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SK hynix forecasts memory demand will exceed supply through 2030

SK hynix said in its 28 October third-quarter earnings report that memory demand will exceed supply through 2030, citing slow fab construction and harder manufacturing, an outlook that keeps AI memory buyers facing tight supply.

TechnologyAnalysisRachel NwosuPublished: 5 November 20265 min readSources 30
SK hynix forecasts memory demand will exceed supply through 2030

In its third-quarter earnings report on 28 October, SK hynix said memory demand will exceed supply through 2030. The company cited two constraints: advanced semiconductor manufacturing is getting technically harder, and building a new fab takes a long time. The forecast covers the period through 2030; it does not mean the shortage ends in 2031.

The 28 October report was the third-quarter update. In the second quarter, revenue was 79.3 trillion won and operating profit was 60.5 trillion won, a 76% operating margin. HBM stacks take up so much DRAM that the buildout is depleting supply for consumer electronics, CNBC reported.

Why supply cannot catch up quickly

On demand, SK hynix expects AI spending to widen from large companies to more businesses and national governments. Over the medium to long term, it points to autonomous driving and robotics.

The capacity is committed, but it arrives in stages

On 7 August SK hynix said it would spend 54 trillion won ($38.1 billion) on two plants: 35.2 trillion won for the Y2 fab at Yongin and 19.1 trillion won for the M17 fab at Cheongju. Y2 breaks ground in July 2027, with its first cleanroom opening in June 2029 to make HBM and other next-generation DRAM. M17 breaks ground in February 2027 and opens its first cleanroom in December 2028, producing NAND.

A cleanroom is the controlled space where equipment is installed and processes are run. Finishing one is not the same as shipping product. Equipment installation and process ramp come after that. SK hynix has not said when Y2 or M17 will reach full capacity or how much shipments will grow. Investment periods run through October 2031 for Y2 and April 2031 for M17, but those are not mass production start dates. The Y2 figure includes office buildings, an integrated R&D building and related infrastructure, so the full amount does not go to manufacturing equipment.

The two fabs are the next tranche of a master plan that commits 600 trillion won to the Yongin Semiconductor Cluster and 100 trillion won to expand the Cheongju base. SK hynix plans capital expenditure in the high 40 trillion won range this year, more than $32 billion.

Indiana adds packaging, not wafer capacity

SK hynix broke ground on its Indiana advanced packaging and testing facility on 27 August. The site handles back-end stacking and testing of wafers made in Korea, so its capacity cannot simply be added to front-end wafer capacity in Korea. The cleanroom is targeted to open by October 2028, with volume production of HBM4E scheduled for the third quarter of 2029.

CEO Kwak Noh-Jung said at the ceremony that the memory shortage will not relent until at least the end of 2030. He said he had seen no meaningful indicators of a coming memory-cycle decline.

Contracts and the HBM4 wobble

Some of the demand is contracted. SK hynix said it has finalized long-term agreements with about 10 customers. It began mass shipments of HBM4 in the second quarter, with production ramping in the second half, and sent samples of HBM4E in the first half of 2026.

The HBM market is concentrated. SK hynix held 58% of it in the first quarter of 2026, with Samsung and Micron at 21% each, according to Counterpoint Research. A Chosun report on 21 October said HBM4 shipments had fallen short of expectations and that SK hynix's HBM revenue share fell to 50.00% in the second quarter from 58.00% in the first.

Analysts are split on the HBM4 transition. DS Investment & Securities cut its SK hynix target from KRW 3.10 million to KRW 2.64 million in September 2026, citing weaker shipment expectations during the HBM4 transition, as reported by Chosun. Meritz Securities raised its target to KRW 3.20 million from KRW 3.10 million on 12 October, Financial News reported. Before the results, Chosun reported a third-quarter operating profit forecast of KRW 76.964 trillion, 5.60% below the KRW 81.5122 trillion estimate made three months earlier.

What happens next

The HBM4 ramp remains the open question. Shipments came in below expectations once already. The 28 October report was due to clarify whether delayed HBM4 shipments move into the fourth quarter. The demand forecast does not settle the timing of that ramp.

