Nvidia (NVDA) enters what many consider its most critical week of 2026. The company’s flagship GTC conference begins Monday, March 16, and continues through March 19. Chief Executive Jensen Huang is scheduled to open the event with his keynote presentation—likely sporting his iconic leather jacket.
NVIDIA Corporation, NVDA
Shares have traded sideways for several months, lingering around the $185 mark since August of last year. An 8% pullback materialized earlier this year before the stock rebounded. Meanwhile, Wall Street’s profit projections have continued trending upward.
Analysts project free cash flow for the fiscal year concluding in January 2027 will reach $178 billion—representing an 85% increase year-over-year. For perspective, Saudi Aramco established the historical benchmark for free cash flow in 2022 at approximately $150 billion. Should Nvidia achieve current consensus estimates, it would claim the title of most profitable corporation ever recorded.
Looking further ahead, analysts anticipate that milestone will be surpassed again, with free cash flow projections climbing to $233 billion in fiscal 2028.
Analyst scrutiny will concentrate on several critical topics. Supply chain visibility tops the list. Nvidia must demonstrate that its upcoming Vera Rubin chip deliveries remain on schedule and customer orders are being fulfilled according to commitments. Any indication of delays would likely trigger market volatility.
AI infrastructure spending sustainability represents another major concern. Tech giants including Amazon and Alphabet are projected to deploy $660 billion toward AI infrastructure throughout this year. Amazon’s capital expenditures alone have surged from approximately $50–$60 billion annually to an estimated $190 billion for the current year. Barclays research suggests total AI-related capital spending across the industry could reach $1 trillion by 2028.
Product development strategy also demands attention. The AI semiconductor landscape is transitioning from model training applications toward inference workloads—the deployment of trained models in production environments. This evolution creates different chip requirements.
Inference operations consist of two distinct phases: prefill, where input tokens are processed simultaneously (optimized for parallel GPU architecture), and decode, which generates output sequentially and benefits from purpose-built hardware designs.
Nvidia invested approximately $20 billion last year to license intellectual property from Groq, an emerging chip company, while bringing its engineering team in-house. Groq develops LPUs—language processing units—engineered specifically for cost-effective, high-efficiency decode operations.
Market participants will be seeking specifics on how Groq’s LPU architecture integrates into Nvidia’s broader chip strategy going forward. This acquisition positions the company to compete more effectively against cloud providers building proprietary silicon.
UBS characterizes the disconnect between its optimistic Nvidia earnings forecasts and the stock’s current discounted valuation as “seemingly unsustainable.” Nevertheless, UBS maintains that a transformative catalyst emerging from the conference appears “hard to see.”
Trading at 17 times projected earnings for next fiscal year, Nvidia currently commands a valuation multiple below the S&P 500 average. Among 70 analysts providing coverage, 93% assign Buy recommendations.
Consensus price targets cluster around $267–$273, implying potential appreciation of 45% to 49% from present levels.
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