Equity research

Major news on CXMT & YMTC all at once.

1. CXMT plans expansion that may more than double monthly wafer output

2. CXMT inks five-year ByteDance supply agreement valued over $7 billion.

3. Trump administration split on additional limits for CXMT, YMTC

4. YMTC executives pushing internally for trillion-yuan IPO valuation target

5. CXMT, YMTC in some cases charge more for memory chips than Samsung, SK Hynix

6. Apple sought assurances CCXMT won't be added to U.S. entity list.

A Senior Executive at Supply Chain Logistics Company on fiber cable:

"We're seeing a huge restriction in fiber cable availability, which that's a very critical part of the network and builds just cannot happen if that fiber is not available. That's for sure creating some concern out there."

Market Demand and Supply Overview

> Seasonal Demand: Demand for fiber buildouts is strong, following the typical seasonal peak that runs from late March/April through the end of the summer.

> The Primary Bottleneck: Bulk fiber cable is severely restricted due to high demand from the data center and hyperscale environment (such as Amazon, Google, and Meta), leaving less capacity for traditional telecom builds.

> Other Components: Aside from fiber cable, other products and miscellaneous items (such as conduit and hand tools) are experiencing no supply or lead time issues.

Impact Across Telecom Tiers

> Tier 1 Providers Protected: Major service providers like AT&T, Verizon, Brightspeed, and Lumen are largely insulated from shortages because they have direct contractual allocation programs with major manufacturers.

> Tier 2 & Tier 3 Providers Impacted: Smaller regional providers (such as Cincinnati Bell or Consolidated Communications) are facing significant challenges, with an estimated 25% of their builds currently impacted or pushed out due to a lack of available fiber.

Manufacturing Shifts (Corning and CommScope)

> Corning's Hyperscaler Focus: Corning has locked up mega-deals with hyperscalers like Amazon Web Services, Google, and Meta, turning its focus toward data center customers.

> CommScope Supply Disruption: Corning cut off its long-standing partnership of supplying raw glass to its competitor CommScope to satisfy its own customer demands, heavily disrupting CommScope and causing lead times to stretch out by months.

> Capacity Timeline: Industry participants are advised that it will take 1.5 to 2 years for new U.S. manufacturing capacity to come online to meet the surge in demand.

Active Electronics Bottlenecks

> Secondary Concern: Active network equipment requiring memory chips—sourced from vendors like Adtran, Nokia, and Calix (including ONTs, OLTs, CPE, and servers)—represents a growing but secondary bottleneck.

> Cost and Lead Times: These active components are facing double-digit cost increases and doubled lead times, though they are not currently causing widespread project cancellations.

$Corning(GLW.US)

Former Strategic Sales & Business Development Manager at Intel:

"Google TPUs are trying to beat that performance per token with 30-40% less power requirement compared to Nvidia, so that's the main point... the performance per token will increase probably by 40x to 50x in two years."

> Packaging Bottlenecks & Reticle Size Limits: TSMC's Chip-on-Wafer-on-Substrate (CoWoS) holds proven yields but is structurally capped at 6.5x to 7.5x reticle sizes. This creates a bottleneck as AI accelerators demand larger dies, more computing cores, and expanded high-bandwidth memory (HBM) stacking.

> Intel's EMIB-T vs. TSMC: Intel's EMIB-T (Embedded Multi-die Interconnect Bridge with Through-Silicon Via) offers projected yields above 90% and is estimated to be roughly 30% lower in cost compared to CoWoS. However, it remains commercially unproven against the 95% threshold required by major customers like Google. Furthermore, Intel faces packaging capacity constraints compared to TSMC's massive expansion.

> Cost Breakdown: Advanced packaging costs typically run under $5,000 to $7,000, representing a fraction of a total system-on-chip (SoC) cost that can reach around $60,000 for advanced 3.5D setups.

> Google's TPU Roadmap: Google is pursuing an aggressive trajectory targeting 30% to 40% lower power than Nvidia alongside a 40x to 50x increase in performance-per-token within two years. This push is driving faster dual-track adoption of 3.5D packaging solutions using small outline integrated circuits and Intel's EMIB-T.

> Glass Substrates Timeline: Meaningful mass production of glass core substrates for high-volume AI accelerators is realistically expected to land around 2029. Consequently, near-term EMIB-T adoption relies on conventional organic substrates.

> Foundry Preferences (14A vs. 18A): If Intel's packaging solutions successfully mature, large hyperscalers are more likely to lean toward Intel's 14A node rather than 18A. This preference is driven by 14A's power and area metrics being comparable to TSMC's N2P process, coupled with potential cost savings and relief from TSMC's allocation bottlenecks.

$Alphabet(GOOGL.US) $Taiwan Semiconductor(TSM.US) $Intel(INTC.US)

Former Senior Director, SoC Design & Development, Data Centre & AI Group at Intel:

"USD 120bn server CPU TAM forecast by 2030 is considered conservative, with physical AI, edge inference and agentic orchestration potentially driving 30-40% upward revision within one year."

> Market Split & AMD's Rise: The x86 server CPU market is currently split roughly 60/40 between x86 and Arm. Within x86, AMD commands nearly 50% of the server segment following years of historical Intel dominance.

> Agentic AI & CPU-to-GPU Ratios: Agentic AI workloads and mixture-of-experts models are dramatically reversing the historical training-phase GPU-to-CPU ratio (which favored GPUs heavily at 4:1 up to 8:1) back towards a 1:1 or 1:2 ratio, with expectations to hit 1:8 in favor of CPUs within a year due to intensive reasoning and orchestration demands.

> Conservative TAM Forecasts: The USD 120bn server CPU Total Addressable Market (TAM) forecast by 2030 is viewed as conservative. Physical AI, edge inference, and agentic orchestration could potentially drive a 30-40% upward revision within a year.

