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SemiAnalysis: AI Silicon Shortage — HBM Bottleneck and N3 Wafer Dominance · history

Version 15

2026-06-13 18:46 UTC · 172 items

What

HBM memory and TSMC N3 logic remain the two binding constraints on AI accelerator production. The NVIDIA-Intel foundry relationship is active but not yet closed: additional reporting describes NVIDIA as in 'early testing/evaluation' stages with Intel's 18A process [20], with Intel reportedly 'working to finalize commitments' [21] for a multi-die GPU targeting 2028 [23] — some sources frame Intel as a potential 'backup AI foundry' rather than a co-primary supplier [22]. Earlier publications named NVIDIA's 'Feynman' GPU architecture as the specific product [16][17][18][19]. SK Hynix has formalized a multi-year HBM co-development partnership with NVIDIA [9] and published a bullish 2026 HBM supercycle outlook [11], while memory supply remains tight despite aggressive capacity expansion by both SK Hynix and Samsung [5].

Why it matters

Whether Intel finalizes a meaningful volume commitment from NVIDIA determines whether 2028 will see real AI chip production outside TSMC at scale, or just a design evaluation. The SK Hynix-NVIDIA co-development deepens HBM supply concentration around the dominant accelerator maker, leaving AMD and other GPU makers structurally disadvantaged in accessing leading-edge memory — a gap that near-term capacity plans do not close.

Open questions

  • Has Intel finalized its foundry commitment from NVIDIA, or is the relationship still in early evaluation as multiple sources now characterize it [20][21]?

  • Does the 'backup AI foundry' framing [22] accurately describe Intel's intended role — a secondary option rather than a primary supplier — and how does that scope Intel's 18A volume targets for 2028?

  • Can Intel's 18A process meet both the Google TPU order [15] and potential NVIDIA Feynman GPU commitments at volume by 2028, given that both engagements target the same production window?

  • Does the SK Hynix–NVIDIA co-development partnership give NVIDIA preferential HBM4/HBM5 allocation, structurally disadvantaging AMD and other accelerator makers competing for the same supply [9]?

Narrative

HBM memory and TSMC's N3 process node are the two binding constraints on AI accelerator production. SemiAnalysis identified HBM wafer supply — not the earlier CoWoS packaging bottleneck — as the primary scarce resource [1]. SK Hynix has sold out its DRAM, NAND, and HBM capacity into 2026 [2], and Micron has similarly sold out its 2026 HBM allocation while committing roughly $200 billion to long-term memory capacity expansion [3][4]. Memory supply remains tight despite aggressive investment by both SK Hynix and Samsung, with new capacity being absorbed by AI demand faster than it comes online [5]. On the logic side, AI is projected to consume approximately 60% of TSMC's N3-family output in 2026, rising to roughly 86% in 2027 [6], with TSMC posting +41% year-over-year Q1 2026 revenue at all-time-high margins [7][8].

The HBM supply relationship is consolidating around the dominant accelerator maker. SK Hynix and NVIDIA formalized a multi-year co-development partnership in June 2026 covering NVIDIA's Vera Rubin platform and future systems [9], making SK Hynix a design collaborator on next-generation AI memory rather than a pure supplier. Jensen Huang stated publicly that NVIDIA consumes essentially all available HBM output [10]. SK Hynix's own 2026 market outlook is explicitly bullish on an HBM-led supercycle [11], and Bernstein analysts project HBM4 pricing will nearly double from $16.6/GB to $37/GB by 2027 [12]. Micron crossed $1 trillion in market cap as investor conviction in the HBM supercycle thesis holds [13].

Intel is tied to two AI chip production engagements targeting 2028, but the scope of each remains open. Google confirmed an order of more than 3 million TPUs from Intel's foundry for 2028 delivery [14][15]. The NVIDIA-Intel relationship is more unsettled: earlier publications named NVIDIA's 'Feynman' GPU architecture as the specific product using Intel Foundry for some components in a multi-die design [16][17][18][19], but additional reporting describes the arrangement as NVIDIA in early testing/evaluation with Intel working to finalize commitments [20][21] — some sources frame Intel as a 'backup AI foundry' rather than a co-primary supplier [22]. The 2028 target timeline is consistent across all accounts [23], but whether this becomes a finalized volume commitment or an evaluation exercise is unresolved. In the near term, AMD's MI455 and VR200 systems remain engineering samples with incomplete software stacks [24], and Intel's Crescent Island targets AI inference by end of 2026 without HBM, competing on cost rather than training performance [25][26].

