NVIDIA stock fell nearly 5% below $200 as concerns over OpenAI’s $250 billion loan guarantee overshadowed new partnerships and continued demand for Vera Rubin AI systems.
NVIDIA stock widens decline due to OpenAI exposure and Chinese competitive pressure on AI stocks
NVIDIA stock came under heavy selling pressure on Monday as investors questioned whether the company’s increasingly large investments across the artificial intelligence ecosystem were supporting real demand or creating circular funding risks.
NVDA fell $10.33, or 4.99%, to $196.51, before dropping another 0.70% to approximately $195.11 in overnight trading. The decline took Nvidia below the psychological $200 level, weighing on the entire semiconductor sector.
AMD fell more than 5%, and memory and semiconductor equipment stocks also fell as concerns about AI infrastructure spending spread across the industry.
The immediate trigger was a report that Nvidia may provide approximately $250 billion in financial guarantees to support OpenAI’s planned data center project in Ohio.
This offer would strengthen one of Nvidia’s most important customer relationships. But its sheer size has raised questions about whether the chipmaker is taking on too much financial exposure so that AI companies can continue to buy its processors.
Nvidia’s $250 billion OpenAI plan raises new questions
Nvidia is reportedly in talks to secure funding related to a 10 gigawatt data center project being developed for OpenAI in Piketon, Ohio.
The facility is being built by SoftBank subsidiary SB Energy and could cost more than $500 billion, including infrastructure and computing equipment. Nvidia’s proposed guarantee would reportedly cover approximately $250 billion related to OpenAI’s lease obligations.
Chips installed within the facility could be worth an additional $350 billion and create even larger commercial relationships.
For Nvidia, this opportunity is significant.
A 10 gigawatt project will require millions of advanced processors, networking products, and related systems. The first phase is expected to use Nvidia’s next-generation Vera Rubin platform, potentially creating multi-year demand.
But the potential structure of the deal has investors worried.
OpenAI remains unprofitable and relies on large amounts of external capital to fund its infrastructure ambitions. Once Nvidia guarantees that OpenAI will have the funds to purchase Nvidia systems, the distinction between independent customer demand and supplier-supported demand becomes clearer.
Cyclic Funding Concerns Pressure from Nvidia
Critics liken the growing AI investment network to the circular lending arrangements seen during the dot-com boom.
Nvidia invests in artificial intelligence developers and infrastructure companies. These companies can use that capital to lease computing power or buy systems containing Nvidia chips, and then return the money to Nvidia as revenue.
Proponents argue that this is a normal feature of emerging technology ecosystems. Strategic investments enable customers to scale faster, create new markets, and increase demand for their underlying infrastructure.
But the magnitude of Nvidia’s commitment makes this issue even harder to ignore.
Nvidia said it could invest up to $100 billion in OpenAI to deploy at least 10 gigawatts of Nvidia systems in 2025. Nvidia has reportedly committed another $30 billion in early 2026, and the proposed $250 billion guarantee would significantly strengthen the relationship.
The concern is not that OpenAI lacks demand for computing power. The concern is whether its earnings and cash flow can ultimately support long-term infrastructure obligations.
If AI developers are unable to quickly monetize their products, suppliers and financial backers could end up taking on more risk than investors previously anticipated.
Secure Superintelligence Contract Expands Nvidia’s Investment Strategy
Nvidia also announced a long-term partnership and investment in Safe Superintelligence, an AI research institute founded by former OpenAI co-founder Ilya Sutskever.
Under the agreement, Safe Superintelligence will receive access to Nvidia’s Vera Rubin platform, increasing the computing power available to the laboratory by approximately 10 times.
The companies will also collaborate on current and future Nvidia systems, with Safe Superintelligence providing research insights that can impact the development of new computing platforms.
This relationship strengthens Nvidia’s ties to one of the industry’s hottest research labs.
Safe Superintelligence raised $2 billion in 2025 at a reported valuation of $32 billion, although it continues to focus primarily on research rather than commercial products.
It creates both opportunities and risks.
If the lab produces significant breakthroughs, Nvidia could benefit as an investor, technology partner, and infrastructure supplier. But the new investments in AI developers, which haven’t yet generated revenue, are fueling concerns that Nvidia is spending money to cultivate customers whose ability to independently finance computing remains uncertain.
Naver Investment Expands Sovereign AI Opportunities
Nvidia’s planned $1 billion investment in South Korean internet company Naver provides another example of the company’s ecosystem strategy.
The proposed transaction would give NVIDIA an approximately 4.5% stake in Naver, making it the company’s third largest shareholder.
Naver, Nvidia, and Brookfield plan to expand their sovereign AI infrastructure serving customers in South Korea and the United States. The first Nvidia DSX AI factory is expected to grow from 55 megawatts to approximately 200 megawatts by 2028.
