, but the spike at the time was difficult to explain through normal demand alone.

According to industry sources, a significant portion of the DDR4 price surge was attributable to Chinese stockpiling. That's what gave smartphone OEMs the room to respond — by downgrading specs on entry-level devices or trimming production volumes. In other words, there was flexibility on the legacy side.

DDR5 is a different story. As I noted in an earlier post, smartphone and PC makers accepted substantial DDR5 price increases in Q1 of this year, and even into Q2.

The implication is clear: DDR5 is not a negotiating target right now — it's closer to an essential input that buyers need to secure even at a premium.

What's more, flagship products built around DDR5 aren't easy to spec down. At most, a spec freeze is on the table.

I've also heard some buyers say they simply can't keep absorbing additional costs on legacy memory. What I failed to account for was that most market participants weren't drawing a clear enough distinction — that this dynamic was specific to legacy — and I didn't anticipate that gap in understanding.

2. Repeating a familiar playbook and adapting to structural change are two different things.

Dan portrayed investors who reflexively sell on spot price declines as sophisticated. I'd disagree.

Memory companies are no longer operating the way they used to. If anything, they're moving toward a model closer to what TSMC does — building out capacity after securing advance paymets and long-term demand visibility from key customers. Just a few days ago, Korean media reported that Samsung is in discussions to pursue prepayment-based agreements with the likes of Microsoft.

And yet the market still treats memory companies as textbook cyclicals. Even as contract structures and demand visibility that resemble TSMC's begin to emerge, the Big 3 trade at valuations that remain absurdly cheap by comparison.

Repeating the old playbook in a changed environment isn't sophistication — it's a failure to price in structural change.

I'm well aware of the counterargument. LTAs existed in prior cycles, and many were torn up when downturns hit.

But the memory companies know that better than anyone.

There's no reason to think they don't want TSMC-like valuations. And precisely because of that, the incentive to avoid repeating the old pattern — overcapacity that destroys their own cycle — is far stronger than it's ever been. They're working considerably harder than most people realize to pursue disciplined expansion rather than reflexive overbuilding.

It's disappointing to see so many participants still running the same old framework, watching spot prices tick on a screen rather than paying attention to how the industry itself is changing on the ground.


Korean media reported that Samsung is in discussions to pursue prepayment-based agreements with the likes of Microsoft


Summary: Author endorses hedge fund review: TSMC capex surge signals 2026 AI cycle acceleration; buy TSMC, ASML, Japan equipment, and Asian AI hardware.

Translation: Review of the TSMC Earnings Call (from a Hedge Fund Manager's Perspective)

The most critical takeaway from this TSMC earnings call is not just the generic "AI is good" sentiment, but the fact that hard data proves "AI has redefined the system." With 4Q net income at $16 billion and a gross profit margin (GPM) of 62.3%, the company comfortably beat estimates. More importantly, the Capex guidance for 2026 has jumped to $52B–$56B (midpoint of $54B), representing a 31% YoY increase and sitting 17% above consensus. CFO Wendell Huang emphasized that the company will maintain "meaningfully high spending for the next three years."

The interpretation of these figures is straightforward. The market knows TSMC is typically not a company to over-invest without clear demand visibility. The fact that they are betting over $50 billion now for supply 2–3 years down the line suggests the AI cycle is not about a "peak debate" but rather a stage of "capacity and time constraints."

CEO C.C. Wei’s comment—"Our headache, if I may call it that, is the gap between supply and demand. We must work hard to bridge that gap"—reveals that fundamental physical constraints (cleanrooms, tools, power, and packaging) are determining the sector’s ceiling, rather than traditional cyclical signals like inventory or unit price. Thus, the focus shifts from "demand slowdown" to the "speed of supply catch-up."

TSMC is accelerating fab expansion in Taiwan and Arizona. Tool-in and installation for Arizona Fab 2 will proceed this year, with mass production (HVM) pulled forward to 2H 2027 due to customer demand. Wei sought to reduce the "US expansion = yield risk" premium by stating that everything in Arizona, including yields, is "very close to Taiwan."

Strategy-wise, capital is naturally gravitating toward "bottleneck locations" rather than just the "direction of demand." The core of 2026 lies not in total foundry volume, but in where the $52B–$56B Capex flows: 70–80% is allocated to advanced nodes (7nm and below), with the rest distributed among advanced packaging, testing, masks, and others. The moment the CFO mentioned that "tools are becoming more expensive and complexity is increasing," the supply chain shifted from a simple leverage play to a long-term game of "securing capacity and improving productivity."

An interesting tension arose when Wei dismissed two major market fears for the new year:

1. Memory Chip Shortage: Wei stated that a "memory chip crunch does not affect TSMC at all," noting that their revenue increasingly stems from high-end AI hardware and premium smartphones, which are less sensitive than low-end electronics. The platform mix supports this: 4Q revenue saw HPC (essentially AI) at 55%, Smartphones at 32%, and Others (Auto, etc.) at 13%. Despite an 11% growth in smartphones, HPC grew by 48% in 2025, dominating the landscape.

