Nvidia Expands US AI Chip Packaging With $1.5B Deal

Nvidia Signs $1.5B Deal to Expand US AI Chip Packaging

Nvidia Signs $1.5B Deal to Expand US AI Chip Packaging

Amkor and NVIDIA logos displayed side-by-side next to a close-up of a high-performance semiconductor microchip on a circuit board, representing chip packaging partnership.

Nvidia’s $1.5 billion Amkor deal will expand US AI chip packaging capacity and could help ease a growing semiconductor supply bottleneck.

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Kezia Jungco
Kezia Jungco
Jul 24, 2026

Nvidia and Amkor are partnering to expand advanced chip packaging and testing capacity for next-generation AI infrastructure. Image generated via ChatGPT

Nvidia is putting $1.5 billion behind one of the less visible but increasingly important stages of AI chip production. The company has signed a multiyear agreement with Amkor Technology to expand advanced semiconductor packaging and testing capacity in the United States.

The partnership will support Amkor’s Arizona expansion and fund new packaging and testing technologies for Nvidia’s future AI and accelerated computing platforms.

For businesses investing in AI infrastructure, the deal could help address a growing packaging bottleneck, add more US capacity to Nvidia’s supply chain, and improve the company’s ability to bring increasingly complex processors, memory, and networking components into finished systems at scale.

Nvidia’s prepayment helps Amkor expand US capacity

Amkor said Nvidia would provide a prepayment under the agreement, allowing the packaging company to expand its US capacity while the two businesses align their technology roadmaps. The companies will focus on high-density interconnects and heterogeneous integration, which combines different types of chips and components within one package.

Amkor already provides packaging services for Nvidia products, including data center processors, networking chipsets, and accelerated computing systems. The expanded partnership is intended to bring future packaging and test technologies into large-scale production as demand for AI infrastructure grows.

Reuters reported that Amkor shares rose 17% in extended trading following the announcement. The publication also noted that Amkor signed a 10-year US packaging partnership with Taiwan Semiconductor Manufacturing Company in June and provides packaging services for AMD.

Why chip packaging is becoming an AI bottleneck

Packaging is the stage where individual chips are assembled, connected, protected, and prepared for use in a larger computing system. For modern AI accelerators, the process must support high-speed communication among processors, memory, and networking components while helping systems manage power consumption and heat.

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The Business Times described advanced packaging as a growing supply bottleneck as chipmakers try to satisfy demand for AI accelerators. Nvidia’s investment could help secure additional capacity for its platforms while giving Amkor funding to build facilities before customer demand fully materializes.

Advanced packaging has also become more important as chipmakers combine specialized processors, memory, and other components instead of relying on a single piece of silicon. Any shortage in packaging and testing capacity can delay finished systems even when the individual chips are available.

What the Amkor expansion could mean for AI hardware supply

Enterprise buyers should not expect the agreement to produce an immediate increase in available AI servers. Building packaging capacity and developing new manufacturing processes can take time, and the companies did not provide a detailed production schedule.

The agreement also does not guarantee that every planned facility or production line will arrive on schedule. Amkor warned that its Arizona campus could face changes involving timing, costs, specifications, or expected commercial benefits.

The longer-term effect could be a more geographically diverse supply chain. Amkor said its Arizona expansion would complement its existing manufacturing presence across Asia rather than replace it, giving Nvidia access to additional US capacity while retaining established production networks overseas.

For infrastructure teams, the main development to monitor is whether the investment reduces supply constraints for future Nvidia systems. More packaging capacity could eventually improve availability, but pricing and delivery schedules will still depend on chip manufacturing, memory, networking, server assembly, and data center demand.

Read more about Nvidia and Microsoft’s RTX Spark Windows PCs for running AI agents locally, with systems from major PC makers expected this fall.

Kezia Jungco

Kezia Jungco is a technology writer and researcher specializing in artificial intelligence, data analytics, CRM software, cloud infrastructure, cybersecurity, and emerging business technologies. With more than five years of experience evaluating software platforms and technology solutions, she helps business leaders understand the tools and trends shaping the future of work. Kezia has extensive hands-on experience testing and analyzing generative AI platforms, chatbots, natural language processing (NLP) tools, CRM systems, and business software. Her work focuses on translating complex technologies into practical insights that help organizations make informed decisions about technology adoption, operational efficiency, and digital transformation. As a staff writer for TechnologyAdvice, Kezia covers AI innovation, business applications of machine learning, data-driven technologies, cloud computing, cybersecurity, and sales technology. Her background in journalism, research, and education enables her to combine rigorous analysis with clear, accessible reporting for both enterprise and consumer audiences. Kezia holds a bachelor's degree in Development Communication with a major in Development Journalism from the University of the Philippines Los Baños. She has also completed professional training in artificial intelligence, data privacy, and information security. Her work has been featured in TechnologyAdvice, TechRepublic, eWeek, Datamation, and Selling Signals, where she helps readers navigate a rapidly evolving technology landscape with practical, research-driven guidance.