GoKawiilJensen Huang, chief executive officer of Nvidia Corp., speaks next to a Vera Rubin Ultra Kyber Compute Tray and a Vera Rubin Ultra Kyber NVLink MidPlane during a keynote address at the Nvidia GTC conference in San Jose, California, US, on Monday, March 16, 2026.
NVIDIA's next marquee product — the Kyber rack-scale architecture designed to house its 2027 Rubin Ultra chips — has been delayed by more than 12 months to 2028, according to research firm SemiAnalysis, the latest in a string of reported setbacks raising questions about the AI giant's product roadmap.
Kyber is a server cabinet that packs 144 of Nvidia's most powerful chips into a single unit so they can work together as one giant computer, providing the horsepower AI companies need to train and run their most advanced models.
The design mounts graphics processing units in compute trays that sit vertically instead of horizontally to boost density and reduce latency, and had been slated to debut with Vera Rubin Ultra, Nvidia's next-generation rack-scale system, in 2027.
The setback stems from difficulties manufacturing a key circuit board at the heart of the system, SemiAnalysis said in a post on Monday.
"Kyber NVL144 rack architecture has been delayed to 2028 as the PCB midplane remains challenging from a manufacturability standpoint," the firm said, referring to a specialized, multi-layer printed circuit board that connects electronic modules within a system.
NVL576 — a larger system linking eight racks via optical connections — is also likely delayed or limited to small volumes, the research firm said.
Nvidia did not respond to CNBC's request for comment.
The reported delay adds to mounting strains across Nvidia's product lines, underscoring concerns that Nvidia's breakneck annual release cadence is colliding with manufacturing limits.
A backup plan — bolting two of Nvidia's current-generation racks together for similar power — has also been scrapped after cloud customers rejected the design as awkward and costly to operate. "It has since been cancelled due to heavy pushback from CSPs [cloud service providers] and hyperscalers over its odd design and heavy operational burden," SemiAnalysis said.
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