Intel has entered high-volume manufacturing using ASML's High NA extreme ultraviolet (EUV) lithography technology for a subset of its Intel Core Ultra Series 3 "Panther Lake" processors, becoming the first company to ship high-volume logic products manufactured with the technology. ASML announced the milestone in an official press release on Wednesday, July 15, confirming that Intel Foundry is running the qualified High NA layers on its Intel 18A process node in Oregon.

According to ASML, Intel is using High NA EUV to pattern selected Intel 18A layers, with products already shipping to customers at yields matched to those achieved on ASML's existing NXE EUV platform. These layers are dual-qualified, meaning the same layer can be exposed on either an existing 0.33 NA NXE scanner or a 0.55 NA EXE scanner, with the resulting wafers being interchangeable.

High NA EUV has long been viewed as the successor to today's EUV lithography, promising to extend semiconductor scaling by enabling manufacturers to print smaller, denser circuit patterns that are becoming difficult to achieve with existing tools. Until now, the platform had been confined to R&D work. ASML’s announcement marks the first time High NA EUV has been used to produce and ship a high-volume commercial logic product.

Panther Lake, built on the Intel 18A manufacturing process, is spearheading this transition. Rather than replacing the company's entire lithography flow, Intel is applying High NA EUV to specific layers while the remainder of the chip continues to be manufactured using conventional lithography.

High NA EUV builds on the same 13.5-nanometer extreme ultraviolet light used by today's scanners but increases the optical system's numerical aperture (NA) — how much light a lens system can collect and focus onto a silicon wafer — from 0.33 to 0.55. The higher value resolves finer features in a single exposure, allowing chipmakers to print smaller patterns with greater precision and process control.

This increased resolution is expected to reduce reliance on complex multi-patterning techniques for some of the industry's most demanding layers, thereby simplifying manufacturing and improving feature fidelity. In the long term, these capabilities are expected to support higher transistor densities and improved performance in future processors, particularly as AI workloads continue driving demand for increasingly advanced semiconductor technologies.

"With increased resolution and better process control, the introduction of High NA EUV marks a substantial development in semiconductor lithography," said ASML President and CEO Christophe Fouquet. "We are proud to play a role in enabling the smaller, denser patterning that will accelerate advancements in AI and other emerging technologies."

Intel and ASML have been working towards this milestone for several years. In 2024, Intel completed installation of one of the industry's first commercial High NA EUV lithography systems, the TWINSCAN EXE:5000, at its Hillsboro, Oregon, research and development facility. The company later became the first to qualify ASML's second-generation TWINSCAN EXE:5200B, which increases wafer throughput and overlay accuracy while incorporating an improved EUV light source over its predecessor.

While the announcement represents High NA EUV's commercial debut, it does not mean Panther Lake is manufactured entirely using the new lithography platform. Instead, Intel has qualified High NA for selected layers, an approach that mirrors how new lithography generations are typically introduced into advanced semiconductor production before broader adoption across future nodes.

Intel Foundry Executive Vice President and General Manager Naga Chandrasekaran said that qualifying the High NA process option on selected Intel 18A product layers enables the company's existing tool fleet to deliver higher manufacturing output while providing flexibility for future process technologies.

Panther Lake itself is not a future product. Intel launched Core Ultra Series 3 at CES on January 5, 2026, opened preorders the following day, and put systems on shelves globally from January 27. The Core Ultra X9 378H followed in April alongside the value-tier Core Series 3, code-named Wildcat Lake, and the handheld-focused Arc G3 parts arrived on May 28.

The announcement’s statement that the product is shipping to customers refers to wafer flow from the fab into the supply chain, rather than to a product launch. ASML says the two companies will continue working on High NA readiness, with the flexibility to incorporate the technology into future nodes based on customer needs — most immediately, Intel 14A, which Intel has designed to use High NA on a set of its tightest-pitch layers.

Google plans to use Intel's EMIB-T packaging for its next-generation TPU codenamed Humufish, according to SemiAnalysis. TSMC's portfolio of chip-on-wafer-on-substrate (CoWoS) technologies has become the de facto standard advanced packaging option for nearly all AI and HPC processors made in the industry. Competing offerings are usually considered as secondary solutions if CoWoS is in tight supply, but things are beginning to change.