> Competitive Landscape (Venice vs. Diamond Rapids): AMD's Venice architecture (reaching 256 cores) provides it with an unofficial 12-month head start over Intel's Diamond Rapids, making AMD breaching a 50% x86 server share by the end of 2027 a realistic possibility.

> Intel's Structural Advantage: Despite operating as two distinct business entities, Intel’s tight internal coupling between design and manufacturing provides an inherent 20-30% architectural advantage once foundry execution and the 18A node stabilize.

> Arm's Core Demand Impact: Arm's CEO, Rene Haas, noted that Agentic AI is scaling CPU core demand up to 4x higher, pushing up to 120 million cores per gigawatt.

> Supply Constraints: Current severe shortages—with AMD sold out through the end of 2026 and lead times hitting 30-plus weeks, while Intel underships true demand by roughly 20%—are tied to the entire integrated ecosystem of advanced front-end logic wafer capacity and tied-in packaging capacity rather than memory.

> Volume vs. ASP Strategy: About 66% of AMD's server CPU growth comes from unit volume increases rather than Average Selling Price (ASP) expansion, contrasting with Intel's historical high-ASP strategy.

$Intel(INTC.US) $AMD(AMD.US)

Former Senior Finance Role at Nebius Group says,

"The problem of CoreWeave is their business model is sign a contract and then allocate data centres, then allocate GPUs and buy the GPUs they don't have and then start project management. The whole cycle within CoreWeave is about 24 months. The majority of their revenue, maybe 95% or more is still Hopper revenue."

"There are neoclouds like Nebius who do it a bit different. We were building data centre capacity, buying GPUs without knowing to whom we're going to sell it to. Coreweave only start working when they have a signed contract and then they're going to look for the data centre capacity and the GPUs, which is fully hedged. It's like without risk, you have always a coverage by a five-year contract. The disadvantage is you can't monetise fast."

> Revenue per Gigawatt Trends & Waves: Revenue per gigawatt does not decline in a straight line; instead, it moves in cycles tied to GPU generations. Prices spike at the launch of a new GPU generation (like Blackwell or Vera Rubin) and then gradually decrease over time within multi-year contracts. CoreWeave’s revenue per gigawatt has decreased over recent quarters because older contracts signed during peak Hopper pricing are rolling alongside newly added capacity at lower rates.

> Business Model Differences (CoreWeave vs. Nebius):

CoreWeave follows a risk-hedged model where they sign multi-year contracts (typically five years) with major customers first, and then procure data center space and Nvidia GPUs.

Nebius often builds out data center capacity and secures hardware proactively before locking down every final end customer, allowing them to monetize faster and cater to urgent capacity needs or mid-sized enterprises.

> Long-Term Outlook on Hyperscalers: Nebius anticipates that hyperscalers (like Microsoft and Meta) will only utilize neoclouds as stopgaps for five to eight years until they fully internalize their own infrastructure. Consequently, Nebius is positioning itself as a "mini hyperscaler" targeting enterprises, European entities seeking data sovereignty away from U.S. jurisdiction, and diverse corporate clients.

> Memory Pricing & Unit Economics Impact: Memory prices (such as high-bandwidth memory) cannot typically be locked in when striking multi-year customer agreements. However, memory accounts for a relatively small percentage of overall unit economics (e.g., roughly 2% to 3% historically), meaning even a 2x-3x price spike only minorly impacts contribution margins. Neoclouds offset these headwinds through advanced natural air and water cooling (saving up to 30% on power costs) or by slightly extending GPU depreciation timelines (e.g., from 5 to 5.5 or 6 years).

> Data Center Outfitting Timelines: For a standard 50MW greenfield powered shell, outfitting and bringing servers online takes about two months, while larger 300MW sites with roughly 90,000 GPUs take 3 to 4 months. While moving from Hopper to Blackwell requires similar configuration windows (around 6 to 10 weeks), upcoming Vera Rubin chips are vastly more powerful and thermally intense, meaning older colocation sites will struggle to handle them without expensive retrofits.

> Financing & Profitability Realities: CoreWeave utilizes heavy debt financing (such as recent deals at a 9.5% interest rate), creating a large interest expense burden. While CoreWeave anticipates operating margins jumping significantly as new capacity comes online, the expert is skeptical of rapid jumps (such as 1% to 16% in the short term) given high capital costs and market impatience regarding profitability.

> GPU Utilization Targets: Neoclouds actively target high capacity utilization rates exceeding 90% (often 94% to 95%) on external customer data centers to maintain competitive pricing against hyperscalers, who typically settle for 75% to 80%.

$Nebius(NBIS.US) $Coreweave(CRWV.US)

Texas Instruments $Texas Instruments(TXN.US) doubled DC sales YoY and grew gross margins by 330 bps QoQ. FCF exploded with cut back in CapEx, but this is one of the few companies that was ahead of the curve with all their CapEx spend to get capacity ready.

They mentioned in the CC that power semis content will only grow as more DCs get built and come online.

They had a great report despite the AH reaction, and expect data center sales to be strong for the foreseeable future.

Power semis look good while many are ignoring them for other names.

$Infineon Technologies(IFNNY.US) $ON Semiconductor(ON.US) $STMicroelectronics NV(STM.US) $Analog Devices(ADI.US)

BofA: Anthropic & AMD Deal

Key Takeaways from the Anthropic Partnership

> Partnership Details: AMD announced a partnership with Anthropic to deploy up to 2GW of AMD MI450 Series AI GPUs starting in the first half of 2027.

> Financial Commitments: AMD committed to a $5 billion strategic equity investment and will use Anthropic's Claude in research and development (R&D) projects.