A third constraint layer sits below the GPU and memory discussion. Each AI server rack requires tens of thousands of MLCCs — multi-layer ceramic capacitors each costing under $1 — now experiencing price hikes and extended lead times [27]. Multiple industry publications confirm AI server demand as the driver of renewed MLCC shortages, with tantalum capacitors similarly strained as MLCC substitution falls short [28][29][30][31].

Timeline

  • 2026-03-01: SemiAnalysis publishes 'The Great AI Silicon Shortage,' identifying HBM wafer supply — not CoWoS packaging — as the binding constraint on AI accelerator production. [1][46]
  • 2026-05-30: SemiAnalysis projects AI consuming 60% of TSMC N3 output in 2026, rising to 86% in 2027. [32][47][6][48]
  • 2026-05-31: SK Hynix confirmed sold out of DRAM, NAND, and HBM into 2026; Micron confirms 2026 HBM sold out and commits roughly $200 billion to long-term memory capacity. [2][3][49][4]
  • 2026-05-31: SK Hynix reports delays to HBM4 mass production while ramping 1c DRAM 8-fold and building new HBM4 packaging plants. [35][50][51][52]
  • 2026-06-01: TSMC posts +41% year-over-year Q1 2026 revenue with all-time-high margins; Arizona Phase 1 fab profitable ahead of schedule. [34][7][8]
  • 2026-06-01: Intel announces Crescent Island GPU targeting AI inference by end of 2026, without HBM, competing on cost and thermal efficiency. [25][26]
  • 2026-06-02: SK Hynix discloses plans to double DRAM wafer capacity by 2031 while projecting memory supply tightness until at least 2030. [36][37]
  • 2026-06-03: SemiAnalysis clarifies AMD VR200 and MI455 racks at CoreWeave and Microsoft are engineering samples with incomplete software stacks and no production tokens. [24]
  • 2026-06-05: SemiAnalysis flags MLCCs as an overlooked AI server supply constraint; multiple publications corroborate AI-driven shortages of the sub-$1 passive components required in tens of thousands per rack. [27][28][29][30][31]
  • 2026-06-06: Micron crosses $1 trillion in market cap as investor conviction in the HBM supercycle thesis strengthens. [13]
  • 2026-06-08: SK Hynix and NVIDIA formalize a multi-year HBM co-development partnership covering NVIDIA's Vera Rubin platform and future AI infrastructure. [9][10]
  • 2026-06-08: Bernstein projects HBM4 pricing to nearly double from $16.6/GB to $37/GB by 2027, contra consensus that memory stocks have peaked. [12]
  • 2026-06-08: Google's order of 3M+ TPUs from Intel foundry for 2028 delivery confirmed across multiple publications; Intel stock surges on the news. [14][53][15][54][42]
  • 2026-06-09: TrendForce reports NVIDIA is evaluating Intel's 18A process node for a multi-die GPU design targeting 2028. [55]
  • 2026-06-10: Multiple publications report NVIDIA's 'Feynman' GPU architecture will use Intel Foundry for some components in a multi-die chiplet design targeting 2028. [16][17][18][19]
  • 2026-06-11: Additional reporting characterizes the NVIDIA-Intel 18A arrangement as early testing/evaluation with Intel still working to finalize commitments; some sources frame Intel as a 'backup AI foundry' for the multi-die GPU. [22][20][21][23]
  • 2026-06-11: SK Hynix publishes a 2026 market outlook projecting an HBM-led memory supercycle through 2026 and beyond. [11]

Perspectives

SemiAnalysis

AI's dominance of leading-edge semiconductor capacity is structural; N3 is the main supply bottleneck, H100 spot pricing is stable, the Ornn index is methodologically misleading, AMD MI455/VR200 racks are engineering samples, and MLCCs are an overlooked passive-component constraint in AI server supply chains.

Evolution: Consistent; the MLCC shortage flag has been corroborated by multiple industry sources.