Google is a long-standing CoWoS customer for TPUs, starting from the Third-Generation TPU, all the way to Google's latest Eighth-Generation TPUs. Assuming that SemiAnalysis's report about Google's decision to move to EMIB-T with its Ninth-Generation TPUs is accurate, it's a big decision for Google, as switching from one advanced packaging technology to another is a complicated endeavor, which involves plenty of changes and unknowns. Understanding Google's reasons for the switch could shed some light on the prospects of Intel's and TSMC's advanced packaging technologies, which will be used by leading chip designers and hyperscalers in the coming years.

Advanced packaging technologies at glance

For years, Google used TSMC's CoWoS-S, and later, CoWoS-L packaging. Initially, the company used CoWoS-S packaging, which relies on a silicon interposer up to 3.3X the reticle size, but with its 7th- and 8th-Generation TPUs, the company moved to CoWoS-L. CoWoS-L relies on a redistribution layer (RDL) interposer with embedded local silicon interconnect (LSI) bridges that enable high-performance die-to-die links, which can scale packages to 5.5X the reticle size today. TSMC promises to improve CoWoS-L's capabilities to scale over 14X the reticle size by the end of the decade.

Unlike CoWoS, Intel's embedded multi-die interconnect bridge (EMIB) technology does not use any interposers. The technology instead relies on tiny embedded silicon bridges within the substrate to enable high-density die-to-die interconnections, whereas everything else is routed through an inexpensive organic substrate.

EMIB-T adds through-silicon vias (TSVs) to the bridge, which enables power to flow vertically instead of going through the organic substrate. In addition, Intel's EMIB-T also integrates sophisticated metal-insulator-metal (MIM) capacitors and a dedicated ground plane into the bridge to improve power integrity. The latter is a particularly important feature of complex next-generation AI accelerators, which demand more, cleaner power, and for which power delivery is becoming as challenging as signal routing.

The main selling point of EMIB (and EMIB-T) is that it is not constrained by interposer reticle limits as it places small silicon bridges only where high-density die-to-die links are needed. Strictly speaking, CoWoS-L is not either, as it uses LSIs locally as well. The difference is that those bridges are embedded into a package-wide RDL interposer that connects everything and enables dense interconnections across the package.

Since both CoWoS-L and EMIB-T are designed to address the same applications and have many similarities in the way they do this, the choice between them is likely driven by a combination of factors rather than one single advantage or disadvantage. On the technology side of matters, these factors include interconnect performance and density, power delivery, scaling beyond very large package sizes, and mechanical rigidity. On the business side of things, costs, capacity availability, and supply chain diversification are also a significant factor.

Crucial differences

SemiAnalysis claims that the main advantage of EMIB/EMIB-T over CoWoS is the lack of reticle limit, but this argument does not fully hold against CoWoS-L, as it was invented specifically to escape the reticle limitation by replacing the monolithic silicon interposer with localized LSI bridges.

When it comes to dense, package-wide routing, CoWoS-L's RDL interposer is fundamentally superior to an ordinary organic substrate offered by EMIB-T. Organic substrate wiring has coarser line/space dimensions and larger vias, so it cannot provide the same routing density as CoWoS-L's fine-pitch RDL. Where an EMIB bridge connects adjacent dies, Intel can achieve very high interconnect density. But anything that needs to travel beyond those bridges must use the package substrate or cross a topology involving additional bridges.

By contrast, CoWoS-L gives the designer two levels of connectivity: LSIs provide extremely dense local die-to-die connections, while the global RDL interposer provides relatively dense and flexible routing across the entire package. This means the RDL can carry longer, lower-density connections without consuming valuable LSI resources, while still offering much finer routing than the underlying package substrate.

One scenario for Google's choice is that it potentially wanted better power delivery than what CoWoS-L could offer. EMIB-T integrates TSVs for vertical power delivery, sophisticated MIM capacitors for local decoupling, and a dedicated ground plane into its silicon bridges. The combination of these features substantially reduces power-delivery impedance and improves transient response and power integrity, which gives EMIB-T a major advantage over conventional EMIB for power-hungry AI accelerators. However, we have no idea how EMIB-T stacks up against CoWoS-L in the case of Google’s Humufish.

Of course, the larger the RDL interposer becomes, the greater its parasitics can become, potentially limiting scaling unless TSMC finds ways to mitigate them. However, EMIB does not eliminate long-distance wiring: If two distant dies must communicate, those signals still have to travel somewhere, and routing them through an organic substrate is not inherently electrically superior to routing them through a purpose-built RDL interposer. Therefore, it is difficult to claim that Google chose EMIB-T over CoWoS-L, simply because EMIB-T offers superior package-wide electrical characteristics.