> Expanded Engagements: This deal expands AMD's MI engagements to four major customers: Anthropic, OpenAI (likely via Microsoft cloud), Oracle, and Meta.

> Financial Upside: The engagement indicates at least a $10 billion to $15 billion upside to current consensus expectations of $35 billion to $40 billion for CY27 MI sales.

Analyst Event & Product Outlook

> Advancing AI Event: Pre-announcements involving Microsoft and Anthropic serve as incremental positives ahead of AMD's analyst event.

> Server CPU Roadmap: The event is expected to spotlight the server CPU roadmap (specifically upcoming Venice CPUs) and how they compete against NVIDIA's Vera in the agentic AI era.

> CoWoS Supply & Sales Potential: Latest TSMC Chip-on-Wafer-on-Substrate (CoWoS) supply estimates point to roughly 1.4 million MI450 Series GPU units in CY27, which could surpass $40 billion in sales assuming a $30k average selling price (ASP).

$AMD(AMD.US)

Manager at a Global Distributor on optical component demand:

"Overall optical components market exceeded our expectation because we were not projecting such a high growth rate for us. Customers were accelerating transition from 400G to 800G."

Vendor Growth Metrics:

"Between Coherent and Lumentum, Coherent performed the strongest."

> Coherent: Saw estimated demand growth increase by 8% quarter-on-quarter and 25% year-on-year, driven by 800G optical components, high-performance lasers, and AI cluster interconnected solutions. Coherent dominated in meeting increased optical bandwidth requirements per GPU cluster, high-fiber connectivity requirements. Overall performance was supported by increased networking investments from hyperscalers.

> Lumentum: Experienced growth in the range of 5% to 7% quarter-on-quarter, or 18% to 22% year-on-year, bolstered by cloud and AI demand growing at 25% to 35% year-on-year.

Speed Segment Breakdown:

> 400G: Remains flat or exhibits low-single-digit growth year-on-year, serving as a volume product for traditional cloud and enterprise deployments.

> 800G: Acting as the core growth engine for AI infrastructure, seeing 50% to 100% year-on-year growth.

> 1.6T: Moving from early evaluation into initial procurement or production validation testing (PVT) phases by hyperscalers, with a 30% quarter-on-quarter demand growth from a small base and a commercial ramp-up expected by 2027.

> 3.2T: Confined to prototype and roadmap discussions with fewer than 10 global customers, contributing less than 5% of current optical revenue.

Pricing & Margins:

> Average selling prices (ASPs) for 800G AI optic modules saw a 10% increase year-on-year driven by product mix and tight supply.

> Quarter-on-quarter ASP growth for 800G is tracking at 2.5% to 5%, while high optical fibers are up 1% to 4%.

> Distributor margins are tightening on mature optical products and telecom optics due to increased competition and price erosion, while high-speed AI optics maintain stability.

Competitive Dynamics & Contracts:

> Chinese vendors (such as InnoLight, Eoptolink, and Accelink) are aggressively pricing and winning share in cost-sensitive, high-volume segments like 400G and pluggable optics, primarily displacing Lumentum within China.

> Coherent typically engages hyperscalers on 1- to 3-year multi-year contracts for Al optical products, while Lumentum primarily secures 1- to 2-year strategic agreements (such as for EML lasers).

$Coherent Corp.(COHR.US) $Lumentum(LITE.US)

Former Senior Post Silicon Validation Engineer at NVIDIA on CPO:

"Eventually, CPO is where the technology is converging and going to converge. Whoever comes with a reliable CPO product first, they will see a huge demand. There is absolutely no doubt about that. All these NPO and LPO are temporary compromise, for the lack of a better word."

Current State & Commercial Timeline

> Experimental Phase: CPO technology is currently in pilot and experimental stages, with no commercial products available yet.

> Timeline for Adoption: Initial CPO products are tentatively expected around 2028, though unexpected delays could occur due to major, unresolved engineering hurdles.

> Demand Dynamics: Once CPO is successfully and reliably commercialized, demand will experience an explosive surge, limited only by production supply rather than market interest.

Key Technical Hurdles

> Thermal Management: Compute chips generate kilowatts of heat, whereas optical engines are exceptionally sensitive to temperature changes (even minor shifts can alter laser wavelengths).

> Glass Substrates & Via Drilling: Transitioning from traditional organic substrates to glass is necessary for scale, but drilling microscopic, precise vias into glass without causing micro-cracking remains a massive challenge.

> Laser Integration: Internal laser setups face severe thermal interference from compute chips, while external laser setups struggle with high optical loss when trying to focus light onto extremely thin substrate layers.

Competitive & Technological Landscape

> Interim Solutions: Technologies like NPO (Near-Packaged Optics) and LPO (Linear Drive Pluggable Optics) are viewed as temporary compromises; once CPO matures, the industry will fully converge on it, causing demand for traditional pluggables to decline.

> Key Players: Major industry stakeholders—including TSMC, Samsung, Intel, and Amkor—are heavily investing in packaging R&D, with TSMC viewed as a dominant pioneer via solutions like CoWoS and CoPoS.

> Laser & Component Suppliers: Lumentum is positioned well ahead of competitors in the optical landscape, supported by strategic partnerships and investments (such as NVIDIA's capital backing).

Bill of Materials (BOM) Breakdown

> Packaging: Forms the largest share of the CPO BOM (~50% to 55%) and represents the hardest problem to commoditize.

> Light Sources / Lasers: Accounts for roughly one-third of the BOM.

> Cooling Solutions: Makes up the remaining portion, playing an equally vital role due to severe thermal constraints.

Optical Circuit Switching (OCS)

> Role in Future Infrastructure: Once signals are converted to light via CPO, OCS will become critical to route traffic dynamically across large clusters of GPUs without re-converting signals back to electrical (which destroys power-saving benefits).

