SANTA CLARA, CALIFORNIA / RankWire.AI / – Nvidia is planning price increases exceeding 15% for numerous AI server configurations expected to ship in early 2027. These adjustments impact systems based on Vera Rubin and Grace Blackwell technologies. The final price hikes vary depending on chip generation, memory capacity, and system design. Nvidia has not announced a comprehensive companywide increase covering all server configurations. Instead, manufacturers assembling AI systems have relayed revised pricing to large data center clients.
Microsoft, Google, and Oracle are among the leading cloud providers procuring substantial volumes of accelerated computing hardware. Their data centers deploy AI servers for training models, inference tasks, and cloud services. Throughout 2026, memory has emerged as one of the most significant cost pressures within these systems. Modern AI servers integrate GPUs with high-bandwidth memory, server DRAM, storage solutions, and high-speed networking. The high demand for these components has kept supplies tight in several segments of the memory market.
TrendForce predicts that contract prices for conventional DRAM will rise by 13% to 18% during the third quarter of 2026. Simultaneously, NAND Flash contract prices are expected to increase by 10% to 15% over the same period. Server DRAM remains particularly limited as memory manufacturers allocate more capacity toward AI and data center applications. The rising memory costs have elevated the expense of constructing advanced computing systems, forming a key element of the pricing environment for next-generation AI servers.
Memory price pressures intensify across AI infrastructure
According to Nvidia, Vera Rubin reached full production with server manufacturers and supply-chain partners in 2026. Systems utilizing this platform are expected to become available in the second half of the year. Rubin combines the Vera CPU and Rubin GPU with NVLink 6 and various networking technologies. This platform aims to support large-scale artificial intelligence workloads in cloud and hyperscale data centers. It follows Grace Blackwell as Nvidia’s newest rack-scale computing architecture.
Grace Blackwell continues to be a central platform in current AI data center deployments. The GB200 NVL72 system links 36 Grace CPUs with 72 Blackwell GPUs within a liquid-cooled rack. Nvidia designed this platform to operate as a single, large NVLink computing domain. Price adjustments related to these systems are determined by hardware configuration rather than a fixed percentage. Variations in memory capacity, processor generation, and rack design all influence the final cost of each server setup.
Demand for servers sustains tight memory supply conditions
As AI demand continues to grow, memory manufacturers have shifted more production toward server and high-performance products. TrendForce indicated this shift has reduced the supply available for certain PC and consumer memory categories. Data center operators also maintained high-volume purchases of server memory through 2026. The research firm predicts that server DRAM availability will remain constrained into 2027 as demand outpaces new supply. This environment continues to influence component costs across AI infrastructure.
Following another quarter of record data center revenue, Nvidia enters this pricing period. The company reported fiscal first-quarter revenue of $81.6 billion for the period ending April 26, 2026. Data Center revenue reached $75.2 billion, marking a 92% increase compared to the same quarter last year. Nvidia has also projected second-quarter revenue of $91 billion, plus or minus 2%. The company is scheduled to release its fiscal second-quarter financial results on Aug. 26, providing an update on its latest performance.