2. Power Constraints in AI Data Centers: Wei noted they have audited the supply chain down to racks and cooling, stating, "So far, so good." He emphasized that Cloud Service Providers (CSPs) are "very smart" and that their data center investments are operating on plans designed 5–6 years ago. In essence, power and memory constraints act as a "brake" for low-end and commodity products, while high-end products absorb the shock through pricing and mix.

The implications extend beyond TSMC. High-end smartphones have low demand elasticity despite rising memory costs. This context suggests robust demand for the iPhone 17 Pro/Pro Max, while low-end devices may suffer. Investment strategies must move past the simple "Memory Shortage = Industry Downside" frame and instead bifurcate the winners (Premium phones, AI accelerators, networking, advanced packaging) from the losers (price-sensitive consumer electronics).

Finally, the core of this call was found in Wei’s attitude. While acknowledging the risk—"Is AI demand real? I am also very nervous. Investing $52B–$56B could be a disaster if we aren't careful"—he confirmed demand signals by meeting with "customers' customers." He drew laughs by adding, "I checked their financials. They are very rich."

This explains why data is projecting supply needs for 2028–2029. Since fabs take 2–3 years to build, today’s investment targets 2028. From the moment Wei mentioned they are "looking at 2028 and 2029 supply," the debate shifted from short-term demand to "how such long-term visibility is even possible." Notably, while 2nm ramp-up may dilute margins by 2–3% in 2H 2026, the 1Q GPM guidance of 63–65% (vs. 59.6% estimate) suggests margins are shifting toward a structural upper bound rather than being impaired.

In conclusion, the strategy isn't just about buying TSMC; it's about recognizing that 2026 is an acceleration of the AI cycle, not a deceleration. Capital should follow the path where profits migrate: utilization, efficiency, node transition, and packaging. The strengthening TWD, foreign inflows, and the positive reaction of ASML and Japanese equipment makers indicate that this guidance is a signal resetting the risk appetite for the entire Asian AI hardware asset class. 2026 tech is not about "whether demand exists," but about "how slowly supply can catch up."

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I happened to come across a review of today’s TSMC call by a Korean hedge fund manager, and there were a few points that really resonated with me, so I’m sharing them here.

Source: https://t.co/BotS7dza5W


the positive reaction of ASML and Japanese equipment makers indicate that this guidance is a signal resetting the risk appetite for the entire Asian AI hardware asset class


Japan semi equip basket: Advantest, DISCO, Shin-Etsu, SCR


Capital should follow the path where profits migrate: utilization, efficiency, node transition, and packaging

AI hardware proxied by semiconductor ETFs SMH/SOXX


Summary: Bullish Nittobo as a beneficiary of quartz cloth / Low Dk glass substrate trend.

It seems Q Glass is really a nightmare for drills.

6. From a manufacturability and commercialization perspective, the quartz cloth used in M10 may be replaced with Low Dk-2 Glass.


Memory prices are expected to continue rising throughout the year, driven by robust demand from AI customers... No customer is able to fully meet their memory demand this year, and Hynix's own DRAM and NAND inventories remain very lean at approximately 4 weeks—reinforcing supplier leverage. I really like how it dispels concerns about double ordering.

Summary: Bullish SK Hynix: memory prices rising all year on AI demand + lean inventories + supplier leverage; double-ordering concern dispelled.

structural marker; pre-classified as canonical yfinance ticker

SK Hynix disclosed the following at today's virtual group meeting with Goldman Sachs:

1. Memory prices are expected to continue rising throughout the year, driven by robust demand from AI customers—underpinned by advancements in AI services—coupled with limited supply growth.

2. A particularly noteworthy point: customers recognize that near-term production ramp-ups are difficult, and understand that double-ordering only drives price increases rather than higher allocations.

3. While there is potential for despeccing among PC and mobile customers, constrained supply growth is expected to offset this.

4. Server customer inventories have reached healthy levels, while PC and mobile customer inventories are on a declining trend.

5. No customer is able to fully meet their memory demand this year, and Hynix's own DRAM and NAND inventories remain very lean at approximately 4 weeks—reinforcing supplier leverage.

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I really like how it dispels concerns about double ordering.


Summary: Re-entered NVDA at $187 avg after selling at $204; initiated new long INTC position at $36 avg.

I sold Nvidia at 204 dollars on November 4, and got back in yesterday at an average price of 187 dollars.

On December 30, I also took a position in Intel at an average price of 36 dollars.