> Current Limitations: Existing OCS solutions lack packet-decoding capabilities and rely on rigid, round-robin scheduling schemes, meaning optical switching technology must heavily evolve alongside CPO.

$Marvell Tech(MRVL.US) $Amkor Tech(AMKR.US) $NVIDIA(NVDA.US) $Taiwan Semiconductor(TSM.US) $Marvell Tech(MRVL.US) $Lumentum(LITE.US) $Intel(INTC.US) $Applied Optoelectronics(AAOI.US)

Former manager at Google on data center interconnect market and spending:

"Your neoclouds, their spend for DCI is double because they don't have that infrastructure in there yet. They're brand new. Some of these guys have only been around five years. They don't have a network between all their buildings yet. They're building that out. Their spend is double."

> 2026 Total Addressable Market (TAM): Estimated at USD 10 billion to USD 15 billion in total DCI orders for 2026, encompassing coherent optical modules, line systems, switches, and software at the system level.

> Long-Term Growth: Most estimates project a Compound Annual Growth Rate (CAGR) of 20% to 30% over the next 3 to 5 years, with the low end around 15% to 20% and the high end around 30% to 35%. The expert suggests the industry could scale up to a USD 30 billion TAM by 2030.

> DCI vs. Scale-Across: The expert highlights that traditional DCI was for redundancy and backup, but AI has created a new category called "scale-across". Scale-across connects multiple buildings within a mega-site campus (e.g., five 200MW buildings roughly 2,000 meters apart) and represents about 50% of the 100GW of new capacity coming online by 2030. True DCI connects data centers hundreds of kilometers apart (or in the 10km to 40km optimal range for AI clusters) due to power constraints and model training scale.

Executive at POET on $Applied Optoelectronics(AAOI.US):

"AOI having their own laser source is a huge differentiator...The laser supply will continue to be constrained. The future networks, the laser power has to increase significantly."

> 800G optics are positioned to remain a dominant mainstream workhorse for the next 12 to 24 months (with a solid 2 to 4-year total lifecycle), giving AOI a durable, multi-year runway before 1.6T fully takes over.

> Owning in-house indium phosphide laser fabrication serves as a vital competitive differentiator and moat, insulating AOI from industry-wide component shortages and positioning them ideally for future high-power architectures like ELSFP (External Laser Small Form-Factor Pluggable).

> Supply constraint in transceivers expected to last several more years.

According to a senior engineer at Inphi:

> Hyperscalers prefer to stay on 800G as long as possible to maximize existing infrastructure investments unless specific inference workloads (like long-context or domain-specific enterprise models) necessitate a faster migration to 1.6T.

>While some anticipate 3.2T deployment by late 2028, a true majority market field deployment is more realistically expected closer to 2030.

> Regarding Credo, the expert notes that the company operates in a similar space to Marvell's scale-up segment and achieved major success by dominating the active copper cable market with a well-timed solution after nearly failing in the past. Many of Credo's engineers previously worked within the expert's group at Marvell, and they are recognized as having strong engineering capabilities. Credo initially capitalized because Marvell's product management and roadmap focus were directed toward optical connectivity rather than that specific copper segment. However, the expert believes that Marvell's next-generation offerings position them on par or ahead in the ongoing race, even though Credo will not easily relinquish its dominant position.

$Marvell Tech(MRVL.US) $Credo Tech(CRDO.US)

BofA: China Semiconductors

> Shift to System-Level Supernodes: China's leading AI accelerator and infrastructure vendors are shifting focus from standalone chip performance to system-level integration through broad product launches of rack-scale supernodes ranging from 64 cards to over 1,000 cards (e.g., Huawei and Biren architectures). This strategy helps offset individual chip performance gaps via higher density, faster interconnects, and parallel computing.

> PCle Switch Demand Growth: Most supernode compute trays feature a high XPU-to-switch ratio of 2:1 (two PCIe switches for every four GPUs), driving meaningful demand for PCIe switches to handle increased density and complex I/O configurations within compute trays.

> Expansion of Edge AI and AIoT: Edge AI is expanding past smartphones and PCs into broader AIoT categories like AI glasses, toys, audio products, vehicle boxes, industrial terminals, and robots. Architectures combining host processors with edge AI coprocessors (such as Rockchip's dual-chip design) are raising semiconductor content value per device.

> Implications of Kimi K3: Moonshot AI's launch of Kimi K3 validates sustained infrastructure demand with its 2.8-trillion-parameter Mixture of Experts (MoE) architecture, native multimodal capabilities, and 1M-token context window.

> Increased Hardware & Memory Demands from K3: K3's scale increases high bandwidth memory (HBM) capacity needs (requiring about 1.4TB of raw model storage before caches and buffers), while its jump to 896 experts and 16 active experts per token places a heavy premium on memory bandwidth, efficient expert routing, and scale-up interconnect efficiency.

