Nvidia’s AI-fueled rally keeps reshaping the tech leaderboard, with Micron and SanDisk also up more than 1,000% since the boom began

Nvidia’s stock surge since the early days of the AI boom has continued to define how investors think about the buildout of data centers and the supply chain that supports them. A market roundup published Aug. 6 highlights that Nvidia, along with memory and storage players Micron and SanDisk, have each risen by more than 1,000% since the AI rally began, underscoring how quickly expectations moved from research demonstrations to large-scale infrastructure spending.

The same roundup frames Nvidia’s gains as part of a broader theme: companies that sit close to the core compute and the tightly linked components needed to run AI workloads have been rewarded as deployment accelerated. In that view, Nvidia benefited from the demand for the chips that power training and inference, while Micron and SanDisk benefited as the industry scaled the memory and storage required to feed those systems.

While Nvidia is the headline name for the AI buildout, the report’s broader takeaway is that other segments of the technology stack have also been pulled higher. Micron, a producer of DRAM and other memory products used in computing systems, and SanDisk, a supplier of flash storage used in devices and data storage systems, are positioned in the roundup as parallel beneficiaries of the same AI-driven demand cycle.

The article also turns to the next layer of infrastructure, where networking hardware and connectivity can become a bottleneck as data center clusters grow. It suggests that networking stocks such as Astera and Arista could be the next major gainers, reflecting the idea that high-bandwidth data movement becomes increasingly important as AI models scale and as more servers are linked together in large training and inference environments.

From a sector perspective, the stock leadership pattern described in the roundup aligns with a common market narrative during AI scaling: early enthusiasm tends to concentrate around the most visible compute suppliers, then expands outward to the supporting components that enable throughput, latency control, and system stability. Networking and memory/storage both matter because AI workloads stress data movement and capacity planning, not just raw arithmetic speed.

That said, the post does not provide granular, stock-by-stock operating details or recent earnings disclosures that would explain how each company’s fundamentals evolved over time. It focuses on the magnitude of the price gains and on the investment theme that additional infrastructure categories may offer further upside. Without more company-specific reporting, it is not possible from the post alone to attribute the entire performance move to particular product cycles, contract wins, or guidance changes.

Investors and analysts watching the next phase would likely look for confirmation that the theme holds up in business results, not just stock performance. For Nvidia, that typically means continued strength in data center demand and the product roadmap for AI compute. For Micron and SanDisk, attention would turn to whether memory and flash supply and pricing align with the pace of AI system deployments. For the networking names mentioned, the key question is whether their hardware and platform adoption tracks the expansion of large-scale AI clusters.