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South Korean chipmaker SK Hynix and US-based Micron Technology have both reached $1 trillion market valuations amid surging demand for AI memory chips.
South Korea’s SK Hynix has officially entered the exclusive $1 trillion market capitalization club, driven by intense global demand for semiconductors used in artificial intelligence [1]. This milestone follows a similar achievement by US-based Micron Technology, which surpassed the $1 trillion valuation threshold on May 26, 2026 [4].
Key takeaways
The rapid ascent of these chipmakers reflects a broader market trend where investors are capitalizing on the explosive growth of AI infrastructure [1]. SK Hynix, the world’s second-largest memory chipmaker, reported that its operating profit surged fivefold year-on-year in the first quarter of 2026, reaching 37.6 trillion won, or approximately $24.9 billion [1]. This financial performance mirrors the company's stock market success, which has seen its value rise alongside a general rally in South Korea’s KOSPI index [1].
In the United States, Micron Technology has similarly benefited from its position as a top supplier of high-bandwidth memory (HBM) for data centers [4]. Micron’s HBM3E solution is currently in high demand, as it is designed to prevent data bottlenecks in AI hardware stacks by offering higher memory capacity and lower energy consumption [4]. While Micron’s stock has experienced significant volatility, its recent valuation milestone makes it the third American semiconductor company to join the trillion-dollar club, following Nvidia and Broadcom [4].
The rise of these companies highlights the critical role of memory chips in the current AI hardware ecosystem. Because HBM is essential for the efficiency of graphics processing units (GPUs), the current supply-demand imbalance has granted manufacturers significant pricing power [4]. However, the sustainability of these valuations remains a subject of industry analysis. While some projections suggest the favorable environment for memory chips could persist through 2030, others note that supply and demand imbalances will eventually normalize [2, 4]. As these companies maintain their positions in the trillion-dollar club, their future performance will likely depend on their ability to scale manufacturing capacity to meet the ongoing requirements of AI data center operators [2, 4].
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