$Micron Tech(MU.US) $DRAM $EWY

Yole Group: CPO Supply Chain

PIC design

Nvidia $NVIDIA(NVDA.US)

Broadcom $Broadcom(AVGO.US)

Marvell $Marvell Tech(MRVL.US)

Lightmatter

Celestial AI

Ayar Labs

Enosemi

ASIC & xPUs design

Nvidia $NVIDIA(NVDA.US)

Broadcom $Broadcom(AVGO.US)

Marvell $Marvell Tech(MRVL.US)

Intel $Intel(INTC.US)

AMD $AMD(AMD.US)

MediaTek $2454.TW

Laser

Lumentum $Lumentum(LITE.US)

Broadcom $Broadcom(AVGO.US)

Coherent $Coherent Corp.(COHR.US)

Sivers Semiconductors $SIVERS SEMICONDUCTORS AB(SIVEF.US)

Scintil Photonics

Scape Photonics

Quintiquent

Foundries

TSMC $Taiwan Semiconductor(TSM.US)

SilTerra - subsidiary of Dagang NeXchange $4456.Kl

NSTIC

IMEC

Leti

ITRI

GlobalFoundries $GlobalFoundries(GFS.US)

SOI wafer & Epi-wafer

Soitec $SOI.PA

Shin-Etsu Chemical $4063.T

LandMark Optoelectronics $3081.TWO

IQE $IQE.L

Shanghai Simgui Technology - subsidiary of National

Silicon Industry Group $688126.SS

Sumitomo Electric $5802.T

VPEC $2455.TW

AXT $AXT(AXTI.US)

Packaging / Assembling / Testing

ASE Holdings $Advanced Semiconductor Engineering(ASX.US)

Foxconn $2317.TW

Fabrinet $Fabrinet(FN.US)

SPIL - subsidiary of ASE Holdings $Advanced Semiconductor Engineering(ASX.US)

ShunSin Technology $6451.TW

Amkor Technology $Amkor Tech(AMKR.US)

Jabil $Jabil(JBL.US)

JCET $600584.SS

Teradyne $Teradyne(TER.US)

FormFactor $Formfactor(FORM.US)

EIC, Retimers, SerDes, PHY

Marvell Technology $Marvell Tech(MRVL.US)

Credo Technology $Credo Tech(CRDO.US)

MACOM Technology $Macom Tech(MTSI.US)

Semtech $Semtech(SMTC.US)

Alphawave Semi - part of Qualcomm $Qualcomm(QCOM.US)

Astera Labs $ALLAB

System / Equipment

Nvidia $NVIDIA(NVDA.US)

Micas Networks

Ruijie Networks $301165.SZ

Cisco Systems $Cisco(CSCO.US)

Inventec $2356.TW

Dell Technologies $Dell Tech(DELL.US)

Hewlett Packard Enterprise $Hewlett Packard Enterprise(HPE.US)

Wistron $3231.TW

Wiwynn $6669.TW

Connectors & Fibers

Molex

Samtec

Corning $Corning(GLW.US)

Yangtze Optical Fibre and Cable (YOFC) $6869.HK

US Conec

TE Connectivity $TE Connectivity(TEL.US)

Sumitomo Electric $5802.T

Hengtong Optic-Electric $600487.SS

Luxshare ICT $002475.SZ

End customers

AWS $Amazon(AMZN.US)

Microsoft Azure $Microsoft(MSFT.US)

Meta $Meta Platforms(META.US)

Tesla $Tesla(TSLA.US)

Tencent $Tencent(TCEHY.US)

ByteDance

OpenAI

xAI

Non-exhaustive list.

Supply shortfall is a big deal in optical components for CPO, says a Marvell engineer.

"Demand is enormous."

For instance, this year’s highest shipment volume is for 800G optical modules, with demand exceeding 80 million units, yet only about 60 million units can be produced, which represents the total available production capacity.

The demand for 1.6T modules this year may exceed 30 million units, but only slightly over 20 million units are likely to be delivered ultimately.

Next year, the demand for 800G optical modules is projected to be around 120 million-130 million units. The situation may improve slightly as all Chinese manufacturers are expanding production capacity and are expected to gradually catch up with demand.

However, he states that price increases for these modules are not expected year after year.

BofA: US Semis

> Chinese Open LLMs Drive Memory Demand: Recent open-source and open-weight model releases from China (such as Moonshot AI’s Kimi K3) do not threaten memory demand; rather, they reinforce a bullish thesis for memory and Micron Technology (MU).

> API Pricing vs. Hardware Requirements: Aggressive Chinese API pricing (up to 5-350x cheaper than Western models) reflects business-model choices and market-share strategies rather than lower hardware costs. For example, Kimi K3 still requires roughly 1.4 TB of High Bandwidth Memory (HBM) per serving instance.

> Non-Hardware Cost Advantages: Chinese model providers achieve cost advantages through architectural efficiency (such as Mixture of Experts [MoE] sparsity, MLA/hybrid attention, and native quantization) and infrastructure efficiencies (lower local electricity, labor, and land costs, alongside potential state-linked subsidies).

> Open Models Expand Memory Sockets: Unlike closed models where millions of users share a single centralized HBM pool, open-weight models are downloaded and self-hosted across thousands of separate enterprise, cloud, and sovereign endpoints, multiplying global memory and storage sockets.

> Scaling Outpaces Compression: While compression techniques and active-parameter sparsity reduce compute intensity, total model parameter sizes continue to scale up drastically (e.g., Kimi K3 reaching 2.8 trillion parameters), driving continuous demand for multi-tier memory hierarchies (HBM, DRAM, and NAND).

> Micron Technology (MU) Outlook: BofA reiterates its Buy rating on Micron with a $1,550 price objective, citing limited competitive threat from China's CXMT (which focuses on underserved consumer DRAM rather than advanced HBM3E/HBM4) and upcoming catalysts like the expiration of CHIPS Act buyback restrictions in late 2026.

$Micron Tech(MU.US) $DRAM $EWY

Meet Lee Seung-ho, a 24-year-old South Korean university student in Seoul, who lost all of his $202,515 earned via 500% margin loan. He plans to borrow again and return to the market the moment he has enough capital.

Within weeks, his account had fallen below his initial investment, leaving him under such strain that he said:

"I literally could not breathe."

Did he learn his lesson? Nope.

Highlights of an expert call from a Senior Director at ARM who was a Former Director at Western Digital regarding memory:

Unique Nature of the Current Memory Upcycle

> AI Data Center Expansion: Unlike past commodity-driven cycles (such as 2017–2018 or 2021–2022), this upcycle is uniquely propelled by sustained, multi-year AI data center buildouts from hyperscalers like Amazon, Microsoft, and Meta.