After Nvidia suffered yield loss with its Blackwell data center GPUs due to an alleged mismatch in the coefficient of thermal expansion (CTE) among the GPU chiplets, LSI bridges, RDL interposer, and motherboard substrate, which led to warping and system failure, it is reasonable to question the mechanical rigidity of CoWoS-L packages. Nvidia has found a solution for its dual compute chiplet Blackwell packages, and so have other developers of AI accelerators. However, as package dimensions increase, they may behave differently, therefore causing yield losses.

By contrast, EMIB/EMIB-T eliminates the large RDL interposer and embeds small silicon bridges in the organic substrate, so most of the package consists of the substrate itself. This does not make EMIB/EMIB-T packages immune to mechanical failures, as large packages can warp and bend, causing various problems. However, as such packages lack the very source of global thermomechanical stress, they can potentially be more robust mechanically. However, EMIB-T can potentially complicate things because TSVs, additional metal structures, MIM capacitors, and their ground plane make the bridge more complex. Thus, Intel must manage both global package warpage and local stresses around each embedded bridge to ensure the mechanical rigidity of these packages.

Ironically, while CoWoS-L can offer denser package-wide routing, which is better for ultra-large processors, EMIB-T may potentially provide better mechanical rigidity required for such devices. Nonetheless, EMIB-T and its organic substrate do not eliminate package bending or cracking risks entirely.

Economics

If Google's Humufish TPU really moves to EMIB-T, the decision could well be both technical and strategic. Google has the engineering resources to opt for an all-new packaging technology in an effort to lower costs and eliminate dependence on TSMC's constrained CoWoS capacity. Nvidia tends to procure advanced packaging allocations years in advance, so it is possible that Google could simply not get enough CoWoS-L wafers for its 9th-generation TPU.

As a bonus, Google can also build relationships with Intel Foundry without using the company's fabrication technologies. In fact, keeping in mind that Intel and Google already have a strategic agreement covering Intel Xeon CPUs, it wouldn't be too surprising to learn that the cloud giant is courting Intel Foundry as well.

Both Intel's EMIB-T and TSMC's CoWoS-L have their own technological and economic advantages and disadvantages. Perhaps the biggest advantage of CoWoS-L is its predictability, as the company has experience with that tech. However, if Google has decided to drop that predictability in favor of an all-new packaging method, it may well have a combination of technological and strategic reasons to do so.

Micron committed up to $3 billion to the U.S. semiconductor supply chain last week. Of that, $500 million goes to GlobalWafers as strategic financing — subject to definitive agreements and closing conditions — for its 300mm raw silicon wafer plant in Sherman, Texas, and the two companies will sign a 10-year agreement for access to that plant's output. Ben Tessone, Micron's senior vice president and chief procurement officer, tied the move to securing "critical input materials." In a second announcement from Boise the same day, Micron raised its planned US spending to more than $250 billion through 2035, up from $200 billion, and poured the first load of concrete at its Clay, New York megafab a quarter ahead of schedule.

Running until 2035, the $250 billion spending target is attached to a goal of making 40% of Micron's DRAM in the U.S. by the mid-2030s. Only a relatively paltry $500 million of that $250 billion has been earmarked for buying wafer supply from GlobalFoundries, the only U.S. supplier that’s capable of producing 300mm wafers.

The 300mm wafer market

Roughly 85% of global 300mm wafer capacity sits with five suppliers, according to market research firm Mordor Intelligence: Shin-Etsu and SUMCO of Japan, Taiwan's GlobalWafers, Germany's Siltronic, and South Korea's SK Siltron. The two Japanese firms hold more than half between them.

GlobalWafers America opened the Sherman plant in May last year on an initial $3.5 billion investment. It’s the first fully integrated 300mm raw wafer facility built in the U.S. in more than two decades, and the company says it’s the only CHIPS-participating supplier capable of producing advanced 300mm wafers domestically. The site holds a CHIPS Act award of up to $406 million, finalized in December 2024 and shared with a silicon-on-insulator plant in St. Peters, Missouri. Commerce Department figures from 2022 put full-build capacity at around 1.2 million wafers per month across a six-phase campus, with one phase currently running.

Meanwhile, SUMCO is ending 200mm production at its Miyazaki site and has slowed new 300mm expansion. The leading-edge capacity Shin-Etsu and SUMCO added in 2025 was sized to match contracted demand rather than to build ahead of the market. Wafer suppliers have run this way for a decade, protecting margins instead of chasing volume, and with suppliers holding back, the capital for new capacity increasingly comes from their customers.

