Nvidia Q4 FY2025: Record $39.3B Revenue, Blackwell GPU Exceeds Expectations

Earnings Call02-27

1. Nvidia announced its Q4 FY2025 earnings:
- Record revenue of $39.3 billion, up 12% sequentially and 78% year-over-year
- Data Center revenue of $35.6 billion, up 16% sequentially and 93% year-over-year
- Blackwell GPU sales exceeded expectations, delivering $11 billion in revenue
2. Outlook for Q1 FY2026:
- Total revenue expected to be $43 billion (±2%)
- Significant ramp-up of Blackwell GPU production anticipated
- Sequential growth expected in both Data Center and Gaming segments
3. Blackwell GPU highlights:
- Fastest product ramp in company history
- Designed for reasoning AI and inference, offering up to 25x higher token throughput
- Addressing pre-training, post-training, and inference across cloud, on-premise, and enterprise
4. AI market trends:
- Increasing demand for post-training and model customization
- Acceleration in inference demand driven by test-time scaling and new reasoning models
- Growing adoption of Nvidia infrastructure for robotics and physical AI development
Disclaimer: This earnings call summary is generated by AI and is for informational purposes only. Due to technical limitations, inaccuracies may exist. It does not constitute investment advice or commitments.

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Nvidia announced its Q4 FY2025 earnings:<br>   - Record revenue of $39.3 billion, up 12% sequentially and 78% year-over-year<br>   - Data Center revenue of $35.6 billion, up 16% sequentially and 93% year-over-year<br>   - Blackwell GPU sales exceeded expectations, delivering $11 billion in revenue<br>2. Outlook for Q1 FY2026:<br>   - Total revenue expected to be $43 billion (±2%)<br>   - Significant ramp-up of Blackwell GPU production anticipated<br>   - Sequential growth expected in both Data Center and Gaming segments<br>3. Blackwell GPU highlights:<br>   - Fastest product ramp in company history<br>   - Designed for reasoning AI and inference, offering up to 25x higher token throughput<br>   - Addressing pre-training, post-training, and inference across cloud, on-premise, and enterprise<br>4. 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