TL;DR
Nvidia has invested at least $6.5 billion in photonics companies since March 2026, including $2 billion each in Coherent, Lumentum, and Marvell, up to $3.2 billion in Corning, and participation in Ayar Labs’ $500 million Series E. The spending aims to replace copper with light-based interconnects as AI training clusters outgrow electrical bandwidth limits.
Nvidia has committed at least $6.5 billion to photonics companies since the beginning of March, making it the largest single investor in the technology that many in the industry believe will replace copper wiring as the backbone of AI data centres. The spending spree reflects a calculation that copper, the standard medium for moving data between chips, is approaching its physical limits just as AI training clusters are demanding exponentially more bandwidth.
Photonics uses light rather than electrical signals to transmit data. It offers substantially higher bandwidth at lower power consumption, two constraints that become critical when thousands of GPUs need to operate as a unified system. The problem is that the photonics supply chain is not yet built to the scale AI infrastructure requires. Nvidia’s broader investment strategy in 2026, which now exceeds $40 billion across AI equity bets, is designed to fix that.
Where the $6.5 billion went #
The bulk of the spending went to three established optical component makers. Nvidia invested $2 billion each in Coherent and Lumentum in early March, with both deals including multi-billion-dollar purchase commitments and funding for new US fabrication capacity. A further $2 billion went to Marvell, which acquired photonics startup Celestial AI in December 2025 and is developing silicon photonics for AI networking.
Nvidia then invested up to $3.2 billion in Corning, the glass and fibre optic manufacturer, through a combination of $500 million in equity warrants and multi-year purchase agreements. Corning will use the funding to increase its US-based optical connectivity manufacturing capacity by 10 times, expand fibre production by more than 50%, and build three new advanced manufacturing plants in North Carolina and Texas, creating more than 3,000 jobs.
Nvidia also participated in Ayar Labs’ $500 million Series E alongside AMD and MediaTek, valuing the co-packaged optics startup at $3.75 billion. Ayar Labs develops silicon photonics chiplets that can be integrated directly with processors, a technology called co-packaged optics that represents the next step beyond the discrete optical modules the larger deals target.
Why copper cannot keep up #
The core problem is physics. Copper interconnects lose signal integrity and consume more power as data rates increase. Inside a single rack of GPUs, copper can still handle the bandwidth at acceptable power levels. But when AI training clusters span multiple racks, which they increasingly must, the distance between chips exceeds what copper can serve efficiently.
Nvidia’s next-generation Vera Rubin platform illustrates the split. The Vera Rubin Ultra NVL576, a 576-GPU supercomputer spanning eight racks, uses copper within each rack and optical interconnects between racks. Jensen Huang has called the platform the largest product launch in Taiwan’s history, with each system containing nearly 2 million parts built through 150 ecosystem partners on the island.
The transition from copper to optics is not a future event. Nvidia launched its Quantum-X and Spectrum-X Photonics platforms in March 2025, the first commercial-grade co-packaged optics networking switches, built with TSMC, Coherent, Lumentum, Corning, and Foxconn. The $6.5 billion in investments is designed to ensure the supply chain can produce these components at the volumes Vera Rubin will require.
A supply chain Nvidia is trying to lock up #
The scale of Nvidia’s photonics spending has raised concerns among competitors. TechTimes reported that Nvidia’s purchase commitments to Coherent and Lumentum could effectively lock up the global supply of high-end laser components through 2027, pushing rival chipmakers and data centre operators to the back of the queue. AMD and MediaTek have responded by co-investing in Ayar Labs, but neither has matched the scale of Nvidia’s photonics commitment. The investments also carry geopolitical weight. Huang has said that Chinese competitors running frontier AI on Huawei chips would be a damaging outcome for the US, and securing domestic photonics manufacturing is part of the same strategic logic.
Other companies in the space include Lightmatter, valued at $4.4 billion, which is developing a 3D-stacked silicon photonics engine called Passage. Its L20 module, announced in March, achieves 6.4 terabits per second in each direction and is expected to begin sampling in late 2026. Broadcom, Intel, and Cisco are also developing optical interconnect products, but none has made the kind of ecosystem-level investment Nvidia has.
The financial context #
Nvidia reported first-quarter revenue of $44.1 billion and guided to $91 billion for the second quarter, authorising another $80 billion in share buybacks. The company’s market capitalisation stands at roughly $4 trillion. The $6.5 billion it has spent on photonics in three months is a rounding error on its balance sheet, but it represents a substantial fraction of the entire photonics industry’s annual revenue.
The pattern across Nvidia’s investments is consistent. Capital flows to companies that either build the components Nvidia needs or buy Nvidia GPUs at scale. The photonics deals follow the same logic, securing supply of a technology that will determine whether Nvidia’s next generation of AI platforms can ship on time and at scale. If copper is the bottleneck, and the physics says it is, then the company that controls the photonics supply chain controls the pace of AI infrastructure deployment. That is the bet Nvidia is making with $6.5 billion of its cash.