GlobalWafers chairperson and CEO Doris Hsu set out her terms for that at the Sherman opening, announcing an additional $4 billion for the site and telling Reuters that further phases depended on the first two turning a profit, on customers signing long-term contracts, and on reasonable pricing, prepayments, and government support. Micron's $500 million in financing and a decade-long supply commitment cover most of that list, and Hsu has since called the Micron agreement the largest long-term deal in her company's history and said a second Sherman phase is now necessary.

Micron is locking in its own customers on the same basis, having signed a strategic customer agreement with General Motors on July 1 and another with Ford on July 6, two of 16 such agreements the company cited on its fiscal Q3 2026 earnings call. Each ties future memory output to a named buyer.

We’ve seen the industry do this before. During the memory boom of 2017-2018, chipmakers signed prepaid, take-or-pay wafer agreements to guarantee supply, but those prepayments became balance-sheet liabilities when DRAM pricing fell through 2019. SK Group chairman Chey Tae-won told an audience at Nvidia's GTC conference that the current wafer shortage could last through 2030 with a deficit above 20%, which is the argument for signing now. Conversely, the 2019 write-downs are the argument against.

HBM packaging

High-bandwidth memory is of course the component that’s currently carrying the steepest premiums in the AI market, and a fabbed wafer isn’t yet HBM. The die has to be stacked and packaged using advanced 2.5D methods with through-silicon vias, the capacity for which is located almost entirely in Asia. Micron's committed HBM packaging anchor is a roughly $7 billion facility in Singapore, with operations starting in 2026. Per a June 2025 SEC filing, the company lists U.S. HBM packaging as an intention, but no committed site or date has yet been announced.

As for U.S. packaging capacity that is scheduled, it’s all clustered in or around 2028. SK hynix is building the first U.S. 2.5D advanced packaging plant in West Lafayette, Indiana, a roughly $3.87 billion project with mass production set for the second half of 2028. Amkor, meanwhile, has expanded its Peoria, Arizona campus to $7 billion, with production slated for early 2028. TSMC's Arizona fabs run leading-edge logic but don’t yet offer high-volume 2.5D packaging on U.S. soil — this is reportedly planned for 2029. While it’s true that a wafer fabbed in New York and packaged in Singapore counts toward domestic DRAM, it doesn’t make the finished HBM stack domestic.

Output timelines vs. 2035

Micron's Manassas, Virginia fab began producing 1-alpha DRAM in May, and it’s the only U.S.-made memory in volume, representing roughly 2% of the world’s supply. The first new Idaho fab should reach wafer output in mid-2027, and the second in late 2028, while the Clay, New York campus isn’t expected to produce until around 2030. The $250 billion capex figure runs five years past that, while conventional DRAM contract prices continue to rise at record amounts — more than 90% quarter over quarter in early 2026, according to TrendForce — and manufacturers increase prices. Apple raised MacBook, iPad, and Vision Pro prices last month, citing memory costs, and none of the announced U.S. capacity will do anything to alleviate such shortages.

Samsung and SK hynix committed a combined $880 billion under a South Korean government-coordinated chip and AI program announced last month, spread over roughly a decade. That spending is domestic to Korea and separate from Samsung's $37 billion Texas footprint. But set next to Micron's $250 billion, we’re seeing a pattern of more companies announcing more capex than construction projects can physically absorb.

HBM consumes roughly three times the wafer area per bit of standard DDR5, so shifting production to HBM removes more commodity memory from the market. DRAM already takes around a fifth of global 300mm capacity, and memory is the largest single application for 300mm silicon. Micron's Sumit Sadana told CNBC in January the company could meet “at most” two-thirds of some customers' medium-term demand.

Intel has unveiled Starfire, a space-grade system-on-chip designed for the U.S. government that pairs eight CPU cores and a three-tile NPU built on its Intel 18A node with an Intel 3 graphics tile, all in one Foveros package. Intel published the Starfire sell sheet, listing two versions that draw 10 W and 35 W and reach up to 45 and 75 TOPS, respectively, rated to run between -55 and 125 Celsius.

Both SKUs share the same layout of four Intel 18A P-cores, four low-power efficiency cores, a three-tile NPU also on 18A, and a four-core Xe GPU with 64 execution units built on Intel 3. The Low Power part runs its P-cores at 1.0 GHz, efficiency cores at 850 MHz, and the GPU between 800 MHz and 1.0 GHz. The Performance part clocks the P-cores to 3.1 GHz, efficiency cores to 2.1 GHz, and the GPU to 2.0 GHz. Both carry 12 PCIe Gen4 lanes, support LPDDR5 or DDR5, and are rated for a 10-plus year lifetime.

