SANTA CLARA, CALIFORNIA / RankWire.AI / – Nvidia is planning to implement price increases exceeding 15% for numerous AI server configurations set for shipment in early 2027. These adjustments impact systems based on Vera Rubin and Grace Blackwell technology. The ultimate increase varies depending on chip generation, memory capacity, and system design. Nvidia has not revealed a singular, companywide price hike covering all server configurations. Instead, manufacturers assembling AI systems have communicated updated pricing to major data center clients.
Microsoft, Google, and Oracle are among the leading cloud providers purchasing large quantities of accelerated computing hardware. Their data centers utilize AI servers for model training, inference, and cloud service delivery. Throughout 2026, memory has emerged as one of the most significant cost pressures across these systems. Modern AI servers integrate GPUs with high-bandwidth memory, server DRAM, storage, and high-speed networking. The strong demand for these components has kept supply shortages tight in various segments of the memory market.
TrendForce forecasted that contract prices for conventional DRAM would rise between 13% and 18% during the third quarter of 2026. It also predicted NAND Flash contract prices to increase by 10% to 15% over the same period. Server DRAM remains particularly limited as memory manufacturers allocate increased capacity to AI and data center products. The rising memory costs have driven up the expenses involved in constructing advanced computing systems. These increases are a key factor shaping the pricing environment for next-generation AI servers.
Memory price pressures influence AI infrastructure costs
In 2026, Nvidia reports that Vera Rubin entered full production with server manufacturers and supply-chain partners. 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. The platform is aimed at large-scale AI workloads within cloud and hyperscale data centers. It succeeds Grace Blackwell as Nvidia’s newest rack-scale computing architecture.
Grace Blackwell remains a central platform in current AI data center deployments. The GB200 NVL72 system links 36 Grace CPUs with 72 Blackwell GPUs inside a liquid-cooled rack. Nvidia designed this platform to function as a single large NVLink computing domain. The pricing adjustments associated with these systems vary based on hardware configuration rather than following a fixed percentage. Factors like memory capacity, processor generation, and rack design all influence the final cost of each server setup.
Growing server demand tightens memory supply even further
As artificial intelligence demand continues to absorb production capacity, memory manufacturers have shifted more output toward server and high-performance products. TrendForce has noted that this shift has reduced the supply of some PC and consumer memory categories. Data center operators also maintained their large-volume purchases of server memory throughout 2026. The research firm predicts that server DRAM availability will remain constrained into 2027 as demand surpasses new supply, continuing to influence component prices across AI infrastructure.
Following another quarter of record data center revenue, Nvidia is entering this pricing phase. The company announced fiscal first-quarter revenue of $81.6 billion for the period ending April 26, 2026. Its Data Center segment achieved $75.2 billion, an increase of 92% from the same quarter last year. Nvidia also provided a forecast of second-quarter revenue at approximately $91 billion, plus or minus 2%. The company is scheduled to release its fiscal second-quarter results on Aug. 26, offering the latest update on its financial performance.