Marvell: Will The AI Underdog Finally Rally In 2026?

For the past three years of the big AI boom, Marvell Technology (NASDAQ:MRVL) has largely underperformed the broader semiconductor, despite supplying critical components that make large-scale AI systems work. While the market focused on GPUs and compute leaders, Marvell remained concentrated on networking silicon and custom logic, areas that received far less attention from investors. However, as we move through 2026, the narrative could change to Marvell’s favor. AI infrastructure is entering a phase where inference, power efficiency, and high-speed interconnects matter more than simply adding more GPUs, and those shifts align directly with Marvell’s core strengths.

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The Inference Pivot

The first wave of AI was about “brute force” training. In 2026, the industry is likely to pivot toward Agentic AI and Inference. Inference – essentially deploying and using the models to run billions of queries from users – requires lower latency and, crucially, much higher power efficiency than training. Marvell’s custom XPUs (AI accelerators) are purpose-built for these specific workloads. Unlike general-purpose GPUs, Marvell’s ASICs are designed to maximize “tokens per watt.” As hyperscalers look to scale their services to billions of users, the cost-per-inference becomes the primary metric. Marvell’s focus on the 3nm and 2nm nodes for these custom chips could give it an edge in the efficiency war, with custom AI revenue projected to hit $1.8 billion this year.

Connectivity 

Perhaps the most significant infrastructure shift of 2026 is the physical limit of copper. As AI data center clusters scale toward millions of processors, electrical interconnects face constraints from heat, power consumption, and signal degradation. At those scales, electrons simply do not move efficiently enough. Marvell is betting on light instead. The company has doubled down on Co-Packaged Optics (CPO) and its $3.25 billion acquisition of Celestial AI to push optical interconnects directly onto the silicon package. By integrating photonic fabric alongside compute and memory, Marvell is targeting one of the most persistent bottlenecks in large-scale AI systems: moving data at scale without unsustainable power and thermal costs. If optical interconnects become a requirement rather than an upgrade, Marvell’s early positioning in CPO could place it at the center of next-generation AI cluster design, with a higher-value role in the data center stack.

Breaking the “Single-Customer” Stigma

Historically, Marvell Technology has been penalized for its heavy reliance on Amazon Web Services. That concentration increased earnings volatility and constrained how the market valued Marvell’s AI exposure. Diversification is therefore critical in 2026, and it is now underway. Marvell has secured custom silicon design wins with three of the four major U.S. hyperscalers, with new programs ramping through 2026.  At the architectural level, Marvell has also ensured compatibility with dominant AI ecosystems rather than positioning itself in opposition. For example, support for Nvidia’s NVLink fabric allows Marvell’s custom silicon to coexist within Nvidia-centric environments, removing a key adoption barrier for hyperscalers. Executing deals with multiple hyperscalers reduces risk, stabilizes earnings, and makes the AI story more credible to Wall Street.

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