Glass Fiber Cloth: The Underlying Material Shortage in AI Infrastructure
Capacity constraints are not expected to ease until mid-2027, affecting lead times and costs across the AI server supply chain
Correction: An earlier version of this article incorrectly listed the English name of glass fiber cloth supplier 宏和電子材料 as "Hongho Precision Textile." The correct English name is Grace Fabric Technology. We apologize for the error and have updated the text and charts accordingly.
The AI infrastructure buildout is often discussed in terms of chips and computing power. But beneath the surface, a set of supply chain bottlenecks is quietly shaping the pace and cost of deployment. Last week, we looked at CPO testing. This week: glass fiber cloth.
The arrival of the Nvidia Rubin generation is reshaping the demand structure for advanced substrate and PCB materials. Compared to its predecessor, the Rubin GPU substrate has seen significant increases in both area and layer count. Furthermore, cableless designs have catalyzed new demand for midplanes and orthogonal backplanes. The introduction of the Rubin LPX rack, a disaggregated rack for inference, has further expanded the overall consumption of high-end glass fiber cloth.
Related report: 2026 Outlook: NVIDIA Rubin Drives New Wave of AI Hardware Upgrades
On the supply side, however, the market faces severe constraints. Nittobo, the leading manufacturer holding approximately 90% market share in T-glass and 60-70% in NER-glass, is not expected to bring new capacity online until mid-2027 at the earliest. Consequently, critical material gaps cannot be filled in the short term. Glass fiber cloth has transitioned from a rarely discussed “supporting role” to a critical bottleneck affecting the lead times and costs of the entire AI server supply chain.