Wolfspeed (WOLF) Operating Expenses (2009 - 2026)
Wolfspeed (WOLF) recorded Operating Expenses of -$4.4 million in fiscal Q4 2026 (quarter ended Jun 28, 2026), compared with $196.5 million a year earlier.
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Analysis
Wolfspeed (WOLF) Operating Expenses (2009 - 2026) Analysis & Trends
For FY2026 (ended Jun 28, 2026), Wolfspeed reported Operating Expenses of $238.4 million, down 69.6% from FY2025.
- Annual Operating Expenses has a five-year compound annual growth rate of -7.9% (FY2021 to FY2026).
- Across earlier fiscal years, Operating Expenses came in at $783.2 million in FY2025 (+67.0%), $468.9 million in FY2024 (+18.9%), $394.5 million in FY2023 (+21.2%) and $325.6 million in FY2022 (-9.4%).
- The fiscal Q4 2026 figure is the lowest quarterly Operating Expenses in data going back to fiscal Q1 2010.
- On a year-over-year basis, Operating Expenses rose in four of the last seven quarters, with growth averaging 31.5%.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 254.3% in fiscal Q4 2023, against a decline of 72.0% in fiscal Q2 2026 at the low end.
- Per Business Quant, the preceding three fiscal quarters came in at $154.4 million (Q3 2026), $80.1 million (Q2 2026) and $84.3 million (Q1 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Nvidia | 5,235.65 Bn | 5,009.82 Bn | 72.14 Bn | 8.41 Bn |
| 2 | Taiwan Semiconductor Manufacturing | 2,206.84 Bn | 1,831.70 Bn | 27.22 Bn | 3.13 Bn |
| 3 | Broadcom | 1,595.23 Bn | 1,521.27 Bn | 20.46 Bn | 4.50 Bn |
| 4 | Micron Technology | 1,011.16 Bn | 916.79 Bn | 47.05 Bn | 2.77 Bn |
| 5 | Advanced Micro Devices | 874.75 Bn | 831.50 Bn | 6.20 Bn | 4.21 Bn |
| 6 | Asml Holding | 634.65 Bn | 590.34 Bn | 5.90 Bn | - |
| 7 | Intel | 469.01 Bn | 338.14 Bn | 6.51 Bn | 4.71 Bn |
| 8 | Lam Research | 331.52 Bn | 308.31 Bn | 3.48 Bn | 965.25 Mn |
| 9 | Applied Materials | 321.88 Bn | 287.32 Bn | 4.59 Bn | 1.51 Bn |
| 10 | Wolfspeed | 924.57 Mn | -175.43 Mn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Mar 29, 2026 | 74.30 Mn |
| Dec 28, 2025 | 80.10 Mn |
| Sep 28, 2025 | 84.30 Mn |
| Jun 29, 2025 | 196.50 Mn |
| Mar 30, 2025 | 172.00 Mn |
| Dec 29, 2024 | 285.80 Mn |
| Sep 29, 2024 | 193.90 Mn |
| Jun 30, 2024 | 121.60 Mn |
| Mar 31, 2024 | 108.30 Mn |
| Dec 31, 2023 | 110.20 Mn |
| Sep 24, 2023 | 108.20 Mn |
| Jun 25, 2023 | 102.40 Mn |
| Mar 26, 2023 | 97.50 Mn |
| Dec 25, 2022 | 89.80 Mn |
| Sep 25, 2022 | 90.30 Mn |
| Jun 26, 2022 | 28.90 Mn |
| Mar 27, 2022 | 99.60 Mn |
| Dec 26, 2021 | 98.20 Mn |
| Sep 26, 2021 | 98.90 Mn |
| Jun 27, 2021 | 91.70 Mn |
API Access
Wolfspeed Operating Expenses API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=operating-expenses&ticker=WOLF&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "WOLF", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=WOLF&period=max&api_key=YOUR_API_KEY");
const data = await res.json();