Intel builds the CPU and NPU on 18A and the GPU on the older Intel 3, the same node division it used for Clearwater Forest, the 288-core Xeon that stacks 18A compute tiles on Intel 3 base tiles. Smaller transistors hold less charge per stored bit, which makes leading-edge silicon more prone to radiation-induced bit flips, so committing 18A to orbit leans on RibbonFET and design-level hardening rather than a mature, inherently more tolerant node.

The market Starfire is targeting has run on BAE Systems' RAD750 for two decades. That radiation-hardened PowerPC part clocks 110 to 200 MHz, carries 10.4 million transistors, and is built on 150nm or 250nm lithography, per public specifications, and it flies on the Mars rovers, Kepler, and Fermi, among more than 150 spacecraft. BAE's multi-core RAD5545 and the Microchip-built processor NASA is developing to reach 100 times the throughput of current spaceflight chips are the more recent step up. Starfire's up to 75 TOPS and dedicated NPU put it in a different bracket, built for on-orbit AI inference rather than telemetry and control.

Intel lists the radiation data, covering total ionizing dose, single-event latch-up, and single-event effects, as characterization in process, so the part isn't radiation-qualified yet, and it notes the specs are subject to change. Intel Government Technologies is handling Starfire, with samples in Q3 2026 and a pitch of market-competitive pricing and domestic manufacturing. Intel Foundry is the only U.S.-based maker of leading-edge logic, holds Trusted Foundry status, and has tied its 18A and packaging roadmap to Pentagon programs including RAMP-C and SHIP, though 18A yields aren't expected to reach industry-standard levels until 2027.

Apple's planned M7 Ultra chip is being designed to support up to 1.5 TB of unified memory and to push AI performance toward the class of Nvidia's Blackwell accelerators, according to a new Bloomberg report published by Mark Gurman. But whether the lofty top memory config can ship at all will depend on the state of the memory market, and the part isn't expected until 2028. The same report says Apple has compressed its Mac silicon timeline, taping out the M7 roughly six months after the M6.

We've already heard that Apple plans to release a base M6 chip this fall for entry-level Macs, then skip the Pro, Max, and Ultra versions of that generation and move straight to the M7 line. However, Gurman now reckons that we'll see a base M7 in the first half of 2027, M7 Pro and M7 Max at the end of 2027, and the M7 Ultra in 2028. Apple reportedly began taping out the M7 about six months after it started the same process for the M6, which is what has enabled the company to pull the schedule forward.

The 1.5 TB target for the M7 Ultra is roughly twice the capacity Apple has planned for the M5 Ultra, per Gurman, who tied the configuration directly to memory availability. Apple already pulled the 128GB Mac Studio this year over supply constraints as DRAM prices climbed, and a 1.5 TB part would call for far more of the same scarce, high-cost memory.

Apple's current M3 Ultra already reaches 819 GB/s of memory bandwidth by fusing two Max dies, and it's the Ultra tier, not the base chips, that carries the heaviest local-AI workloads. Gurman describes the M7 Ultra as a large step up in AI performance rather than stated parity with Nvidia's data-center silicon. "I'm told the processor dramatically upgrades AI performance, bringing it closer to the class of dedicated AI accelerators such as Nvidia Corp.'s Blackwell," Gurman wrote in his report.

Apple is also preparing an AI server built on the M5 Ultra under the code name J246 for deployment soon, with a second server chip based on the M7 Ultra planned for 2029, according to the report. The 2028 generation, which includes an M8 chip code-named Soko and a high-end Mac part called Cardinal, moves to a 1.4nm process. That aligns with TSMC's A14 node, which the foundry has scheduled for mass production in the second half of 2028.

None of the dates or specifications have been confirmed by Apple.

SK hynix has completed the largest-ever foreign company IPO in U.S. history, raising $26.5 billion in its Nasdaq debut today, July 10. The South Korean memory giant sold 177.9 million American depositary receipts (ADRs) — a U.S.-listed stand-in for a foreign share — at $149 apiece, each representing a tenth of a Seoul-listed share. The offering was more than seven times oversubscribed and drew demand from more than 500 investment firms, according to Financial Times. Temporary Nasdaq trading is underway under the ticker SKHYV before regular-way trading begins as SKHY on Monday, July 13.

