Marvell Technology Stock Drops 4.35% in 4th Consecutive Day of Decline, Trading Volume Ranks 52nd

On March 28, 2025, Marvell Technology, Inc. (MRVL) experienced a significant decline, with its stock price dropping by 4.35%. This marked the fourth consecutive day of decline, resulting in a total decrease of 14.73% over the past four days. The company's trading volume for the day was substantial, reaching 11.61 billion, placing it at the 52nd position in terms of trading volume for the day.

Marvell Technology, Inc. recently announced a conference call to review its fourth fiscal quarter and fiscal year 2025 financial results. This call is scheduled to provide investors and analysts with a comprehensive overview of the company's performance and future outlook.

In a significant technological advancement, Marvell Technology, Inc. and TeraHop demonstrated the industry's first end-to-end PCIe Gen 6 over optics solution at OFC 2025. This breakthrough showcases the transmission of PCIe signals between a root complex and endpoint across 10 meters of TeraHop OSFP-XD active optical cable using Marvell's Alaska P PCIe Gen 6 retimer. This collaboration enables low-latency, standards-based AI scale-up infrastructure by extending PCIe reach beyond traditional electrical limits. The solution incorporates PCIe Gen 7 SerDes technology running at 128 GT/s through TeraHop's linear-drive pluggable optical module, ensuring reliable high-speed connectivity between AI accelerators, CPUs, CXL-pooled memory, SSDs, and NICs. This advancement is crucial for next-generation accelerated infrastructure, addressing the exponential data growth driven by AI workloads that demand higher bandwidth and longer reach capabilities.

Marvell's demonstration of the industry's first end-to-end PCIe Gen 6 over optics represents a significant technical achievement in data center connectivity. By extending PCIe signals across 10 meters via optical cable, Marvell addresses a fundamental limitation in traditional electrical PCIe connections that typically max out at much shorter distances. The technical implications are substantial. As AI compute clusters scale up, the ability to maintain PCIe's native low latency while extending physical reach creates new architectural possibilities for distributed processing. The Alaska P PCIe Gen 6 retimer technology effectively converts electrical signals to optical data without sacrificing performance characteristics, enabling flexible placement of processing elements across larger physical spaces. More forward-looking is the demonstration of PCIe Gen 7 SerDes running at 128 GT/s through TeraHop's optical modules. With PCIe Gen 7 specifications expected to finalize this year, Marvell is positioning itself at the bleeding edge of this technology curve. While impressive technically, this remains a technology demonstration rather than a product announcement. The real challenge will be transitioning from proof-of-concept to commercial deployment in hyperscale environments. The market impact depends on how quickly Marvell can productize this technology and whether major cloud providers and AI infrastructure developers adopt it for their next-generation architectures. This PCIe-over-optics demonstration addresses a critical bottleneck in current AI compute infrastructure. The 10-meter optical connection may seem modest, but it represents a paradigm shift in how AI compute elements can be physically arranged in data centers. Traditional PCIe electrical connections impose strict distance limitations, forcing tightly packed server configurations that create thermal and power distribution challenges. By enabling PCIe Gen 6 (which operates at 64 GT/s) to function reliably over optical fiber, Marvell opens possibilities for more distributed AI compute architectures while maintaining the performance benefits of direct PCIe connectivity. The collaboration with TeraHop leveraging OSFP-XD active optical cables and retimed riser cards shows a complete ecosystem approach rather than just component development. This suggests the technology could move toward commercial readiness faster than typical early-stage demonstrations. For hyperscalers building massive AI training clusters, this technology could allow more optimal physical distribution of GPUs, CPUs, memory pools (via CXL), storage, and networking components. This flexibility potentially addresses power delivery, cooling, and rack density constraints that currently limit AI infrastructure scaling. While technically innovative, the market impact will ultimately depend on cost structure, reliability at scale, and whether the distance extension creates enough architectural advantages to justify adoption over traditional configurations. The demonstration is significant, but real-world deployment remains the true test.