> Longer Cycle Duration: While past cycles typically flipped every 18 months, strong demand and constrained supply mean suppliers are already largely sold out through 2027, with market softening potentially expected around 2028 as new fabs come online.

Memory Bandwidth & Capacity Constraints (Training vs. Inference)

> Training Phase: Demand for HBM, LPDDR, and storage remains robust to support trillion-parameter models, though the baseline of model creation is becoming more established.

> Inference & The Agentic World: Inference is the primary revenue driver (exemplified by Micron's performance) and the "token economy". As multi-user agent systems scale, demand for faster token generation explodes, creating a "double whammy" of high demand for both GPU-attached HBM and CPU-orchestrated LPDDR bandwidth.

Supply Growth, Market Share, and Competitors

> Current Market Shares:

HBM Share: SK Hynix leads at approximately 58% to 60%, followed by Samsung and Micron at around 20% each.

DRAM Share: Samsung leads overall with roughly 40%, followed by SK Hynix (30%), Micron (20%), and others/China vendors (10%).

> Strategic Allocation: Vendors are balancing high-margin LPDDR capacity (driven by tight markets in smartphones and PCs) alongside HBM.

> The CXMT Threat: China's CXMT is expected to capture growing single-digit market share, primarily focusing on older nodes and LPDDR products for domestic data centers and smartphone brands (Xiaomi, vivo, OPPO).

Long-Term Supply Agreements (LTAs) & Pricing Outlook

> Shift in LTAs: Data center customers are pushing for 3-year or even 5-year LTAs to secure guaranteed supply, giving memory vendors stronger pricing power compared to historical 1-year agreements.

> Pricing Trajectory:

HBM/DRAM/NAND: Broad consensus expects prices to trend upward through 2026 and 2027 due to supply constraints.

HBM Pricing Trajectory: Blended average selling prices (ASPs) per stack are estimated around $330 to $360 for HBM3E in 2026, projected to rise to about $500 for HBM4 in 2027 as it gets introduced, and expected to soften slightly to around $450 for HBM4E in 2028 as supply catches up.

Company Optimism & Outlook

> SK Hynix: Highly praised for its market leadership in HBM, though integrating logic dies for future iterations poses a competitive frontier.

> Samsung: Viewed favorably due to an inherent margin and pricing advantage via its in-house logic foundry (Samsung Foundry), positioning it to potentially claw back some HBM share in the 2027–2028 timeframe.

> Micron: Expected to maintain its steady ~20% market share while benefiting strongly from current supply-constrained margins.

$Micron Tech(MU.US) $EWY $DRAM

Cantor Fitzgerald: Intel & AMD

Intel ($Intel(INTC.US))

> Outlook: Cantor maintains a "Neutral" rating with a $150 price target, noting that the risk/reward profile into earnings is skewed to the upside.

> Drivers: The company is expected to see a "modest beat/raise" in its upcoming results, fueled by demand for agentic AI and expansion in average selling prices (ASP) within its Client segment.

> Key Focus: Analysts are closely monitoring Intel's ability to outperform in a supply-constrained environment and how a potential decline in Client unit sell-through during the second half of the year will impact the company.

> Foundry Progress: There is optimism regarding progress on 18A-P and 14A nodes, alongside developments with both current and new customers. This is expected to lead to a forecast for significantly higher capital expenditure (Capex) in 2027.

AMD ($AMD(AMD.US))

> Upcoming Event: AMD will host its third annual Advancing AI 2026 Event on July 22–23 in San Francisco.

> New Tech: The company is expected to launch its next-generation Instinct MI450-series GPUs and Zen 6-based EPYC "Venice" processors.

> Infrastructure Growth: AMD is anticipated to provide updates on the third-quarter ramp of its "Helios" rack-scale platform and offer more context on a "rapidly expanding pipeline" of large-scale AI infrastructure opportunities.

> Market Projections:

AMD is expected to raise its view on the Server CPU Total Addressable Market (TAM) for 2030 to over $150B (up from $120B).

There is anticipation for an updated view on the AI Accelerator TAM, with potential upside to $600B–$800B in the 2029/2030 timeframe.

> Financial Outlook: Cantor believes AMD is positioned to guide for data center revenues to at least double in 2027. AMD remains a "Top Pick" with an "Overweight" rating and a $700 price target.

J.P. Morgan: TSMC CoWoS

CoWoS Capacity Expansion

> Capacity Increase: J.P. Morgan is raising its CoWoS capacity estimates for 2026–2028 by 1%, 9%, and 11% respectively.

> Targets: TSMC’s CoWoS capacity is expected to reach 115k, 190k, and 225k wafers per month (wfpm) by the end of 2026, 2027, and 2028.

> Strategic Shifts: TSMC is accelerating expansion at AP7 Phase 2 (reallocating capacity from SoIC to CoWoS) and is selectively outsourcing interposer manufacturing to Vanguard.

> OSAT Role: Capacity for CoWoS-like processes at Outsourced Semiconductor Assembly and Test (OSAT) providers is expected to reach 15k, 50k, and 85k wfpm by the end of 2026, 2027, and 2028, primarily to support server CPU packaging.

3D SoIC and CoPoS Outlook

> 3D SoIC: The capacity ramp is now more focused on 2028 (projected 65k wfpm) to align with mass adoption in accelerators. While 2027 may see a slight push-out to accommodate CoWoS demand, key customers like AWS, OpenAI, Meta, and NVIDIA (Feynman versions) are expected to adopt SoIC in 2028.