[32][6][1][7][33][24][27]

NVIDIA

Structurally dominant in AI accelerator production; the multi-year SK Hynix co-development partnership extends dominance into memory design; Jensen Huang states NVIDIA consumes essentially all available HBM supply; the Feynman GPU architecture reportedly targets Intel Foundry for some components in a 2028 multi-die design, though that commitment is still in evaluation and finalization.

Evolution: New items describing the arrangement as early testing with Intel working to finalize commitments slightly soften the earlier 'will use Intel Foundry' framing — the deal is active but not yet closed.

[9][10][16][17][18][19][20][21][23]

TSMC

AI demand is structurally robust through at least 2027–2028; Q1 2026 delivered all-time-high margins on +41% growth; TSMC Arizona is profitable ahead of schedule; AI chips are projected to consume 86% of N3 output by 2027.

Evolution: Consistent; Feynman GPU reports add a competitive pressure signal for the 2028+ horizon, though TSMC's near-term dominance is not disputed by any source.

[6][34][7][8]

SK Hynix

Committed to HBM leadership through a multi-year co-development partnership with NVIDIA; targets DRAM capacity doubling by 2031; expects memory supply to remain tight until at least 2030; its own 2026 market outlook is explicitly bullish on an HBM-led supercycle.

Evolution: The 2026 market outlook publication adds a direct bullish signal from SK Hynix itself, consistent with prior disclosures.

[35][2][36][9][37][11]

Micron

2026 HBM sold out; committed roughly $200 billion to an AI memory supercycle; crossed $1 trillion in market cap with analysts positioning it as a multi-year AI infrastructure beneficiary.

Evolution: Consistent.

[3][4][13]

Intel

On two foundry tracks targeting 2028: Google's confirmed 3M+ TPU order and NVIDIA's Feynman GPU reported to use Intel Foundry for some components, though that NVIDIA commitment is still in evaluation and finalization; separately targeting AI inference with the HBM-free Crescent Island by end of 2026; Cadence is reportedly designing for Intel's future 14A node beyond 18A.

Evolution: New items frame Intel as working to finalize the NVIDIA commitment and as a potential backup foundry, adding negotiation context to the earlier framing that treated the deal as more settled.

[25][26][14][15][16][17][18][19][22][21]

Samsung

Scaling HBM production to meet AI demand while facing HBM4 yield challenges and rollout delays that reinforce SK Hynix's structural lead in AI memory.

Evolution: Consistent; no new disclosures this pass.

[38][39][40][41]

Independent market analysts and investors

The HBM bottleneck is confirmed and investable; Bernstein projects HBM4 nearly doubles to $37/GB by 2027; Intel stock surged on the Google foundry news; the 'early testing/evaluation' characterization adds modest uncertainty to the Intel foundry thesis relative to earlier confident framing.

Evolution: New items introduce some hedging on the Intel foundry thesis; the investment case remains intact but the deal maturity is less settled than last pass suggested.

[12][42][43]

Tensions

  • Earlier reports state NVIDIA's Feynman GPU 'will use Intel Foundry for some components' [16][18], while newer items describe NVIDIA as in 'early testing/evaluation stages' with Intel still 'working to finalize commitments' [20][21] — the two framings assign different levels of maturity to the same deal. [16][18][20][21]
  • NVIDIA's Feynman GPU is reported to use Intel Foundry for 'some components' in a multi-die design [18], but some sources frame Intel as a 'backup AI foundry' [22] while TSMC is projected to supply 86% of N3 wafers to AI by 2027 [6] — the scope of Intel's role (limited chiplet versus meaningful die area) is unspecified and unresolved. [18][22][6]
  • The NVIDIA–SK Hynix co-development partnership structurally concentrates HBM supply toward the dominant accelerator maker [9], while AMD's MI455/VR200 remain engineering samples [24] and Intel's Crescent Island deliberately avoids HBM [26] — neither competitor is positioned to access leading-edge HBM at scale in the near term. [9][24][26]
  • Investor framing positions Micron as an 'AI gatekeeper' [44][45], but SK Hynix holds dominant HBM market share, leads HBM4 development, and has formalized a co-development partnership with NVIDIA [9] — the two narratives assign structural primacy to different memory suppliers. [44][45][2][9]
  • SK Hynix is delaying HBM4 mass production [35] while targeting a 2031 DRAM capacity doubling [37] and publishing a bullish 2026 HBM supercycle outlook [11] — near-term execution risk coexists with confident long-term supply projections. [35][37][11]

