Photronics (PLAB) Operating Expenses (2011 - 2026)
Photronics' Operating Expenses was $26.25 million in fiscal Q3 2026 (quarter ended Aug 2, 2026), up 15.7% from $22.69 million a year earlier and up 11.3% from the prior quarter.
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Analysis
Photronics (PLAB) Operating Expenses (2011 - 2026) Analysis & Trends
On a trailing twelve-month basis, Photronics' Operating Expenses was $96.91 million through Aug 2, 2026, up 2.5% year-over-year; for FY2025 (ended Oct 31, 2025), it came in at $91.43 million, down 3.1% from FY2024.
- Operating Expenses shows a five-year compound annual growth rate of 5.3% (FY2020 to FY2025).
- In earlier fiscal years, Operating Expenses was $94.34 million in FY2024 (+13.5%), $83.11 million in FY2023 (+0.9%), $82.33 million in FY2022 (+8.3%) and $76.02 million in FY2021 (+7.5%).
- The fiscal Q3 2026 figure marks the highest quarterly Operating Expenses since fiscal Q4 2024.
- Compared with a year earlier, Operating Expenses has increased for three straight quarters, with growth averaging 5.6% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was fiscal Q4 2024 (growth of 30.8%); the worst was fiscal Q4 2025 (a decline of 11.8%).
- Per Business Quant data, PLAB's Operating Expenses in the three fiscal quarters before Q3 2026 was $23.58 million (Q2 2026), $23.9 million (Q1 2026) and $23.19 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Nvidia | 5,369.70 Bn | 5,143.86 Bn | 72.14 Bn | 8.41 Bn |
| 2 | Taiwan Semiconductor Manufacturing | 2,240.62 Bn | 1,865.48 Bn | 27.22 Bn | 3.13 Bn |
| 3 | Broadcom | 1,610.24 Bn | 1,536.29 Bn | 20.46 Bn | 4.50 Bn |
| 4 | Micron Technology | 1,032.70 Bn | 938.34 Bn | 47.05 Bn | 2.77 Bn |
| 5 | Advanced Micro Devices | 903.31 Bn | 860.06 Bn | 6.20 Bn | 4.21 Bn |
| 6 | Asml Holding | 651.41 Bn | 607.10 Bn | 5.90 Bn | - |
| 7 | Intel | 474.60 Bn | 343.73 Bn | 6.51 Bn | 4.71 Bn |
| 8 | Lam Research | 327.65 Bn | 304.45 Bn | 3.48 Bn | 965.25 Mn |
| 9 | Applied Materials | 324.38 Bn | 289.82 Bn | 4.59 Bn | 1.51 Bn |
| 10 | Photronics | 1.68 Bn | -854.37 Mn | 71.73 Mn | 26.25 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Aug 2, 2026 | 26.25 Mn |
| May 3, 2026 | 23.58 Mn |
| Feb 1, 2026 | 23.90 Mn |
| Oct 31, 2025 | 23.19 Mn |
| Aug 3, 2025 | 22.69 Mn |
| May 4, 2025 | 22.19 Mn |
| Feb 2, 2025 | 23.36 Mn |
| Oct 31, 2024 | 26.29 Mn |
| Jul 28, 2024 | 22.99 Mn |
| Apr 28, 2024 | 23.29 Mn |
| Jan 28, 2024 | 21.77 Mn |
| Oct 31, 2023 | 20.10 Mn |
| Jul 30, 2023 | 21.54 Mn |
| Apr 30, 2023 | 21.36 Mn |
| Jan 29, 2023 | 20.12 Mn |
| Oct 31, 2022 | 19.73 Mn |
| Jul 31, 2022 | 20.11 Mn |
| May 1, 2022 | 20.82 Mn |
| Jan 30, 2022 | 21.67 Mn |
| Oct 31, 2021 | 18.42 Mn |
API Access
Photronics 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=PLAB&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "PLAB", "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=PLAB&period=max&api_key=YOUR_API_KEY");
const data = await res.json();