SANTA CLARA, CALIFORNIA / RankWire.AI / – Nvidia is planning to implement price increases surpassing 15% for numerous AI server configurations expected to be shipped in early 2027. These adjustments target systems based on Vera Rubin and Grace Blackwell technologies. The magnitude of the increases varies depending on chip generation, memory capacity, and system design. Nvidia has not announced a uniform, companywide price hike covering all server models. Instead, manufacturers involved in assembling AI systems have relayed revised pricing details to major data center clients.
Microsoft, Google, and Oracle are among the leading cloud service providers purchasing large quantities of accelerated computing hardware. Their data centers rely on AI servers for tasks including model training, inference, and cloud offerings. During 2026, memory has emerged as one of the most significant cost pressures affecting these systems. Modern AI servers integrate GPUs with high-bandwidth memory, server DRAM, storage, and fast networking components. The strong demand for these parts has kept supply shortages prevalent in several memory market segments.
TrendForce forecasted that standard DRAM contract prices would increase by 13% to 18% in the third quarter of 2026. It also projected NAND Flash contract prices would rise by 10% to 15% over the same period. Server DRAM remains especially constrained as memory manufacturers shift more production capacity toward AI and data center applications. As a result, the rising memory prices have heightened the overall costs of constructing advanced computing systems. These increases significantly influence the pricing landscape for next-generation AI servers.
Memory cost pressures intensify in AI infrastructure
Nvidia reports that Vera Rubin entered full production with server manufacturers and supply chain partners in 2026. Systems utilizing the platform are scheduled for release in the latter half of the year. Rubin combines the Vera CPU and Rubin GPU with NVLink 6 and various networking technologies. This platform is aimed at supporting large-scale AI workloads in cloud and hyperscale data centers. It follows Grace Blackwell as the company’s latest rack-scale computing architecture.
Grace Blackwell continues to serve as a fundamental platform in current AI data center deployments. The GB200 NVL72 system pairs 36 Grace CPUs with 72 Blackwell GPUs inside a liquid-cooled rack. Nvidia designed this setup to function as a unified NVLink computing domain. Pricing adjustments associated with these systems are based on hardware configuration rather than a single uniform percentage. Factors such as memory capacity, processor generation, and rack design influence the final cost of each server setup.
Demand for servers sustains tight memory supply conditions
Memory manufacturers have shifted more production toward server and high-performance products, driven by increasing artificial intelligence demand. TrendForce has indicated this shift has reduced the supply of some PC and consumer memory categories. Data center operators continued purchasing substantial volumes of server memory throughout 2026. The research firm anticipates that server DRAM availability will remain limited into 2027, as demand outpaces new supply. This environment continues to exert influence over component prices within AI infrastructure.
Following another quarter of record data center revenue, Nvidia is entering 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, representing a 92% increase from the same quarter a year earlier. Nvidia also provided an outlook for second-quarter revenue at approximately $91 billion, plus or minus 2%. The company is set to release its fiscal second-quarter results on Aug. 26, offering the latest update on its financial performance.