The offering was led by Bank of America, Citigroup, Goldman Sachs, and JPMorgan, with nine additional firms rounding out a 13-bank syndicate. Anchor demand came from heavyweight institutions including Baillie Gifford, Coatue Management, and Situational Awareness Partners, which together signaled interest in as much as $7 billion of stock, according to people familiar with the matter cited by Financial Times.

SK hynix is the world's leading maker of high-bandwidth memory (HBM), the vertically stacked DRAM that has become critical infrastructure for AI accelerators. The company has said it will steer the proceeds toward boosting its AI-memory manufacturing capacity. Confirmed build-outs include the first-phase fab at the massive Yongin semiconductor cluster, a new P&T7 advanced-packaging line in Cheongju, and EUV lithography equipment slated for delivery by the end of next year. Separately, SK hynix is constructing its first U.S. production site, a $4 billion advanced-packaging plant in West Lafayette, Indiana, targeted for completion around 2028. The facility is eligible for up to $458 million in CHIPS Act grants and up to $570 million in federal loans.

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SK hynix is seeing sensational growth thanks to the ongoing AI boom. The company is reportedly on track to post over 200 trillion won ($133 billion) in operating profit this year, a record-breaking figure that would see SK hynix employees earn around $400,000 each in bonuses. The company’s Seoul-listed stock is up roughly 220% year-to-date and has climbed more than sixfold over the past year.

In late June, SK hynix briefly surpassed Samsung as South Korea's most valuable company, closing at around 2,080 trillion won (about $1.35 trillion), a meteoric rise for a company that almost declared bankruptcy in 2001 and, more recently, recorded an annual operating loss of 7.73 trillion won in 2023. That rise doesn't seem like it will be slowing down any time soon. SK hynix has said its entire 2026 output of HBM, DRAM, and NAND is already sold out, with the crunch expected to extend into 2027.

Japanese chipmaker Rapidus will try to lure customers away from TSMC not only by offering a different kind of service, but also by offering its manufacturing services at lower prices, chief executive Atsuyoshi Koike announced this week. The company's plan to rival TSMC in terms of pricing appears on the surface as a risky move, as the company moves to develop leading-edge process technologies.

At present, Rapidus is looking at charging ¥3 million – ¥3.5 million ($18,550 - $21,635) per wafer processed using its 2nm-class fabrication process, which is significantly below TSMC's rumored quote of around $30,000 per N2 wafer, and is comparable to what Samsung is rumored to offer with its SF2 manufacturing technology, set at $20,000 per-wafer. Actual prices will depend on exchange rates, though Rapidus' general idea of offering significantly lower quotes than TSMC is immediately apparent.

Rapidus plans to start high-volume manufacturing (HVM) using its 2nm-class fabrication technology by the second half of 2027. The ramp of a new fab will take some time, so expect meaningful volumes from Rapidus to only be produced in 2028, when TSMC's N2 will no longer be its leading-edge node.

By the time Rapidus starts HVM at its IIM-1 in 2027, TSMC will have ramped production of chips using its performance-enhanced N2P manufacturing node, and the company will also absorb all the yield learning with gate-all-around the company will have with its N2 present at five fab modules. Furthermore, by the time Rapidus reaches meaningful volumes at IIM-1 in 2028, TSMC will have ramped up production using its advanced A16 fabrication process with Super Power Rail backside power delivery as well as a 3^rd-generation 2nm-class node named N2X.

In addition to the vast 2nm-capable capacity and process maturity that should be kept in mind when comparing Rapidus with TSMC, there is another factor to consider. One of TSMC's major advantages over its rivals is its Open Innovation Platform (OIP) ecosystem, which includes comprehensive electronic design automation tools, silicon-proven IPs, even for the latest nodes, a host of contract chip designers, and advanced packaging services not only from TSMC but also from its partners. For now, neither Rapidus nor Intel and Samsung Foundry can offer anything close to TSMC's OIP.

Given the advantages that TSMC will likely have over competitors with its 2nm-class fabrication technologies in 2028, lower pricing may be among the few ways to compete against the world's largest foundry. Rapidus' strategy of offering lower quotes while operating a single fab does not seem like the best way of earning money, but perhaps a certain way to lose it.

However, Rapidus may have another ace up its sleeve with single wafer processing across all process steps. The approach will greatly speed up the production cycle, which will be its indisputable advantage over other chipmakers, albeit at the cost of tool usage efficiency. Will lower quotes and shorter production cycles be enough for Rapidus to win customers from TSMC? Only time will tell.

Rapidus is reportedly negotiating with more than 60 potential customers, mainly overseas companies, which demonstrates the company's ambitions to become a viable rival to the global leader TSMC as well as contract chipmakers Intel Foundry and Samsung Foundry.