Sovereign AI is a significant growth market as governments and businesses seek to operate artificial intelligence systems under their own data, security, and regulatory requirements.
Unlike early-stage laboratories, Naver has established internet, cloud, and data center operations. The partnership could then become more commercially diversified.
Nevertheless, the pattern is similar. While Nvidia provides the computing platform, it also provides the capital to use its products to accelerate infrastructure.
China competition puts pressure on AI trade
Growing concerns about China’s advances in artificial intelligence and semiconductor manufacturing also spurred the selloff.
Low-cost Chinese open source models such as the Kimi K3 are raising questions about whether future AI workloads will require as much high-end computing power as the market currently expects.
Improving model efficiency does not necessarily reduce total chip demand. Lower inference costs facilitate broader adoption and enable additional uses.
However, the possibility of developing and operating capable models with fewer resources calls into question the assumption that computing requirements will grow indefinitely at the current pace.
Reports on advances in China’s lithography equipment added a new source of uncertainty. Domestic production of advanced semiconductor tools could ultimately reduce China’s dependence on Western suppliers and strengthen its broader chip ecosystem.
It may take years for increased competition from China to impact Nvidia’s leadership, but the market is no longer willing to ignore the risks.
Political resistance threatens data center expansion
Nvidia’s growth also depends on the industry’s ability to build huge data centers.
These projects require significant amounts of power, water, land, and grid infrastructure. Local resistance is growing as communities question whether the economic benefits are worth the increased energy demands and environmental costs.
New York state has instituted a moratorium on the construction of some large data centers, and politicians in several other states have proposed limiting or changing tax incentives.
The 10 gigawatt scale planned for the Ohio project illustrates the challenge. A facility of this size requires an energy infrastructure comparable to that used in an entire city.
Political resistance is unlikely to completely halt global AI investment. However, construction delays, tightening regulations, and rising power costs could slow the speed at which customers adopt Nvidia systems.
NVDA technology outlook falls below $200
From a technical perspective, Nvidia’s 4-hour chart deteriorated sharply.
NVDA is trading below all listed simple and exponential moving averages at $196.51. The 200-period simple moving average at $199.90 and the 200-period EMA at $201.22 form the first major resistance zone.
The Hull moving average is at $198.74, reinforcing the psychological $200 level.
If the rally continues above $201, buyers could challenge the 50-period simple moving average at $202.71. Stronger resistance is centered between approximately $204 and $209, where the short-term average, Ichimoku reference line, and 100-period simple moving average are located.
Until Nvidia recovers this cluster, the rebound may continue to attract sellers.
Momentum indicators indicate that the decline is widening. RSI is 38.50 and Stochastic %K is close to oversold territory at 20.38.
Williams’ %R has fallen to -94.30, indicating a buy signal, but the Stochastic RSI is only 9.44. The Commodity Channel Index has fallen to -224.33, again indicating extreme short-term weakness.
However, the MACD remains a sell signal and the bull-bear power is significantly negative. These numbers suggest that a bailout rebound could occur without confirmation that the correction is over.
The $195 region represents immediate support. A decisive break below this could expose $190, followed by a deeper test near $180. On the positive side, Nvidia first needs to recoup $200-201 and then $205 before the 4-hour structure starts to improve.
Nvidia’s AI ecosystem strategy faces serious challenges
Nvidia continues to be a leading provider of computing systems driving the artificial intelligence boom.
As the company’s Vera Rubin platform goes into production and major AI labs continue to seek access to its systems, the Sovereign AI project offers another potentially huge market.
However, its risk profile is changing due to the company’s expanding role as a supplier, investor and financial supporter.
OpenAI’s potential $250 billion in guarantees gives it insight into future demand, but it also could give Nvidia more direct insight into its customers’ ability to monetize its AI services and meet long-term obligations.
For now, a drop below $200 indicates investors want more clarity.
Oversold indicators could support a short-term rebound, but NVDA needs to recover the $200-$205 region before buyers regain technical control. Until then, funding concerns, Chinese competition and political resistance to building data centers could continue to overshadow Nvidia’s strong long-term growth story.
Aishwarya Gopan
Financial Writer and Editor – Asia & Europe Desk
Aiswarya Gopan is a financial journalist, editor, and content strategist with over 19 years of experience in financial markets, fintech, blockchain, and technology. She has worked with major cryptocurrency exchanges such as BingX and KuCoin to drive content strategy, market research, and editorial initiatives covering digital assets, DeFi, Web3, and global financial markets. With a background in cybersecurity, technology journalism, and market research, Aiswarya specializes in translating complex financial and blockchain developments into clear and timely insights. FX Leaders covers cryptocurrencies, stocks, forex, and macroeconomic trends in the Asian and European trading sessions.
