Nvidia beats forecasts with $68.1 billion quarter as agentic AI era begins

Nvidia’s fiscal fourth‑quarter earnings underscore how quickly the company has turned its data‑center GPUs into the de‑facto platform for “agentic AI,” a term analysts use to describe models that can act autonomously on user instructions. The Santa Clara‑based chipmaker posted $68.1 billion in revenue, a 73 % year‑over‑year jump, and net income of roughly $43 billion, or $1.76 per share, more than doubling the profit reported a year earlier. Those figures blew past the consensus forecasts compiled by analysts, a pattern that has persisted since Nvidia’s high‑end H100 and subsequent Hopper‑based GPUs became the preferred hardware for large‑scale language models three years ago, according to Fastcompany.

The company’s outlook for the next quarter reinforces the narrative that the AI boom is still in its infancy. Nvidia projected revenue for the February‑April period to climb 77 % from the prior year, a trajectory that would keep the firm on a growth curve well above the 50 % annual increases that many investors expected for the sector. “AI is here, AI is not going to go back,” CEO Jensen Huang told analysts on the earnings call, adding that demand for Nvidia’s chips is “skyrocketing” and will only intensify as enterprises move from proof‑of‑concept pilots to production‑grade deployments of autonomous agents, Fastcompany reported.

Investors, however, remain cautious about the sustainability of the surge. Wall Street analysts cited in a Reuters briefing noted that while the earnings beat was welcome, the market is now demanding a clearer plan for returning cash to shareholders. Nvidia’s market capitalization has ballooned from about $400 billion at the end of 2022 to nearly $4.8 trillion today, a ten‑fold increase that has raised concerns about a potential correction after three years of near‑continuous double‑digit growth, Reuters wrote. Jake Behan, head of capital markets at Direxion, warned that “no quarter has had more riding on it than this one,” emphasizing that the broader AI trade needs tangible profit‑sharing mechanisms to maintain investor confidence.

The earnings beat also highlighted the expanding ecosystem around Nvidia’s hardware. Original equipment manufacturers, cloud providers, and a growing cohort of AI‑first startups have all accelerated orders for the company’s GPUs, spurred by the launch of new generative‑AI services that rely on “agentic” capabilities such as real‑time decision making and autonomous task execution. Fastcompany noted that Huang’s thesis positions Nvidia not merely as a component supplier but as a foundational layer of the emerging AI economy, a view that aligns with the firm’s recent strategic moves to deepen software integration and offer end‑to‑end development stacks for autonomous agents.

Looking ahead, the key question for Nvidia will be whether it can translate its hardware dominance into recurring revenue streams as AI models mature and enterprises seek more predictable cost structures. Bloomberg’s live‑blog coverage of the earnings call flagged a sharp after‑hours sell‑off, suggesting that some investors are pricing in the risk that the current “agentic AI” hype could wane if model efficiency improves or alternative chip architectures gain traction. Nonetheless, the company’s guidance and the sheer scale of its quarterly results reinforce the view that Nvidia remains the central engine driving the next wave of AI‑powered productivity, a sentiment echoed across the coverage from Fastcompany, Reuters, and Bloomberg.