Researchers in Korea and Japan have presented two separate memory-integration proposals that aim to increase HBM (High-Bandwidth Memory) capacity and bandwidth without trapping more heat inside ever-taller DRAM (Dynamic Random Access Memory) stacks, one of the most pressing challenges facing future AI accelerators. Presented at the 2026 IEEE/JSAP Symposium on VLSI Technology and Circuits held in June, the two approaches — V-Die from a Korean research collaboration and MOSAIC from a University of Tokyo-led group — both explore the same broad idea of standing DRAM memory dies on their edges instead of stacking the memory dies only upward like conventional HBM.

The Korean proposal, called Vertical-Die (V-Die), was presented by researchers at the Ulsan National Institute of Science and Technology (UNIST). The design rotates custom DRAM dies upright, drops through-silicon vias to free die area for more memory cells, gives each die its own bottom-edge I/O, and runs liquid-cooling channels between adjacent dies. In simulations against an HBM4 system at equal capacity, the V-Die system reportedly achieved 540 tokens per second on a GPT-3-sized workload, compared to 296 tokens per second for HBM4.

The Japanese project, MOSAIC, takes a similar “sideways stack” idea but focuses on the practical difficulty of connecting so many vertical dies to a GPU or package substrate. Presented by University of Tokyo researchers, the MOSAIC work uses orthogonal die stacking and a contactless die-to-die interface, in which data is transferred through tiny inductive coils rather than requiring every signal pad to land perfectly on a physical contact. The researchers say the prototype interface achieved up to 4 Gbps per channel, while the memory structure could double HBM4-class capacity in a DRAM-on-GPU configuration.

Both projects aim to solve the growing problem of AI chips being held back by memory. Modern accelerators can perform enormous amounts of computation, but large, powerful models depend on moving huge amounts of data between memory and compute. This is why HBM has become one of the defining technologies of modern AI hardware.

The technology addresses the memory wall by stacking multiple DRAM dies vertically on a base die and placing that stack very close to the processor. Nvidia's Blackwell Ultra B300, for instance, carries up to 288GB of HBM3E memory, without which much of the silicon would sit idle waiting for data. The dies are connected via through-silicon vias (TSVs) — tiny vertical channels etched through the silicon and filled with metal.

The stack then communicates with the GPU over an extremely wide interface, often routed through a silicon interposer or an advanced package. This is the core reason HBM can deliver terabytes per second of bandwidth: it uses a very wide, very short data path instead of sending memory traffic across a motherboard, as with conventional DIMMs (Dual In-line Memory Modules), physical sticks of RAM used in computers.

However, that same structure creates several problems. While taller stacks add more capacity, they also make it harder to remove heat. Heat generated in the lower dies and at the high-speed interface must pass through layers of silicon, bonding materials, underfill, and package structures before it reaches a heat spreader. Furthermore, TSVs consume die area that could otherwise be used for memory cells, and as bandwidth rises, more routing and I/O place additional pressure on both signal integrity and packaging costs.

HBM4, the latest generation of HBM, addresses a number of these challenges. Meanwhile, companies such as SK hynix, Samsung, and Micron are racing to improve speed, capacity, base-die performance, and thermal management. SK hynix has already shown iHBM, which embeds cooling elements into the HBM interface area, and Samsung has shown an HBM5 mockup with Heat Path Block cooling to more directly extract heat from the stack. However, they all retain the same upward stacking structure.

This convention is what V-Die and MOSAIC are challenging. By standing DRAM dies upright, the researchers expose far more silicon surface area to the cooling path. In theory, this turns the memory stack into something closer to a heat-sink fin array, where heat can move laterally and escape more directly instead of being trapped in the middle of a thick vertical pile. It also opens the door to new connection schemes along the bottom or side of each die, rather than forcing every die to communicate through TSVs running vertically through the stack.

For V-Die, the key shift is removing TSVs from the memory dies and replacing them with bottom-edge connections. Each DRAM die gets its own I/O along the bottom edge and connects directly to the substrate, with links reportedly spaced every 20 microns. The team says this layout gives four times as many connections as HBM4 and cuts memory read time by 37%, although some signals must travel farther across the package to reach the processor.

Cooling is the other half of the V-Die argument. The proposal places microfluidic cooling channels between adjacent upright DRAM dies, allowing coolant to dissipate heat closer to its source. According to the researchers, this could keep the stack around 45°C, far below the 80°C-plus range associated with dense HBM systems. In a simulated 16-die stack matched to H100-class hardware on a GPT-3-scale model, V-Die hit 540 tokens per second, compared to HBM4's 296, and cut first-token latency by 32%, or about 24 milliseconds.

