Written by: Rita

Goldman Sachs Group maintained NVIDIA's buy rating in a report released on September 10, 2026, with a 12-month target price of $300. Based on the closing price of $223.67 on September 9, there is an upside potential of 34.1%. The target price is based on a price-to-earnings ratio of 30 multiplied by a normalized earnings per share of $10. NVIDIA reiterated at the Communacopia + Technology 2026 conference that by 2030, the potential market size for AI is estimated at $3 trillion to $4 trillion.

Jensen Huang indicated that demand visibility comes from the shift in computational paradigms. The transition from retrieval-based computing to generative computing requires a completely new layer of computing infrastructure. Goldman Sachs analyst James Schneider quoted management's views in the report, pointing out that the slowdown of Moore's Law has actually amplified the value of NVIDIA's tightly coupled hardware and network stack, with NVLink interconnection architecture and scale-up, scale-out architecture being key options for customers pursuing higher performance and efficiency.

AI Market Expected at $3 Trillion to $4 Trillion by 2030

NVIDIA reiterated at the conference that AI represents a potential market opportunity of $3 trillion to $4 trillion by 2030. The driving force behind this judgment is the shift from retrieval-based computing to generative computing, which necessitates a new layer of computing infrastructure. Goldman Sachs quoted management's views in the report, stating that the slowdown of Moore's Law has increased the value of NVIDIA's tightly coupled hardware and network stack, including NVLink interconnection architecture and scale-up, scale-out architecture.

During the conference, Jensen Huang stated that NVIDIA is capturing a larger share of the overall AI capital expenditures by providing more value to customers. Goldman Sachs views this statement as an indication of NVIDIA's positioning extending from a chip supplier to a system-level platform provider, where the co-design of networking and software constitutes a competitive barrier.

Supply Constraints Cover the Entire Industry Chain

Jensen Huang acknowledged that upstream supply constraints are widespread, involving advanced packaging, wafers, and memory. The infrastructure layer for data centers is similarly constrained in terms of power and site selection. Goldman Sachs pointed out in the report that the scale of NVIDIA's ecosystem and customer visibility are key advantages in addressing downstream bottlenecks.

Despite continued supply tightness, management reiterated expectations of approximately 70% year-over-year growth for CY27. Goldman Sachs interprets this as a signal of demand visibility, stating that supply constraints are part of a capacity ramp-up issue, and demand has not weakened. The report also mentioned that NVIDIA supports the AI ecosystem's acquisition of data center capacity through financial guarantees and commitments, while management believes this does not align with the qualitative aspects of revolving financing, as the ultimate returns and diversity of investment partners do not support this judgment.

Physical AI is the Next Inflection Point

Jensen Huang is optimistic about physical AI, with autonomous driving as a major use case, and warehouse automation and navigation systems as emerging applications. He anticipates that the next major inflection point will come from manipulation systems based on inference, expected in about two years. 6G-enabled systems are also viewed as another use case for physical AI.

Goldman Sachs pointed out in the report that the advancement of physical AI will expand NVIDIA's deployment scenarios beyond data centers. The requirements for real-time inference and edge computing in autonomous driving and robotic systems extend NVIDIA's architectural advantages accumulated on the training side.

Target Price of $300 Maintained as Buy

Goldman Sachs maintains a buy rating for NVIDIA, with a 12-month target price of $300, based on a price-to-earnings ratio of 30 multiplied by $10 normalized earnings per share. With the closing price of $223.67 on September 9, there is an upside potential of 34.1%.

The report lists downside risks including a slowdown in AI infrastructure spending, intensified competition leading to market share erosion, competition pressuring margins, and supply constraints. Jensen Huang also mentioned at the conference that programming is currently one of the most attractive applications of GenAI, and cybersecurity is a significant opportunity for AI. AI-driven programming and software development enhance productivity while supporting more advanced security capabilities; Goldman Sachs views these applications as factors sustaining NVIDIA's demand on the inference side.

Disclaimer

This article is a compilation and interpretation of the third-party brokerage report (Goldman Sachs Group, September 10, 2026) by Chaoxiang Research, combined with publicly available market information. The ratings, target prices, earnings forecasts, and related judgments quoted in this article are solely the views of the analysts of that brokerage and represent only the position of their respective institutions, not the views of Chaoxiang Research, and do not constitute any investment advice.

Markets involve risks, and decisions should be made independently. This article should not be considered the basis for buying or selling any securities.