According to Kuaitech on August 31st， NVIDIA has announced that GTC 2026， one of NVIDIA’s most significant annual events， will be held in San Jose， California， from March 16th to 19th， 2026.
GTC has consistently served as a key indicator for the evolution of GPU technology and data center advancements， drawing considerable interest from developers， researchers， and investors worldwide. This timing is strategic， allowing NVIDIA to showcase its latest innovations and roadmap in the burgeoning AI and high-performance computing landscape.
At this year’s GTC 2025， NVIDIA outlined its future GPU hardware roadmap， confirming upgrades for the Blackwell Ultra (NVL72) and announcing the upcoming Vera Rubin architecture for 2026. The Vera Rubin architecture is slated to scale with NVL144 systems， designed for large-scale deployments. This strategic progression of hardware architectures demonstrates NVIDIA’s commitment to continuous improvement and catering to the escalating demands of data-intensive workloads.
Looking further ahead， NVIDIA also provided a glimpse into its future plans with the Rubin Ultra (NVL576) expected in 2027 and the next-generation Feynman architecture planned for release in 2028. This forward-looking roadmap underscores NVIDIA’s proactive approach to innovation and its ability to anticipate and meet future technological needs.
In terms of software， NVIDIA also made significant announcements at the 2025 conference， introducing NVIDIA Dynamo， described as the operating system for AI factories， Isaac GR00T N1， a foundational model for robotics， Cosmos AI model for synthetic training data generation， and Newton， a new physics engine for robot simulation. These software advancements are crucial for unlocking the full potential of NVIDIA’s hardware， enabling more sophisticated AI development and robotic applications.
The upcoming GTC 2026 conference is widely anticipated to focus on the launch of the Rubin GPU and the Vera CPU. Discussions are expected to delve into their deployment timelines， performance capabilities， and enhanced scalability， particularly in comparison to the current Blackwell architecture. The introduction of these new architectures will be critical for NVIDIA in maintaining its leadership position in the AI hardware market， especially as competition intensifies.