MOSAIC, meanwhile, is focused on making the sideways stack manufacturable. Because the dies are assembled flat and then turned on edge, even a few microns of die-thickness variation across dozens of dies can add up to an alignment miss where the signal pads no longer land. The Japanese team’s answer is a contactless interface based on inductive coupling. One side of the memory die carries oblong coils, while a corresponding set of coils sits on the substrate or mating chip. Current in one coil induces a signal in the other, allowing data to cross the small gap without a direct metal-to-metal signal contact. This eliminates the need for precise overlapping, giving the package greater tolerance for assembly variation. Power, which requires fewer, larger connections than data, can still be supplied via physical contacts on the sides of the memory cube.

The VLSI MOSAIC prototype achieved up to 4 Gbps per channel and demonstrated TSV-free 3D integration for a memory-on-GPU layout. The team says the approach can enable twice the memory capacity of HBM4 without significantly increasing peak temperature. A related bump-MOSAIC hardware demonstration at ECTC used 100-micron-pitch microbumps, achieved stacking alignment within 6 microns as verified by X-ray CT, and showed a configuration with three times the thermal conductivity of conventional stacking while adding up to 30% more memory capacity.

While the results look promising, neither V-Die nor MOSAIC is close to replacing commercial HBM. Neither is close to shipping. V-Die is still a proposed architecture, with a prototype in the works to validate its thermal and electrical behavior; MOSAIC has proof-of-principle hardware, but the researchers have yet to show it scales to commercial DRAM capacity, yield, cost, and reliability.

Still, any viable solution to the multifaceted AI memory problem is a welcome development. SoftBank and Intel’s Z-Angle Memory (ZAM) and NEO Semiconductor’s 3D X-DRAM — both still in development — aim to solve the constraints of conventional memory. Meanwhile, the overall market is already feeling the squeeze on price and availability, even as memory makers divert capacity toward the more lucrative AI HBM and server products, driving consumer RAM prices even higher.

Micron has said it will invest up to $3 billion in the U.S. semiconductor supply chain, with $500 million of that going to GlobalWafers as strategic financing for its 300 mm raw silicon wafer plant in Sherman, Texas, alongside a 10-year agreement giving Micron access to that plant's wafer output. In a separate announcement, the memory maker raised its planned U.S. spending to more than $250 billion through 2035, up from $200 billion, and confirmed the first concrete pour at its Clay, New York campus more than a quarter ahead of schedule.

Sherman is the sole operating facility in the U.S. capable of producing advanced 300 mm raw silicon wafers, the substrate on which every leading-edge DRAM, NAND, and logic die is built. GlobalWafers opened the plant in May last year and holds a $406 million CHIPS Act award covering the site and a silicon-on-insulator facility in St. Peters, Missouri. The 142-acre campus is designed for up to six phases, one of which is running. Micron's other American sites draw their wafers from Japan, Taiwan, Germany, and South Korea; Shin-Etsu, SUMCO, GlobalWafers, Siltronic, and SK Siltron together control the overwhelming majority of global 300 mm supply, making raw silicon the most concentrated layer in the chip space.

Doris Hsu, chairperson and CEO of GlobalWafers, set out her terms for building phase two at Sherman during the plant's opening last year, telling Reuters the company needed profitability at the first two phases, customers willing to sign long-term contracts, reasonable pricing, prepayments, and government support. Thursday's announcement supplies most of that list in a single transaction.

Wafer suppliers spent the 2023-2024 downcycle protecting margins rather than adding capacity, and SUMCO is winding down 200mm production at Miyazaki this year while holding the line on new 300mm expansion. Customers, not suppliers, are therefore now underwriting the capacity. The last time the industry did this, during the 2017-2018 megacycle, chipmakers signed prepaid long-term agreements that turned into liabilities when pricing rolled over.

Silicon wafer shipments reached 3,275 million square inches in Q1 2026, up 13.1% year over year, with SEMI.org attributing the growth to AI data center demand across advanced logic, memory, and power devices. Micron's first new Idaho fab, ID1, is expected to begin wafer output in mid-2027, and production at Clay isn't expected until around 2030. The company began making 1-alpha DRAM at its Manassas, Virginia fab in May.

Micron told investors last December that it can serve only half to two-thirds of customer demand, and nothing announced Thursday changes the supply position of DRAM this year or next.