Sources

  1. [1] The Great AI Silicon Shortage - SemiAnalysis — reactive:great-ai-silicon-shortage
  2. [2] SK Hynix sells out DRAM, NAND, and HBM capacity into 2026 amid ... — reactive:great-ai-silicon-shortage
  3. [3] Micron's Sold Out 2026 HBM And US$200b Bet On AI Demand — reactive:micron-hbm-bull-case
  4. [4] Micron's AI Supercycle Accelerates (NASDAQ:MU) | Seeking Alpha — reactive:great-ai-silicon-shortage
  5. [5] Samsung and SK are expanding fast, but why is memory still in short supply? | SemiWiki — reactive:aws-garman-a100-demand
  6. [6] Our work shows AI taking roughly 60% of N3 family wafers in 2026 and stepping up to about 86% in 2027, which is a regime… — SemiAnalysis Twitter (2026-05-30)
  7. [7] After posting +41% y/y growth with ATH GM and OM in 1Q26, TSMC is tracking to high-30s growth in CY26. We raised our TSM… — SemiAnalysis Twitter (2026-06-01)
  8. [8] The foundry industry hit a record $48.8B in 1Q26, +32% y/y and +3% q/q in seasonally soft Q1, marking the 9th consecutiv… — SemiAnalysis Twitter (2026-06-01)
  9. [9] SK hynix and NVIDIA just formed a multi-year memory partnership to build the chips behind the next wave of AI factories. — Rohan Paul Twitter (2026-06-08)
  10. [10] In Seoul, Nvidia CEO Jensen Huang handed out SK Hynix x 7-Eleven HBM Chips snack bags while addressing the crowd. — Rohan Paul Twitter (2026-06-08)
  11. [11] 2026 Market Outlook: SK hynix's HBM to Fuel AI Memory Boom — reactive:great-ai-silicon-shortage
  12. [12] Most investors think memory stocks have peaked but they are completely wrong. (Save this). — Milk Road AI Twitter (2026-06-08)
  13. [13] Micron crossed $1 trillion in market cap and it is still undervalued (Save this). — Milk Road AI Twitter (2026-06-06)
  14. [14] The Information reports that Google has picked Intel to manufacture 3M+ Google TPUs in 2028. — Rohan Paul Twitter (2026-06-08)
  15. [15] Google orders 3 million TPUs from Intel as TSMC strains - Quartz — reactive:great-ai-silicon-shortage
  16. [16] NVIDIA Feynman and Intel Foundry: New Report, Old Core – But With an Important Packaging Clue|igor´sLAB — reactive:great-ai-silicon-shortage
  17. [17] Nvidia's Next-Gen GPU Could be Coming to Intel Foundry — reactive:great-ai-silicon-shortage
  18. [18] Nvidia Feynman GPUs to use Intel Foundry for some components — reactive:great-ai-silicon-shortage
  19. [19] NVIDIA to Build GPUs on Intel Foundry from 2028: Report - Reddit — reactive:great-ai-silicon-shortage
  20. [20] $NVDA Nvidia is in early testing/evaluation stages with $INTC Intel's ... — reactive:great-ai-silicon-shortage
  21. [21] Intel is reportedly 'working to finalize commitments from Nvidia' as a foundry partner, suggesting gaming potential for the 18A node : r/hardware — reactive:great-ai-silicon-shortage
  22. [22] Key facts: Intel tests 18A multi‑die; backup AI foundry; Cadence 14A — TradingView News — reactive:great-ai-silicon-shortage
  23. [23] NVIDIA to Build GPUs on Intel Foundry from 2028: Report — reactive:great-ai-silicon-shortage
  24. [24] IMPORTANT: it is important to understand that the CoreWeave & Microsoft photos are still Engineering/Quality Samples… — SemiAnalysis Twitter (2026-06-03)
  25. [25] Intel: Our upcoming AI chip will be cheaper, run cooler than Nvidia, AMD options — Ars Technica AI (2026-06-01)
  26. [26] Intel's new inference chip, Crescent Island, doesn't use HBM. — reactive:great-ai-silicon-shortage (2026-06-05)
  27. [27] Nobody is asking who makes the <$1 multi-layer ceramic capacitor (MLCC) that keeps voltage stable across every chip i… — SemiAnalysis Twitter (2026-06-05)
