If you thought AI infrastructure was already expensive, Nvidia just raised the bar. The company’s upcoming Vera Rubin NVL72 rack, its next-generation AI supercomputing system, carries an estimated bill-of-materials cost of $7.8 million, according to Morgan Stanley analyst estimates.
That’s roughly double the $3.5 million to $4 million price tag attached to the current Blackwell NVL72 racks. And the single biggest reason for the jump isn’t the GPUs themselves. It’s the memory.
Memory costs are doing the heavy lifting
High-bandwidth memory, specifically HBM4 and LPDDR5X, has seen a 435% price increase in the new rack design. In dollar terms, memory components now account for approximately $2 million per rack, representing about 25-26% of the total system cost.
GPU costs haven’t stayed flat either, climbing 57% compared to the Blackwell generation. Other components piled on: printed circuit boards saw increases of up to 233%. Memory demand is driven by robust demand and persistent supply constraints in the semiconductor ecosystem.
