NVIDIA debuts Rubin platform at CES 2026, delivering 50 petaflops, faster AI

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NVIDIA debuts Rubin platform at CES 2026, delivering 50 petaflops, faster AI
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NVIDIA says its Rubin platform is now in full production, delivering up to 50 petaflops and powering the next wave of agentic AI systems.

NVIDIA used the CES 2026 stage today to formally launch its new Rubin computing architecture, positioning it as the company’s most advanced AI hardware platform to date.CEO Jensen Huang said Rubin has already entered full production and will scale further in the second half of the year, signaling NVIDIA’s confidence in demand.

Huang framed Rubin as a direct response to the explosive growth in AI workloads, particularly large-scale training and long-horizon reasoning tasks. He told the audience that AI computation must continue to rise at an unprecedented pace.Rubin replaces NVIDIA’s Blackwell architecture, which itself succeeded Hopper and Lovelace.The update continues NVIDIA’s rapid hardware cadence that has helped turn the company into the world’s most valuable corporation.Built for agentic AIRubin takes its name from astronomer Vera Florence Cooper Rubin and introduces a six-chip architecture designed to work as a unified system.At the center sits the Rubin GPU, supported by major upgrades to interconnect and storage components.NVIDIA redesigned NVLink to address communication bottlenecks across large clusters. The company also expanded its BlueField data processing platform to manage growing memory demands from advanced AI systems.A new Vera CPU joins the architecture and targets agentic reasoning workloads.NVIDIA designed it to support AI systems that plan, remember context, and act over longer periods.Rubin systems are already scheduled for deployment across the AI ecosystem. Cloud providers, including partners such as Anthropic, OpenAI, and Amazon Web Services, plan to adopt the platform.NVIDIA also confirmed Rubin will power HPE’s Blue Lion supercomputer and the upcoming Doudna system at Lawrence Berkeley National Laboratory.Speed and efficiency gainsNVIDIA claims Rubin delivers major performance improvements over Blackwell. Internal tests show up to 3.5 times faster training performance and 5 times faster inference speeds.Peak performance reaches 50 petaflops.Efficiency also improves sharply. Rubin supports up to eight times more inference compute per watt, according to NVIDIA.These gains matter as AI infrastructure strains power grids and data center budgets worldwide.Huang has previously estimated that global AI infrastructure spending could reach $3 trillion to $4 trillion over five years. Rubin appears designed for that scale.Reinventing AI storageAlongside Rubin, NVIDIA unveiled a new AI-native storage approach powered by BlueField-4. The Inference Context Memory Storage Platform targets a growing problem in AI systems: managing massive key-value caches.As AI agents handle long conversations and multi-step reasoning, they generate context data that cannot remain on GPUs indefinitely.NVIDIA BlueField-4 AI-native storage infrastructure. Credit – NVIDIANVIDIA’s new platform extends memory capacity beyond the GPU while maintaining high-speed access.Senior director Dion Harris said new AI workflows place intense pressure on memory systems. NVIDIA responded by adding an external storage tier optimized for scaling context efficiently.The platform uses Spectrum-X Ethernet and NVIDIA’s DOCA framework to share context across rack-scale systems. NVIDIA claims up to five times higher token throughput and power efficiency compared with traditional storage.BlueField-4-based systems will reach partners in the second half of 2026, as NVIDIA pushes deeper into the full AI infrastructure stack.We’re at the CES 2026!You can explore all CES 2026 stories and coverage from the IE team by clicking here.

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