NVIDIA Corp., an American semiconductor company and a leading global manufacturer of high-end graphics processing units (GPUs), in its Q4 earnings call discusses three critical AI scaling laws driving compute demand: pre-training; post-training, requiring more compute than pre-training; and inference-time reasoning, potentially requiring 100x more compute. Management emphasizes AI’s mainstream adoption across industries, outlined three emerging domains of agentic AI for enterprise, physical AI for industrial systems, and robotics that will eventually surpass cloud service provider usage, and highlights Blackwell’s 25x performance improvement for reasoning models. The company confirmed Blackwell Ultra will launch in second-half 2025, addressed ASIC competition by emphasizing Nvidia’s advantages, and noted China revenue remains at approximately half of pre-export control levels.
NVIDIA delivered exceptional 4Q performance, with revenue soaring 78% and adjusted EPS of $0.89, significantly surpassing analyst expectations. The company’s data center business dominated with 91% of total sales, growing 93% to $35.6 billion due to unprecedented AI chip demand, while its next-generation Blackwell AI processors contributed $11 billion in its first full quarter, the fastest product ramp in Nvidia’s history. Looking ahead, Nvidia projects approximately $43 billion in 1Q revenue, representing 65% year-over-year growth, though potential challenges include growth deceleration, increasing competition from custom chips developed by tech giants, and U.S. export controls affecting Chinese markets.
Continue Reading: Unearth the Vital Insights from NVIDIA Corp.’s Earnings Call!
Financial/Operational Metrics:
- Revenue: $39.3 billion, up 78% YoY.
- Net Income: $22.1 billion, up 80% YoY.
- Diluted EPS: $0.89, up 82% YoY.
- Operating Income: $24.03 billion, up 77% YoY.
- Operating Expense: $4.69 billion, up 48% YoY.
- Free Cash Flow: $15.5 billion, up 38% YoY.
Q1 Outlook:
- Revenue: Expected to be $43.0 billion (±2%).
- Gross Margin: 70.6% (±0.5 percentage points).
- Operating Expenses: $5.2 billion GAAP, $3.6 billion Non-GAAP.
Analyst Crossfire:
- Inference & AI Compute Scaling, Blackwell Ramp & Supply Chain (C.J. Muse – Cantor Fitzgerald, Joe Moore – Morgan Stanley): Post-training and inference demand significantly outpace pretraining, with reasoning AI models requiring up to 100x more compute. Blackwell was specifically designed to handle long-thinking AI models with 25x higher throughput. Blackwell’s ramp has been highly successful, with 350 plants manufacturing its 1.5 million components. Despite initial challenges, major customers like CoreWeave, Microsoft, and OpenAI have successfully deployed Blackwell (Jensen Huang – CEO).
- Gross Margins & AI Demand Sustainability, Blackwell Ultra Launch & Transition (Vivek Arya – Bank of America, Harlan Sur – JPMorgan): Gross margins will remain in the low 70s during the Blackwell ramp but are expected to recover to the mid-70s later this year. Jensen Huang reaffirmed confidence in long-term AI demand, citing increasing capital investments, growing enterprise AI adoption, and continued startup activity. Blackwell Ultra will launch in H2 2025, with a smoother transition than Hopper-to-Blackwell. NVIDIA is already working with partners on the Vera Rubin platform, set to follow Blackwell Ultra (Colette Kress – CFO, Jensen Huang – CEO).
- Custom ASICs vs. Merchant GPUs, U.S. Market Growth & China Impact (Timothy Arcuri – UBS, Ben Reitzes – Melius Research): NVIDIA GPUs are more general-purpose, support a broader AI ecosystem, and offer significantly faster performance. NVDA highlighted that the AI software stack complexity makes custom ASIC adoption challenging, and NVIDIA’s ability to rapidly deploy solutions remains a competitive advantage. AI adoption has gone mainstream across industries, ensuring continued demand even with shifting geographic contributions. AI is now integral to fintech, education, healthcare, and logistics (Jensen Huang – CEO).
- Enterprise AI Expansion & Industrial AI, AI Infrastructure Replacement Cycle (Mark Lipacis – Evercore ISI, Aaron Rakers – Wells Fargo): Long-term AI adoption will extend beyond cloud providers to industrial applications like autonomous vehicles and robotics, creating new computing needs for enterprises. Older NVIDIA architectures like Volta and Pascal remain in use due to CUDA’s flexibility, with AI workloads being distributed across generations of GPUs to optimize efficiency (Jensen Huang – CEO).
- Gross Margins & Tariff Uncertainty, Enterprise AI Growth & CSP Spending (Atif Malik – Citi, Mark Lipacis – Evercore ISI): Gross margin improvements will come from cost efficiencies in Blackwell’s production. The impact of potential U.S. tariffs remains uncertain but is being monitored. Enterprise AI revenue doubled YoY, growing at a similar rate to large CSPs. Enterprises consume AI through both CSP-hosted services and their own infrastructure, signaling long-term expansion (Colette Kress – CFO).
The post NVDA Q4 Call Highlights: Growth, Blackwell’s Ramp, and Market Leadership! first appeared on AlphaStreet.
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