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Nvidia Rubin delay may lift Blackwell chip shipments

Nvidia’s Rubin AI accelerator may be delayed beyond this year as HBM4 validation, power use, and cooling issues persist.

The shift potentially affect South Korean suppliers Samsung Electronics and SK hynix.

TrendForce cut Rubin’s share of Nvidia’s high-end GPUs this year to 22% from 29%, while raising Blackwell’s share to 71% from 61%.

Nvidia may have cut its Rubin production target to 1.5 million units from 2 million after delays in HBM4 validation at SK hynix and Micron, while Samsung Electronics said it began mass production of HBM4 in February.

🔗 Source: Chosun Daily

🧠 Food for thought

Implications, context, and why it matters.

Nvidia’s technical demands helped drive the HBM4 delays

  • Validation problems tie back to Nvidia raising the technical bar for its Rubin platform 1.
  • In the third quarter of 2025, Nvidia updated High Bandwidth Memory 4 (HBM4) specifications. It asked for per pin speeds above 11 gigabits per second (Gbps), which pushed SK Hynix, Samsung, and Micron to rework and resubmit samples 1.
  • The update brought tough production constraints, even for top memory makers.
  • Samsung’s advanced 1c DRAM process, a newer memory manufacturing technology needed for this product, starts near 60% yield. That limits Samsung’s ability to cover Nvidia’s full volume on its own 2.
  • SK Hynix has reportedly struggled to hit the 11 Gbps target during early reliability evaluations 2.

The HBM4 bottleneck boosts Nvidia’s leverage in AI hardware

  • Nvidia bought more than 60% of global HBM supply in 2024. That purchase scale lets its schedule sway the advanced memory market 3.
  • Delays can spill over to rivals like AMD. Its upcoming MI400 accelerator, an AI chip for data center workloads, also needs steady HBM4 supply, so disruptions can shift competing launch plans 3.
  • Nvidia may relax some requirements to keep supply on track 2.
  • Industry sources say Nvidia could buy lower tier 10.6 Gbps HBM4 plus top tier 11.7 Gbps parts. That mix would reduce strain on suppliers and secure enough volume for accelerators 2.

Recent Nvidia developments

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