Nvidia’s Vera Rubin AI Chips Now in Full Production
▼ Summary
– Nvidia’s next-generation Vera Rubin AI superchip platform is in full production and on schedule to begin arriving to customers later this year.
– The Rubin system is expected to drastically reduce AI operating costs, cutting them to about one-tenth of current levels and requiring far fewer chips for training.
– Major partners Microsoft and CoreWeave will be among the first to offer Rubin-powered services, with Microsoft planning to install thousands of the chips in new data centers.
– The announcement aims to reassure investors that Rubin is on track, countering rumors of delays, following a previous delay with the Blackwell chips due to a design flaw.
– While demand for Rubin will be high, some customers like OpenAI are investing in custom chips, but Nvidia’s tightly integrated platform is becoming a harder-to-displace full AI system.
Nvidia has confirmed its next-generation Vera Rubin AI superchip platform is now in full production, with the first systems expected to reach customers later this year. CEO Jensen Huang made the announcement at a CES press event, signaling a major step forward for the company’s roadmap. The new platform promises to dramatically reduce the cost of running advanced AI models, potentially cutting operational expenses to roughly one-tenth of the current leading Blackwell system. This leap in efficiency could make it significantly more challenging for clients to justify moving away from Nvidia’s hardware ecosystem.
The performance gains are substantial. According to the company, the Rubin platform can train certain large AI models using approximately one-fourth as many chips as the Blackwell architecture requires. This combination of reduced chip count and lower operational cost represents a powerful value proposition aimed at solidifying Nvidia’s market dominance. Early adoption is already underway, with partners Microsoft and CoreWeave slated to be among the first to offer cloud services powered by Rubin chips. Notably, two major AI data centers Microsoft is constructing in Georgia and Wisconsin are planned to eventually house thousands of these new processors.
Nvidia is also expanding its software partnerships to complement the new hardware. The company revealed a collaboration with Red Hat, a major provider of open-source enterprise software, to develop more products optimized for the Rubin system. This move underscores a strategic push to offer a more complete, vertically integrated solution. The platform itself is a complex assembly of six different chips, including the Rubin GPU and the Vera CPU. These components are fabricated using Taiwan Semiconductor Manufacturing Company’s advanced 3-nanometer process and incorporate cutting-edge bandwidth memory technology, all linked together by Nvidia’s own sixth-generation interconnect.
Huang described each element of the system as “completely revolutionary and the best of its kind.” While the “full production” terminology can be ambiguous in the semiconductor industry, often starting at low volumes for testing before a full ramp-up, the announcement serves a clear strategic purpose. Industry analysts suggest it is a direct message to investors and the market that the project remains on schedule, countering rumors of potential delays. The company has stated that systems built on Rubin should begin arriving in the second half of 2026.
This confidence follows a previous setback. In 2024, Nvidia faced delays in delivering its Blackwell chips due to a design flaw that caused overheating in server racks, though shipments were back on track by mid-2025. The timely progress on Rubin is therefore critical. As the AI industry’s hunger for computing power grows exponentially, demand for the new platform is expected to be immense. Cloud providers and software firms routinely compete fiercely for access to Nvidia’s latest hardware.
However, a long-term strategic challenge is emerging. Major players like OpenAI are investing in custom silicon designs, such as its partnership with Broadcom, to gain more control over their hardware destiny. This trend toward in-house or bespoke chips represents a potential threat to Nvidia’s business model. Despite this, analysts note that Nvidia’s strategy is evolving. The company is positioning itself not just as a GPU supplier but as a comprehensive AI system architect, offering a tightly integrated stack spanning compute, networking, memory, and software. This holistic approach, combining groundbreaking hardware with a robust ecosystem, may make its platform increasingly difficult for competitors to displace, even as some customers explore their own chip designs.
(Source: Wired)