> CoPoS: This technology is currently in the engineering stage. Risk production is expected in early 2028, with mass production likely in 2029.

Customer Demand and Forecasts

> NVIDIA: CoWoS allocations for NVIDIA are rising, reflecting strong demand for new CPUs (Vera in 2027, Rosa in 2028) and accelerators. All NVIDIA accelerator and Co-Packaged Optics (CPO) products are on CoWoS-L at TSMC.

> AMD: Estimates for AMD are rising significantly in 2027–2028, driven by the Venice server CPU family, which will largely utilize a CoWoS-L-like process from ASE.

> CPUs and ASICs: Server CPUs (e.g., NVDA Vera, AMD Venice) have emerged as a primary upside catalyst for CoWoS demand in 2027. Other programs like Google’s TPU and AWS’s Trainium continue to ramp, though ASICs for companies like Microsoft and Meta remain at a smaller scale.

> Supply Chain Roles: AWS and Alchip are expected to remain the primary suppliers for the Neuronlink and UALink versions of Trainium 4. Marvell may take on some share for specific variants that utilize "NVLink fusion" based interconnects. While Trainium 4 volumes in 2028 are expected to be relatively flat compared to Trainium 3 volumes in 2027, the wafer consumption and average selling prices (ASPs) for these chips are expected to be significantly higher.

> 2027 as a Key Ramp Year: While TPU and Trainium are currently the only large-scale ASIC programs, 2027 is viewed as a key year for others to ramp, with a heavy focus on Meta’s MTIA and Microsoft’s Maia.

Other Technological Notes

> Intel EMIB: Intel’s EMIB-T process is seeing incremental demand, notably for the MediaTek TPUv9 Humufish. However, substrate capacity remains a limiting factor for this process. Intel’s EMIB process is positioned as a cheaper alternative, with costs estimated at approximately 50% of TSMC's CoWoS-L packaging technology. Current substrate-level yields for the EMIB process are around 60%, which is considered acceptable by the researchers for a process 1–1.5 years away from ramp. However, substrate capacity is viewed as a key limiting factor for capacity expansion because the processes for substrate build-up and embedding the silicon bridge steps currently have low yields.

$Intel(INTC.US) $Alphabet(GOOGL.US) $AMD(AMD.US) $NVIDIA(NVDA.US) $Taiwan Semiconductor(TSM.US)

Speedrun | Upcoming Events This Week - [July 20 - July 24, 2026]

Stay informed on events/news for the coming week.

Geopolitical & Market Outlook

> Iran Conflict: Tensions have escalated following an Iranian drone attack on a U.S. base in Jordan that resulted in the deaths of two U.S. service members. U.S. forces have responded with strikes on Iranian military coastal targets for eight consecutive nights.

> Energy Prices: The conflict has pushed crude oil prices above $80/barrel from a low of $68.55 on July 6th. This rise in energy costs poses a challenge to the Federal Reserve’s outlook and may impact future Consumer Price Index (CPI) reports.

> Momentum Unwind: High-beta momentum stocks have experienced a significant sell-off, with Goldman Sachs' High Beta Momentum basket dropping 32.8% in just three weeks since its June 22nd peak. This drawdown is compared to the market environment in late 2021, just prior to the 2022 bear market.

Earnings Calendar

This is a major week for earnings releases. Key companies to watch include:

> Google ($Alphabet(GOOGL.US)): Investors are focused on AI ROI, capital expenditure (CapEx) trends for 2026/2027, and memory cost pressures. There is concern that the market is not properly pricing in higher CapEx spending.

> Intel ($Intel(INTC.US)): As a major semiconductor company reporting this week, Intel will be watched for CPU demand trends related to agentic AI growth.

> Other Notable Releases: Tesla ($Tesla(TSLA.US)), Texas Instruments ($Texas Instruments(TXN.US)), GE Vernova ($GE Vernova(GEV.US)), Nokia ($Nokia Oyj(NOK.US)), STMicroelectronics ($STMicroelectronics NV(STM.US)), TE Connectivity ($TE Connectivity(TEL.US)), IBM ($IBM(IBM.US)), and ServiceNow ($ServiceNow(NOW.US)).

Sector Notes

> Semiconductors: The Philadelphia Semiconductor Index (SOX) is down 19% from its peak and is approaching oversold territory with an RSI of 40.62.

> Strategy: There is a suggestion to shift focus toward "quality names" for long-term survival, as the previous market trend of buying "anything" between April and June appears to have ended.

Check it out 👇

Morgan Stanley: Semiconductor Production Equipment

Market Dynamics by Application

> Segment Dominance: Logic/Foundry is the largest segment of the Wafer Fab Equipment (WFE) market. Within this segment, TSMC accounts for approximately 30–50% of the market.

> Industry Specialization: Among major Japanese equipment makers, companies are typically associated with specific application plays:

SCREEN: Primarily a Logic/Foundry play.

TEL (Tokyo Electron): Primarily a DRAM-related play.

KOKUSAI: Primarily a NAND-related play.

Front-End vs. Back-End

> Market Split: The semiconductor equipment market is split roughly 9:1 between front-end and back-end equipment.

> Trend Rebound: While the back-end equipment share trended downward for over 20 years as front-end tool value-add and unit prices rose, it has recently rebounded due to surging demand in the AI semiconductor market.

Competitive Landscape in Key Equipment Segments

> Lithography: The market is highly concentrated, with ASML holding a 95% share of the CY25 worldwide lithography equipment market.

> Dry Etching: The market for etchers is diverse. Lam Research leads with a 43% share, followed by Tokyo Electron (20%) and AMAT (19%).

In Conductor Etch, Lam Research is the dominant player with a 50% share.

In Dielectric Etch, Tokyo Electron holds the majority share at 55%.

