Nvidia's Stock Plunges 3.28% as $41.84 Billion Trading Volume Surges, Capping Record Activity Amid Landmark AWS Supply Pact

Market Snapshot

Nvidia (NVDA) closed with a 3.28% decline on March 20, 2026, despite surging trading volume of $41.84 billion—a 37.35% increase from the previous day—ranking it as the most actively traded stock. The drop contrasts with the magnitude of its news-driven momentum, as the company announced a landmark multi-year supply agreement with Amazon Web Services (AWS) to deliver 1 million AI chips and infrastructure components by 2027.

Key Drivers

The AWS deal, disclosed at Nvidia’s GTC 2026 event, represents one of the largest single-client contracts in Nvidia’s history. Under the agreement, AWS will integrate a diverse portfolio of Nvidia products, including Blackwell and Rubin GPUs, Spectrum-X networking gear, and Groq inference processors acquired via a $17 billion licensing deal. Deliveries begin in 2025 and extend through 2027, aligning with CEO Jensen Huang’s projection of a $1 trillion addressable market for these chip families. The partnership underscores Nvidia’s growing role as a foundational infrastructure provider for cloud AI, with AWS leveraging seven distinct chip types to optimize AI inference—a technically complex process requiring multi-chip collaboration.

A critical factor in the stock’s performance is the broader context of AI infrastructure demand. The deal highlights the intensifying competition among cloud providers to secure advanced computing resources, with AWS collaborating on custom networking solutions despite its historical reliance on proprietary systems. This strategic shift signals the scale of AI workloads and the necessity for specialized hardware. Analysts have noted that inference workloads now account for roughly two-thirds of AI compute demand, up from a third in 2023, reinforcing the value of Nvidia’s diversified offerings.

The Groq licensing agreement, announced in late 2025, further amplifies Nvidia’s technical edge. By integrating Groq’s inference-focused chips into its platform, Nvidia aims to address the “wickedly hard” challenge of inference efficiency, as described by VP Ian Buck. This move complements its recent Vera CPU launch for agentic AI and reinforcement learning, showcasing a multi-pronged approach to expanding its AI ecosystem. However, the stock’s decline may reflect investor caution amid broader market concerns about uneven hyperscaler spending and regulatory scrutiny, particularly regarding export controls to China.

While the AWS deal and Groq integration present long-term growth catalysts, near-term volatility could persist as investors balance optimism about $1 trillion in potential sales against execution risks. The absence of disclosed financial terms for the AWS contract and the ongoing U.S. investigation into alleged chip smuggling to China add layers of uncertainty. Nonetheless, the agreement solidifies Nvidia’s position at the forefront of the AI infrastructure race, with its Blackwell and Rubin architectures poised to capture a significant share of the expanding cloud computing market.

Strategic Implications

The AWS partnership also highlights a broader trend: cloud providers are increasingly relying on third-party semiconductor expertise to meet surging AI demands. For Nvidia, this represents a shift from being a chip supplier to becoming a core infrastructure layer for cloud giants. The inclusion of networking components like ConnectX and Spectrum-X in the deal further diversifies Nvidia’s revenue streams, reducing dependency on standalone GPU sales. However, AWS’s parallel development of custom chips, such as Trainium2, suggests that cloud providers are adopting a hybrid strategy, balancing proprietary solutions with external partnerships to optimize performance and cost.

In summary, while the 3.28% drop in Nvidia’s stock on March 20 may reflect short-term market dynamics, the underlying fundamentals—driven by the AWS deal, Groq integration, and AI inference demand—are robust. The stock’s trajectory will likely depend on the execution of these partnerships, regulatory developments, and the pace of AI adoption across industries.