$NVDA $INTC


I also took a position in Intel at an average price of 36 dollars


Raising Target Price to $308 ... Buy, AMD US ... we are raising our 2025/2026 EPS estimates by 1% and 2%, respectively

Summary: GF raises AMD PT to $308 (Buy) on CPU price tailwinds, strong server demand, and $17.8B AI revenue estimate; also carries Buy on NVDA.

《GF Overseas Electronics & Communications》
AMD (Buy, AMD US): Performance Outlook, Tailwinds in CPU and GPU

Raising Target Price to $308: Since last November, AMD's stock has been consolidating, but it rebounded 15% in the past week, mainly driven by reports of CPU price increases. We agree with this, due to substrate shortages and tight wafer capacity. At the same time, we expect server CPU demand to remain strong, with AMD's share gain momentum continuing. For AI, we still maintain a higher-than-consensus revenue estimate of $17.8 billion, primarily driven by the MI455X and the resilient MI325X, while also anticipating potential upside as we have removed Meta's Iris from our ASIC expectations. Therefore, we believe the company is on track to achieve its guidance of data center revenue CAGR exceeding 60%. In the short term, we expect the company to provide optimistic guidance at its earnings call on February 3. Considering the short-term outlook and higher CPU prices, we are raising our 2025/2026 EPS estimates by 1% and 2%, respectively. We are shifting our valuation benchmark from 38x 2026E to 33x 2026E/2027E EPS to capture the long-term CAGR momentum, resulting in a higher target price of $308.

AI Demand/Supply Tailwinds and Meta ASIC Progress: In the short term, we believe AI revenue will be supported by MI325X, based on an estimated 160,000–180,000 units for 2H26 supply chain buildout. If the Chinese government approves imports of NVIDIA's (Buy, NVDA US) H200 and AMD's MI325X, there could be upside potential in 2Q26. For 2026, we maintain our $17.8 billion estimate (compared to $6.3 billion in 2025), mainly driven by: 1) Solid customer pipeline for MI455X, primarily from OpenAI's first 1GW project, followed by Oracle, Meta, Microsoft, etc.; 2) 90,000 AI GPU CoWoS capacity in 2026, with MI430X/MI455X accounting for approximately 470,000 units; 3) Helios progressing as planned, with an expected ramp-up of about 4,000 racks in 2026; 4) We have removed Meta's Iris ASIC project from expectations due to design/ramp complexity, while retaining the high-end/testing project for Iris Plus—this implies upside potential in AMD's allocation at Meta.

CPU Price Increase Tailwinds, Server Demand, and 2nm Process: Objectively speaking, PC demand may remain soft due to rising memory prices, yet the supply chain continues to manage inventory and profitability. On January 15, reports emerged that AMD will raise prices for its new PC CPUs to reflect substrate costs and tight wafer capacity—we expect this round of PC CPU price increases to be 10–15%. For servers, strong AI demand has already driven demand for general-purpose servers; meanwhile, TSMC's N3 capacity remains tight, so we do not rule out the possibility of server CPU price increases. For AMD, the Venice CPU ramp is progressing as planned, which will benefit from N2 and CoWoS to boost ASP. To alleviate wafer supply concerns, we maintain our view that server CPUs may adopt Intel's 14A process by 2028.


Samsung Electronics and SK Hynix's combined Q1 operating profit could exceed USD 20 billion, surpassing TSMC

Summary: BofA's Simon Woo bullish on Samsung and SK Hynix: combined Q1 OP could top $20B on rising DRAM and NAND prices.

Bank of America's Simon Woo, in his latest memory report, argued that if improved optimism on not only DRAM but also NAND is fully reflected, Samsung Electronics and SK Hynix's combined Q1 operating profit (OP) could exceed USD 20 billion (over KRW 30 trillion), surpassing TSMC. He added that with memory chip prices expected to rise further in April, each Korean memory company's quarterly operating profit could easily exceed USD 20 billion or KRW 30 trillion.


each Korean memory company's quarterly operating profit could easily exceed USD 20 billion or KRW 30 trillion


significant upside potential for demand … the global NAND supply shortage is expected to intensify further

Summary: Shares Citi view that ICMS-driven NAND demand (2.8%→9.3% of global demand) will tighten supply and create significant upside; tags SNDK as beneficiary.

Citi: We estimate that approximately 1,152TB of additional SSD NAND will be required per Vera Rubin server system to support NVIDIA's ICMS operations.

Accordingly, assuming Vera Rubin server shipments of 30,000 units in 2026 and 100,000 units in 2027, NAND demand driven by ICMS is projected to reach 34.6 million TB in 2026 and 115.2 million TB in 2027.

This represents 2.8% of expected global NAND demand in 2026 and 9.3% in 2027, a meaningful scale that is likely to create significant upside potential for demand.

As a result, with this structural demand increase factored in, the global NAND supply shortage is expected to intensify further.

$SNDK