The artificial intelligence revolution has propelled chip giant Nvidia (NVDA) to the pinnacle of global market capitalization, with its market value currently approaching $5 trillion. Although the stock price is hovering around $205 (adjusted for the stock split) after a historic rally, Wall Street’s optimistic outlook on its prospects has not cooled. Some analysts have set a 12-month target price as high as $743, which would imply its market value leaping to an unprecedented level of over $15 trillion. This ambitious forecast is mainly built on bets placed on its next-generation technologies.
Nvidia’s growth narrative is ushering in a new core chapter. Its new-generation AI chip platform, Vera Rubin, has entered full production and is expected to begin official shipments in the coming months. The platform consists of six chips working in synergy, constructing a supercomputer designed specifically for agentic AI and inference tasks, while significantly expanding Nvidia’s chip coverage within server racks. At a critical juncture when the AI industry is transitioning from model training to inference applications, this is regarded as a key growth catalyst.
However, a stock price jump to $700 within a year would largely depend on valuation expansion. Based on the price-to-sales ratio calculated over the past 12 months of sales, Nvidia currently stands at about 20 times. Even taking into account high growth expectations, pushing the stock price to $700 would require a significant increase in this ratio. Although the stock has enjoyed higher valuation multiples historically, maintaining such a high multiple becomes increasingly difficult as the company’s size grows. Therefore, while achieving this target price might be possible, it remains quite challenging to realize within the next 12 months. Analysts believe that investors should shift their focus from short-term target prices to the company’s overall development trajectory. As Vera Rubin gradually contributes revenue over the coming quarters, Nvidia is entering a new growth phase. This may explain why, among the 69 Wall Street analysts surveyed by CNN Business, as many as 94% have given the stock a “buy” rating.
Meanwhile, Goldman Sachs (GS) pointed out in a report that AI is giving rise to a capital expenditure super cycle driven by private sector investment. The rapid development of technologies such as large language models has prompted companies to significantly increase their investment in infrastructure and computing power. This marks an acceleration in capital demand after several decades, with companies not only investing in technological upgrades but also focusing on strengthening supply chains and operational resilience to cope with economic and geopolitical pressures. Governments are also increasing spending on defense and critical infrastructure, further driving up capital demand across multiple sectors.
Goldman Sachs’ analysis suggests that this environment will profoundly impact financial markets: higher borrowing costs may suppress stock valuations, making robust earnings growth a key factor driving stock price performance. At the same time, as corporate earnings divergence intensifies, active stock-picking strategies may offer greater opportunities for excess returns than simply positioning in broad market indices. In the wave of AI spending, chip manufacturers have emerged as the primary beneficiaries.
