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Markets Score 35 Bullish

Sandisk Poised to Outpace Nvidia as AI Storage Demand Surges

Apr 11, 2026 20:35 UTC
SNDK, NVDA
Short term

Rising demand for NAND flash memory in AI data centers is driving significant price increases and earnings growth for Sandisk. The company currently trades at a valuation discount compared to its AI peers and the broader market.

  • NAND flash contract prices expected to increase 70-75% this quarter
  • Sandisk fiscal Q2 non-GAAP EPS reached $6.20, up 5x YoY
  • Analyst projections for fiscal Q4 EPS stand at $18.63
  • SNDK trades at 13.8x forward earnings vs S&P 500's 20x average
  • Supply constraints in memory market creating tailwinds for storage providers

Sandisk (SNDK) is emerging as a high-growth alternative to Nvidia (NVDA) within the artificial intelligence ecosystem, driven by a critical shortage of data center storage. While Nvidia remains the dominant force in AI processors, the infrastructure required to support these chips—specifically high-capacity storage—is facing severe supply constraints. Industry data indicates that demand for NAND flash memory is significantly outpacing production. Competitors such as Kioxia have already reported selling out their 2026 supply, and Sandisk management has noted that customer demand is expected to remain above supply beyond the 2026 calendar year. This supply-demand imbalance is exerting upward pressure on pricing. Market research from TrendForce suggests contract prices for NAND flash could rise by 70% to 75% this quarter, an acceleration from the 60% jump seen in the first quarter. This pricing power is already reflecting in Sandisk's financials; the company reported non-GAAP earnings of $6.20 per share for fiscal Q2, a five-fold increase year-over-year. Looking ahead, analysts project a massive leap for fiscal Q4, with earnings per share potentially reaching $18.63. Despite this trajectory, Sandisk trades at approximately 13.8 times forward earnings, notably lower than the S&P 500 average of 20 times. As AI data centers scale, the bottleneck is shifting from compute to storage, positioning memory specialists to capture significant value.

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