  28. [28] MLCC Shortages Return as AI Server Demand Strains Capacity - Astute Group — reactive:great-ai-silicon-shortage
  29. [29] MLCC Consider Price Increase as AI Demand Outpaces Supply — reactive:great-ai-silicon-shortage
  30. [30] AI server boom strains tantalum capacitors; MLCC substitution falls ... — reactive:great-ai-silicon-shortage
  31. [31] AI drives MLCC shortage ... — reactive:great-ai-silicon-shortage
  32. [32] It also explains why the bottleneck conversation is migrating away from CoWoS, which is finally easing, and onto memory,… — SemiAnalysis Twitter (2026-05-30)
  33. [33] The recent Ornn H100 index drop to $2.63 (-7.72%) is confusing. But mostly because it's a misleading index. Our H100 hou… — SemiAnalysis Twitter (2026-06-02)
  34. [34] TSMC Arizona surprised. After ramping up strongly in CY25 ($2B+ revenue), Phase 1 net profit in 1Q26 alone exceeded the … — SemiAnalysis Twitter (2026-06-01)
  35. [35] SK hynix Delays HBM4 Mass Production and Capacity Expansion — reactive:aws-garman-a100-demand
  36. [36] SK hynix just said AI memory demand is now so large that it will double wafer capacity within 5 years, yet still expects… — Rohan Paul Twitter (2026-06-02)
  37. [37] SK hynix said to be planning to double DRAM capacity by 2031 - New Electronics — reactive:great-ai-silicon-shortage
  38. [38] Samsung and SK Hynix to scale up memory production capacity in ... — reactive:aws-garman-a100-demand
  39. [39] Samsung delays HBM4 rollout to 2026 due to yield challenges, all ... — reactive:aws-garman-a100-demand
  40. [40] Major tech firms shift to Samsung as TSMC capacity falls short | Jeffrey Cooper — reactive:great-ai-silicon-shortage
  41. [41] Samsung Breaks TSMC Monopoly, Supplies Tesla AI Chips | DBR — reactive:great-ai-silicon-shortage
  42. [42] 🟢 Intel Surges After Report Google May Use Its Foundry for AI Chips — reactive:great-ai-silicon-shortage (2026-06-08)
  43. [43] A massive concentration of institutional structural rotation is catching fire across the semiconductor landscape ahead o... — reactive:great-ai-silicon-shortage (2026-06-08)
  44. [44] FinancialContent - The Memory Supercycle: Why Micron Technology is the New AI Gatekeeper — reactive:great-ai-silicon-shortage
  45. [45] Micron Stock Up 100%: What the HBM Leader Plans for 2026 — reactive:great-ai-silicon-shortage
  46. [46] The Great AI Silicon Shortage — reactive:great-ai-silicon-shortage
  47. [47] The broader implication, which we work through in detail in the piece, is that the supply curve for frontier accelerator… — SemiAnalysis Twitter (2026-05-30)
  48. [48] One of the throughlines in our Great AI Silicon Shortage piece is that the conversation about leading-edge capacity has … — SemiAnalysis Twitter (2026-05-30)
  49. [49] Sold-Out HBM Supply and AI Tailwinds Point to Strong 2026 Growth — reactive:great-ai-silicon-shortage
  50. [50] HBM4 race accelerates: SK hynix builds new packaging plant and ... — reactive:aws-garman-a100-demand
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  52. [52] SK hynix Begins Expanding HBM4 Production Capacity with New ... — reactive:great-ai-silicon-shortage
  53. [53] Google orders over 3 million TPUs from Intel for 2028 as Nvidia tests ... — reactive:great-ai-silicon-shortage
  54. [54] Google taps Intel for 3M AI chips in 2028 - Mobile World Live — reactive:great-ai-silicon-shortage
  55. [55] [News] Intel Foundry Gains Momentum as Google Reportedly ... — reactive:great-ai-silicon-shortage