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By Vedprakash sahu Published:

Nvidia Strikes $900 Million Deal With Enfabrica, Secures Key Talent and GPU Interconnect Technology

Nvidia has made a bold move in the chip interconnect space, hiring top executives from Enfabrica and licensing its breakthrough technology in a deal valued at more than $900 million.

Enfabrica, a Silicon Valley startup founded in 2019, has developed technology capable of linking more than 100,000 GPUs together, a critical capability as demand for large-scale AI and data center performance accelerates. Nvidia had already backed the company during a $125 million funding round in 2023, and is now deepening its bet by securing its core innovations.

Enfabrica’s Strategic Role in GPU Scaling

The startup has quickly gained attention for solving one of the toughest challenges in AI infrastructure — connecting vast numbers of GPUs efficiently. This technology could significantly enhance Nvidia’s dominance in AI chips, data center networking, and GPU interconnect solutions.

At the center of the deal is Rochan, Enfabrica’s founder, president, and CEO. Known for his strategic vision and product leadership, Rochan previously headed Broadcom’s data center Ethernet switching division, where he oversaw the launch of multiple generations of Tomahawk and Trident chips. His move to Nvidia marks a major talent win for the semiconductor giant.

Nvidia Strengthens Its AI Leadership

  • Strengthens Nvidia’s leadership in GPU interconnect and data center technologies.
  • Integrates Enfabrica’s innovations into Nvidia’s expanding AI infrastructure ecosystem.
  • Brings on board key engineers and executives with proven expertise in high-performance networking.

Industry analysts see this as a strategic acquisition that not only boosts Nvidia’s technical edge but also secures a team with deep domain knowledge in chip-to-chip communication — an area critical to scaling next-generation AI models.

With Enfabrica’s technology and talent now in-house, Nvidia is positioning itself for the next wave of data center growth, AI workloads, and cloud-scale GPU deployments.



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