Nvidia Eyes CPU, Memory, Inference Speed with Secured $750 Billion AI Chip Backlog

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Analyst highlights Nvidia’s CPU performance, memory capacity, and inference speed as critical drivers for its Q1 results and notes a secured $750 billion AI chip backlog over the next 18 months, underpinning next year’s estimates. Memory price increases are being passed to hyperscale customers, reinforcing Nvidia’s ability to maintain 70%+ margins.

1. Key Q1 Metrics to Watch

Analysts are zeroing in on Nvidia’s CPU throughput, memory bandwidth, and inference speed as the primary indicators of its Q1 performance, given the growing demand for high-performance AI workloads and data center expansion.

2. $750 Billion AI Chip Backlog Strength

Nvidia has secured roughly $750 billion in AI chip orders over the next 18 months, providing a robust revenue backlog that makes consensus estimates for the coming fiscal year highly reliable and lowers execution risk.

3. Margin Sustainability Amid Competition

Despite competitors like Broadcom, TSMC, Intel, and AMD achieving margins in the 70–80% range, Nvidia is choosing stable pricing to deter competition, and analysts believe its ability to raise prices if needed secures current margin levels.

4. Memory Supply and Pricing Strategy

Nvidia has locked in memory supply to mitigate cost volatility and is passing price increases onto hyperscale customers, ensuring that rising DRAM and HBM costs do not erode its gross margins.

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Nvidia Eyes CPU, Memory, Inference Speed with Secured $750 Billion AI Chip Backlog - NVDA News | Rallies