Nvidia Invests $6 Billion in Marvell, Coherent and Lumentum to Lock In AI Infrastructure
Updated
Updated · The Motley Fool · Jun 5
Nvidia Invests $6 Billion in Marvell, Coherent and Lumentum to Lock In AI Infrastructure
3 articles · Updated · The Motley Fool · Jun 5
Summary
$6 billion in disclosed March commitments gives Nvidia roughly $2 billion stakes each in Marvell, Coherent and Lumentum, extending its AI push beyond GPUs into networking, photonics and custom processors.
The investments aim to secure critical supply as AI data centers scale and optical bottlenecks worsen: McKinsey estimates demand for 800-Gbps transceivers will exceed production by 40% to 60% through 2027.
Coherent and Lumentum are using the capital to expand U.S. manufacturing and fabrication capacity, helping Nvidia lock in access to optical components needed for low-latency, high-bandwidth AI clusters.
Marvell adds another layer by supplying custom AI processors and networking gear for rack-scale systems; it raised fiscal 2027 revenue guidance to $11.5 billion, up 40%, with faster growth projected next year.
The broader bet is that tighter control of the AI hardware ecosystem will protect Nvidia's growth and reinforce its position in semiconductors even as competition in AI chips intensifies.
As tech giants build their own AI chips, are Nvidia's billions a power move or a desperate defense?
Nvidia bets billions on light-speed tech. Can it scale in time to prevent an AI bottleneck?
How Nvidia’s $4B Photonics Investment Is Reshaping AI Supply Chains and Data Center Efficiency
Overview
Nvidia is driving a major transformation in AI infrastructure by investing heavily in photonics technology between March and June 2026. This move addresses the urgent need for faster and more efficient data transfer in hyperscale data centers, which are struggling with the heat and high energy costs of traditional copper-based systems. By integrating photonics—which uses light instead of electricity to move data—Nvidia is reducing energy consumption and operational expenses while boosting data speeds. These strategic investments mark a pivotal shift, laying the foundation for more powerful and sustainable AI operations in the future.