NVIDIA CEO says AI spending flywheel is accelerating rapidly
- Jensen Huang states AI factory ROI is roughly one year with $50B-$60B build costs
- GPU rental prices for Grace Blackwell systems rose from $5 to $16 per hour
- Token generation rate increased 25-fold in less than a year
- Open models now account for nearly 70% of generated tokens, up from 30%
- Testing is expected to become a third major category of AI infrastructure demand

*this image is generated using AI for illustrative purposes only.
NVIDIA Corp. (NASDAQ: NVDA) CEO Jensen Huang stated that demand for artificial intelligence computing is accelerating as companies race to build new infrastructure. He described the current cycle as a flywheel that is "really, really flying."
Speaking with CNBC’s Jim Cramer at Dreamforce in San Francisco, Huang highlighted the rapid construction of NVIDIA-powered "AI factories" over the past six months.
AI Factory Economics
Huang estimated that a 1-gigawatt NVIDIA AI factory costs about $50 billion to $60 billion to build. He said this infrastructure can generate about $50 billion in annual rental revenue. This implies a return on invested capital of roughly one year under current market conditions.
He noted that NVIDIA infrastructure can remain useful for more than five or six years. Meanwhile, AI usage continues to climb. The rate of token generation has increased 25-fold in less than a year. Open models now account for nearly 70% of generated tokens, up from about 30%.
New Demand Drivers
Huang pushed back against concerns that AI safety efforts could derail industry growth. He said thousands of companies worldwide are working on AI safety, security and guardrails.
He expects testing to become a third major category of AI infrastructure alongside training and inference. Large testing environments will require additional data centers, creating another source of compute demand.
Rental Price Surge
Huang pointed to rising rental prices as evidence of tight demand. NVIDIA Grace Blackwell systems can now rent for about $16 per GPU hour, compared with roughly $5 under some contracts signed a year ago.
As older contracts expire, cloud providers are raising prices. This boosts revenue forecasts and returns on invested capital, prompting customers to buy more equipment and build more infrastructure.
What the Numbers Show
The tripling of GPU rental prices from $5 to $16 per hour directly supports Huang’s claim of an accelerating spending cycle. Higher rental costs improve the return on invested capital for existing infrastructure, which in turn incentivizes further capital expenditure on new data centers. This creates a self-reinforcing loop where higher utilization rates drive higher revenues, which justify additional infrastructure builds.
Stock Performance
NVIDIA stock rose in Wednesday premarket trading as technology stocks gained alongside U.S. equity futures. Nasdaq futures rose 0.39%, while S&P 500 futures gained 0.16%.
NVIDIA is trading 2.6% below its 20-day simple moving average of $218.81. The stock is roughly in line with its 50-day SMA of $213.24. It trades 7.7% above its 200-day SMA of $197.79. The 20-day SMA remains above the 50-day average, while the 50-day remains above the 200-day.
Momentum is neutral. NVIDIA’s relative strength index stands at 45.60. Resistance sits near $214, close to the 50-day SMA. Support is at $190. The stock’s 52-week range is $164.27 to $236.54.
Analyst Outlook
NVIDIA carries a Buy consensus rating with an average price forecast of $348.22. Piper Sandler initiated coverage with an Overweight rating and a $300 price forecast on Sept. 10. Rosenblatt maintained a Buy rating and $390 forecast on Sept. 4. Needham also maintained a Buy rating and $300 forecast that day.
ETF Exposure
NVIDIA accounts for 9.94% of the Xtrackers Net Zero Pathway Paris Aligned U.S. Equity ETF (NYSE: USNZ). It holds 9.79% of the First Trust Innovation Leaders ETF (NYSE: ILDR) and 9.73% of the Franklin Focused Dynamic Growth ETF (NASDAQ: FFOG).
Large inflows or outflows from these funds can translate into additional buying or selling of NVIDIA shares.
How might the rapid escalation of GPU rental prices from $5 to $16 per hour impact the long-term profitability margins of cloud service providers and enterprise AI adopters?
Could the shift toward open-source models accounting for 70% of token generation alter NVIDIA's competitive landscape by reducing dependency on proprietary, high-cost infrastructure?
What are the potential risks if the 'flywheel' effect reverses due to a slowdown in AI application adoption or stricter regulatory guardrails on AI safety?

































