Micron and Sandisk Have Crushed Nvidia as the Top Artificial Intelligence (AI) Stock in 2026. Can That Continue?

Micron is up 228% in 2026 and Sandisk nearly 600% as AI-driven memory chip shortages keep NAND and DRAM prices elevated. Nvidia remains comparatively subdued at about +12% this year, but it still posted 85% revenue growth last quarter and guided to $91 billion in next-quarter revenue, with hyperscaler AI capex seen reaching $1 trillion next year. The article argues Nvidia's valuation still looks reasonable at 23.3x fiscal 2027 earnings, though Micron and Sandisk may continue to outperform in the near term.

Analysis

The hidden winner in this setup is not just the memory vendors but the entire AI buildout chain that monetizes scarcity before end-demand normalizes. When NAND/DRAM pricing rips, hyperscalers have to choose between absorbing higher storage and memory costs or delaying incremental AI capacity; that tends to shift spend toward the highest-ROI compute first, which indirectly supports NVDA even if it lags the memory names in relative performance. The second-order effect is margin compression for server OEMs, module assemblers, and any customer with fixed-price data center rollouts.

The market is also underestimating how long supply discipline can persist in memory. Even if capex accelerates, memory is a lagging commodity cycle: by the time new wafer starts and packaging capacity hit the market, pricing power can already be rolling over, so the best equity returns usually occur before supply catches up. That argues for a months-long trade rather than a years-long chase in the most momentum-rich names, especially once investors start discounting peak earnings in 2027.

NVDA looks like the cleaner asymmetry if the goal is to own the AI capex envelope rather than the most extended commodity beneficiary. The stock can rerate quickly if investors start capitalizing the next 12 months of hyperscaler spend and the broader data center capex trajectory, but the upside path is likely more measured than in the memory complex. The contrarian miss is that the strongest trade may already be behind MU/SNDK on a percentage basis, while NVDA still has room to outperform on a risk-adjusted basis because expectations remain less extreme.

Key Decisions for Investors

• Prefer long NVDA vs long MU/SNDK for a 3-6 month horizon: lower multiple compression risk and better exposure to durable AI capex than the most crowded memory trade; use a relative-value pair if you want to stay long the AI theme.
• Take profits gradually in SNDK on momentum spikes over the next 2-8 weeks: the stock is most vulnerable once the market starts pricing peak margin assumptions rather than supply scarcity; trail stops tightly because commodity inflection points can reverse fast.
• Consider a long NVDA Jan-2027 call spread financed by selling farther out-of-the-money calls: captures a second-half 2026 rerating if hyperscaler spend inflects, while limiting downside if the market keeps ignoring forward guidance.
• Avoid chasing new longs in memory suppliers after a sharp post-earnings gap: the risk/reward deteriorates once revenue revisions become consensus, and the trade becomes dependent on perfect supply constraints persisting into 2027.