NVIDIA's Price Target Raised to $180 Amid Robust AI Demand

NVIDIA's price target has been raised to $180 by DBS analyst Fang Boon Foo, who maintains a "buy" rating. The analyst forecasts robust demand for AI accelerators, with revenue reaching $45 billion in Q2 2026. Despite risks from U.S. export controls, NVIDIA's annual product update cycle and compliant chip variants are expected to support market growth. However, there may be short-term pressure on gross margins with the production of Blackwell chips.

NVIDIA (NASDAQ:NVDA) received a fresh boost on Friday as DBS analyst Fang Boon Foo raised his price target to $180 from $160, maintaining a "Buy" rating. The analyst pointed to sustained global demand for NVIDIA's AI accelerators, forecasting that revenue for Q2 FY 2026 will reach about $45 billion, up slightly from the prior quarter, as Hopper and Blackwell chip orders outpace supply [1].

Foo acknowledged that while U.S. export curbs on China present risks, a China-compliant variant under development may help mitigate potential headwinds, supporting continued growth in that market. The analyst also highlighted NVIDIA's annual product refresh cycle, transitioning from Hopper to Blackwell and then to Rubin, as a key advantage in the competitive AI chip landscape. He warned that gross margins might dip in the short term as Blackwell production ramps, but management expects margins to rebound to the mid-70% range in fiscal year 2026 [1].

Valuation concerns are tempered by NVIDIA's strong free cash flow and high return on equity, with Foo arguing that a 22-times forward price-to-book multiple is justified given the company's market position. Despite these positive indicators, investors should be aware of potential risks such as supply constraints and market volatility [1].

NVIDIA's recent financial results signal a paradigm shift in the semiconductor industry, positioning the company as a prime candidate to join the $1 trillion market cap club. The company's data center revenue surged to a record $26.3 billion in Q2 2025, up 154% year-over-year and accounting for 88% of total revenue. This explosive growth is driven by NVIDIA's GPU architecture, which is synonymous with AI performance. The Hopper-based H100 and H200 GPUs, now complemented by the next-gen Blackwell architecture, are the engines behind everything from generative AI models to enterprise-grade inference systems [2].

The AI Tsunami: Fueling NVIDIA's Revenue Surge
NVIDIA's dominance is rooted in its GPU architecture, which has become synonymous with AI performance. The Hopper-based H100 and H200 GPUs, now complemented by the next-gen Blackwell architecture, are the engines behind everything from generative AI models to enterprise-grade inference systems. In Q2, the H200 began ramping to cloud providers and enterprises, while anticipation for the Blackwell architecture—described by NVIDIA as “incredible”—is already driving pre-orders. The Blackwell B200 GPUs, capable of accelerating large language model inference by 30x, are expected to generate “several billion dollars” in revenue by Q4 2025 [2].

The data underscores NVIDIA's strategic brilliance: its AI software stack, including tools like NIM (NVIDIA Inference Microservices) and the AI Foundry, creates a flywheel effect. Over 150 companies are now integrating NIM into their platforms, slashing costs and latency while expanding use cases—from customer service bots to drug discovery. Meanwhile, the AI Foundry, which gives enterprises access to Meta's Llama 3.1 models, has already secured Accenture as its first major partner. These initiatives aren't just incremental; they're redefining how organizations build and deploy AI at scale [2].

Semiconductor Supremacy: Why NVIDIA's Lead Can't Be Matched
NVIDIA's competitive advantage lies in its ecosystem. While competitors like AMD and Intel have made strides, NVIDIA's GPUs remain unmatched in raw performance for AI workloads. The Blackwell architecture's ability to support trillion-parameter models in real-time sets a new benchmark, and its networking platforms like Spectrum-X Ethernet—now doubling in adoption quarterly—are enabling hyperscalers to build exascale AI clusters [2].

Geographically, NVIDIA's China revenue, though still below pre-export-control levels, is stabilizing, while demand from Japan (via projects like the ABCI 3.0 supercomputer) and other sovereign AI initiatives is filling the gap. The company's “low-double-digit billions” revenue forecast for sovereign AI projects alone highlights the global demand for its infrastructure [2].

Critically, NVIDIA's software-first strategy creates switching costs. Enterprises investing in its tools and architectures are unlikely to pivot to competitors without incurring massive retooling costs. This moat is deepening as AI becomes embedded in healthcare, automotive, and enterprise software—a trend NVIDIA's management calls “the next wave of AI adoption” [2].

Risks and the Path to $1 Trillion
No investment is without risks. Supply constraints for Blackwell GPUs could limit near-term growth, and China's market remains volatile. However, NVIDIA's outlook is bullish: it expects trailing-12-month data center revenue to grow further as Blackwell production scales and inference workloads—already 40% of data center revenue—expand [2].

To reach $1 trillion, NVIDIA needs to sustain its current revenue trajectory. Assuming $100 billion in annual data center revenue by 2026 (a conservative extrapolation given its 154% YoY growth), with margins expanding due to higher ASPs for advanced chips, NVIDIA's valuation could easily surpass $1 trillion. The addressable market for AI infrastructure—estimated at $200 billion by 2030—is still in its infancy, and NVIDIA's ecosystem lock-in ensures it captures a disproportionate share [2].

Investment Thesis: A Long-Term Play on AI's Future
For investors, NVIDIA represents a generational opportunity. Its financials are firing on all cylinders, its technology is unassailable for AI's most demanding workloads, and its software ecosystem is creating recurring revenue streams. While near-term volatility is inevitable—semiconductor stocks often swing with macroeconomic cycles—the secular tailwinds of AI adoption are too strong to ignore [2].

Recommendation: NVIDIA is a buy for long-term portfolios. Investors should focus on the company's secular growth narrative rather than short-term hiccups. The $1 trillion milestone isn't a question of “if,” but “when,” making it a core holding for those betting on AI's transformative potential [2].

Historically, NVIDIA's stock has demonstrated resilience following significant earnings beats. A backtest of its performance since 2022 shows that periods following earnings surprises yielded a final return of 7.33%, with a 70% win rate at the 30-day mark. This underscores the market's consistent positive reaction to NVIDIA's outperformance, reinforcing its long-term growth narrative [2].

As the AI revolution accelerates, NVIDIA isn't just keeping pace—it's writing the rules [2].

References:
[1] https://finance.yahoo.com/news/top-analyst-hikes-nvidia-target-143507845.html
[2] https://www.ainvest.com/news/nvidia-1-trillion-ambition-riding-ai-tsunami-dominance-semiconductors-2507/