Nvidia Compute Chip Cost Breakdown

> Gross Profit: The gross profit margin accounts for 75% of the total cost.

> Frontend Costs: The wafer cost represents 6% of the total.

> Backend Costs: These total 19% of the cost structure, broken down into:

HBM cost: 13%.

Test cost: 3%.

CoWoS cost: 3%

ASIC Cost Breakdown

> Gross Profit: The gross profit margin is significantly lower at 45% of the total cost.

> Frontend Costs: The wafer cost represents 13% of the total.

> Backend Costs: These total 42% of the cost structure, broken down into:

HBM cost: 24%.

Test cost: 7%.

CoWoS cost: 11%.

$NVIDIA(NVDA.US) $Alphabet(GOOGL.US) $Amazon(AMZN.US) $Applied Materials(AMAT.US) $Lam Research(LRCX.US)

Morgan Stanley: Memory

Agentic AI: Sizable Memory Demand

> Boost to DRAM Bit Demand: The implementation of Vera CPU is projected to increase total DRAM bit demand compared to 2025 levels. Specifically, a 2.5mn Vera CPU configuration is estimated to boost demand by 10%, while a 4mn configuration is estimated to boost it by 16%.

> Increased Memory Capacity: The transition from "GB NVL72" to "VR NVL72" shows a significant jump in LPDDR5X capacity requirements, rising from 17 TB to 54 TB.

DRAM Bit Shipment and ASP YoY Growth

> Decoupled Growth: The divergence between bit volume and Average Selling Price (ASP) shows that recent revenue gains are not driven by massive increases in raw shipment volume, but rather by surging prices for high-value products.

$Micron Tech(MU.US) $DRAM $EWY

Needham: WFE Spending

> Estimates Raised: Needham has increased its adjusted WFE spending estimates for the years 2026, 2027, and 2028;

2026: Adjusted WFE is now estimated at $145.3B (up from $130.1B).

2027: Adjusted WFE is now estimated at $201.0B (up from $149.6B).

2028: New CY28 WFE forecast introduced at $191.6B. Growth Drivers: The upgrades are primarily driven by accelerating DRAM and NAND spending, alongside faster-than-expected growth in leading-edge foundry/logic.

> CY28 Outlook: The forecast for 2028 reflects a "pause in growth" following two years of expansion, with memory spending—specifically DRAM—expected to moderate.

Key Segment Insights

> Foundry/Logic: Spending has strengthened, particularly at leading-edge nodes. For 2027, Needham expects leading-edge growth of approximately 30% year-over-year.

> DRAM: Described as "the true AI bottleneck," DRAM WFE for 2027 is now modeled at $84.1B, a 72% increase from the previous estimate of $49.0B.

> NAND: While pricing has been volatile, long-term bit growth driven by AI is expected to remain in the mid-20s to 30% range.

$KLA(KLAC.US) $Lam Research(LRCX.US) $Applied Materials(AMAT.US)

Mizuho Securities: Optics

Market Trends & Technologies

> Optical Circuit Switches (OCS): OCS is gaining traction among hyperscalers, with Google (GOOGL) leading adoption in its Jupiter Network and other hyperscalers like Amazon (AMZN) and Microsoft (MSFT) exploring its use. Lumentum (LITE) and Huber+Suhner (HUBN) are identified as key partners in this space.

> Co-Packaged Optics (CPO) vs. Near-Packaged Optics (NPO): While interest in CPO continues to grow (with potential deliveries in 2028/29E), industry focus is shifting toward NPO in the near-term because it is easier to deploy and requires less co-integration than CPO, despite being less power-efficient.

> Silicon Photonics (SiPho) & InP: The supply chain for SiPho remains constrained, with demand potentially outpacing foundry capacities at GFS and TSEM. A transition to 6-inch wafers is underway to help alleviate supply tightness by providing ~130% higher wafer area.

> Micro-LED (uLED) Potential: uLED/ALC is emerging as a potential disruptor for networking, offering 20-30m reach at approximately 1/5th the cost of optical pluggables, with no InP supply constraints. Credo (CRDO) is noted as a key player in this space, targeting deliveries starting in 2027-28E.

Company-Specific Updates (Lumentum & Credo)

Lumentum (LITE):

> Growth Drivers: Lumentum management noted that the "best is yet to come" as several major growth drivers—optical scale-up, optical scale-out, and optical circuit switches (OCS)—are just beginning to ramp up and are not yet fully reflected in their numbers.

> 1.6T Transition: The company is seeing a significant tailwind from the transition to 1.6T transceivers, led by NVIDIA and Google, with 200-gig EMLs providing roughly double the average selling price (ASP) of previous generations.

> Scale-Out Business: The partnership with NVIDIA for high-powered lasers in CPO switch platforms is a major focus, with expected incremental revenue of $50 million to $100 million in the fourth quarter of fiscal 2026 alone.

Credo Technology (CRDO):

> Market Outperformance: Credo has significantly outperformed larger rivals like NVIDIA and Broadcom in share price gains during 2026, largely due to its specialized role in high-speed, energy-efficient connectivity.

> Optical Portfolio: Following its acquisition of DustPhotonics, Credo has strengthened its silicon photonics capabilities. The company expects its optical connectivity business to generate over $600 million in revenue in fiscal 2027, supported by a 1.6T networking transition.

$Lumentum(LITE.US) $Credo Tech(CRDO.US) $Broadcom(AVGO.US) $NVIDIA(NVDA.US) $STMicroelectronics NV(STM.US) $Alphabet(GOOGL.US) $Meta Platforms(META.US) $Tower Semicon(TSEM.US) $Marvell Tech(MRVL.US) $Taiwan Semiconductor(TSM.US) $Microsoft(MSFT.US) $Amazon(AMZN.US)