AI accelerators need far more high-bandwidth memory than legacy systems.
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Price
$865.46
1D change
+1.94%
Market cap
$977.44B
Sector
Technology
| Metric | MU |
|---|---|
| Price | $865.46 |
| 1D Change | +1.94% |
| Market Cap | $977.44B |
| Enterprise Value | $939.15B |
| Trailing P/E | 19.2 |
| Forward P/E | 5.7 |
| PEG Ratio | 0.12x |
| Price / Sales | 10.8 |
| EV / Revenue | 10.4 |
| Revenue Growth | 345.7% |
| Earnings Growth | 1368.5% |
| Gross Margin | 72.6% |
| Operating Margin | 80.4% |
| Net Margin | 55.9% |
| ROE | 66.6% |
| Free Cash Flow | $7.64B |
| FCF Margin | 8.5% |
| Debt / Equity | 6.33x |
| Current Ratio | 3.42x |
| Dividend Yield | 0.07% |
| Next Earnings | Sep 23, 2026 |
| Quarterly Revenue | $41.46B |
| Revenue QoQ | +73.7% |
| Quarterly Net Income | $28.24B |
| Net Income QoQ | +104.9% |
MU thesis lens
AI memory / HBM
Why it could benefit
- AI accelerators need far more high-bandwidth memory than legacy systems.
- Tighter HBM supply can improve Micron's pricing power and mix.
- Memory is cyclical, but AI demand can make the upcycle sharper and longer.
Moat / edge
- Complex manufacturing know-how in memory.
- Scale economies and technology roadmaps matter enormously.
- HBM positions it closer to the highest-value part of AI memory demand.
What to watch
- HBM market share, margins, and capacity ramps.
- Inventory discipline across DRAM and NAND.
- Gross-margin trajectory through the cycle.
Key risks
- Memory remains cyclical and can overshoot in both directions.
- Execution issues on next-gen nodes or HBM qualification would matter a lot.