New hardware catalysts are on the horizon: Nvidia's Rubin rack and AMD's Helios rack are both expected to begin shipping in Q4 2026 .
Goldman Sachs released a separate forecast in June 2026 projecting the global server market reaching $1.1 trillion by 2028, with AI server rack revenue growing at a 118% CAGR to $561.4 billion, or 51% of total market revenue .
Hyperscale capital expenditure is the engine behind these server shipment forecasts, and the numbers are staggering:
Supporting data from other sources paints a consistent picture:
Perhaps the most significant structural shift documented in the tracker is the rapid rise of custom application-specific integrated circuits (ASICs) for AI workloads. Hyperscalers are increasingly deploying their own silicon to reduce dependence on merchant GPUs and optimize for specific inference and training tasks .
Broadcom has emerged as the leading AI ASIC design partner. Key developments include:
Marvell is now ramping ASIC production for all four major cloud service providers (AWS, Microsoft, Google, and others) . Marvell designs AWS Trainium and Microsoft Maia
. The company projects up to ~$11 billion in AI ASIC revenue in 2026
.
The overarching theme from Bernstein's Q2 2026 tracker is that AI infrastructure investment remains on a steep upward trajectory, driven by both GPU-based systems (Nvidia and AMD) and a rapidly scaling custom ASIC ecosystem led by Broadcom and Marvell, with no sign of a near-term capex pullback among the largest cloud providers. While merchant GPUs still dominate — TrendForce projects GPUs will account for 69.7% of AI server shipments in 2026 — the ASIC share is growing at a faster clip and represents a fundamental shift in how hyperscalers are building out their AI compute capacity.