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Sources

30
  1. 01SK hynix Expects Memory Demand to Outpace Supply Through 2030, Even With Major Fab InvestmentEN
  2. 02SK Hynix says memory shortages to persist until 2030EN
  3. 03SK hynix Rejects Memory Peak Talk, Says HBM Sold Out Through 2029EN
  4. 04SK hynix CEO says DRAM, HBM sold out through 2029, vows shareholder returnsEN
  5. 05SK Hynix to invest $38 billion building new memory chip plants as demand soarsEN
  6. 06An inside look at SK Hynix $720 billion AI-fueled buildout that's taking over South KoreaEN
  7. 07SK Hynix Supplies More Than Half the World's HBM Memory. Its Stock Costs Under 4 Times Next Year's Earnings.EN
  8. 08SK Hynix HBM4 outlook weakens as DS Investment cuts target for SK Hynix stockEN
  9. 09SK Hynix Opens US HBM Era in Indiana as CEO Warns of Prolonged Memory CrunchEN
  10. 10South Korea unveils $520 billion investment plan with Samsung and SK Hynix to expand memory chip dominanceEN
  11. 11Apple faces unprecedented memory cost increases as RAM prices continue to surge, manufacturing bill climbs by $33 billionEN
  12. 12SK hynix Officially Launches US AI Investment Vehicle 'HYAICO'; Chey Tae-won Named Board Chairman, Acquires 510 Billion Won Stake in Penguin Solutions - BigGo FEN
  13. 13Scientists discover mysterious “lonely” brain waves linked to memory lossEN
  14. 14Nintendo Switch 2 sales plunge 41% as price hikes and memory crunch biteEN
  15. 15Chipfertigung: EU investiert Hunderte Millionen in Chipdesign-PlattformEN
  16. 16Route to Remember: Adaptive Memory Selection for LLM AgentsEN
  17. 17FlyHash for LLM Agent Memory: An Empirical Validation and a New ApplicationEN
  18. 18Reglos: A Self-Evolving Personal Memory Agent with Recursive Self-ImprovementEN
  19. 19Congress Is Cutting Off Transportation Investments that Help Families Save MoneyEN
  20. 20The ETS Investment Engine: Scaling Europe’s Strategic E-fuel Market for Shipping & AviationEN
  21. 21Xen Hypervisor Flaws Let One Malicious VM Read and Write Any Other VM's MemoryEN
  22. 22Xiaomi follows Li Auto with planned Sunwoda EVB investment to deepen battery tiesEN
  23. 23SK Hynix Says Memory Is Sold Out Through 2029. Micron Is a Winner, TooEN
  24. 24Qualcomm Validates HBC Stacked Memory Ahead of 2027 Dragonfly AI250 SamplingEN
  25. 25Article: Systemic Approach to Memory, Knowledge, and Context in Agentic AI ArchitecturesEN
  26. 26Samsung, SK hynix split strategies as AI boom drives record profits in Korea - ChosunbizEN
  27. 27SK hynix Warns RAM Shortages Could Last Until 2030EN
  28. 28SK hynix Just Became My Favorite Memory PlayEN
  29. 29HBM explained: the AI memory behind SK Hynix’s record profits and rising chip pricesEN
  30. 30Media rights squeeze, US investment and AI tech: The sports business trends from Sportel 2026EN

All figures and quotations in this text come from the sources listed below.

Content prepared by the editorial team with AI assistance.

Rachel Nwosu

Rachel Nwosu

AI, models and technology

Rachel Nwosu covers AI, models and technology for FLASH24, working from public model documentation, benchmark releases and repository histories rather than press summaries, and she skips announcements that arrive without reproducible numbers. She checks training-data claims against dataset cards and reruns reported metrics where code is available. She spends much of her week interviewing researchers and engineers, tracking model launch calendars, and comparing vendor benchmarks with independent evaluations. Outside the desk she runs 3D printers, restores old computers, and tests how models learn from internet junk. She does not publish benchmark figures she cannot trace to a source.

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