Diodes (DIOD) Operating Expenses (2010 - 2026)
Diodes (DIOD) posted Operating Expenses of $114.28 million for Q2 2026, up 7.9% from $105.94 million a year earlier and up 4.8% from the prior quarter.
Powered by 
Analysis
Diodes (DIOD) Operating Expenses (2010 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Diodes was $440.94 million, up 9.0% year-over-year; for FY2025, it was $426.97 million, up 10.8% from FY2024.
- Annual Operating Expenses shows a five-year compound annual growth rate of 7.5% (FY2020 to FY2025).
- In prior years, Diodes' Operating Expenses was $385.41 million in FY2024 (-5.4%), $407.61 million in FY2023 (-2.7%), $419.04 million in FY2022 (+6.3%) and $394.38 million in FY2021 (+32.9%).
- The Q2 2026 figure stands as the highest quarterly Operating Expenses in data going back to Q1 2010.
- On a year-over-year basis, Operating Expenses has increased in each of the last seven quarters, with growth averaging 7.5% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q3 2021, with growth of 42.0%; the weakest was Q1 2024, with a decline of 19.8%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $109.03 million (Q1 2026), $108.73 million (Q4 2025) and $108.92 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Nvidia | 5,257.94 Bn | 5,032.10 Bn | 72.14 Bn | 8.41 Bn |
| 2 | Taiwan Semiconductor Manufacturing | 2,182.39 Bn | 1,807.25 Bn | 27.22 Bn | 3.13 Bn |
| 3 | Broadcom | 1,596.71 Bn | 1,522.75 Bn | 20.46 Bn | 4.50 Bn |
| 4 | Micron Technology | 1,020.41 Bn | 926.05 Bn | 47.05 Bn | 2.77 Bn |
| 5 | Advanced Micro Devices | 879.62 Bn | 836.36 Bn | 6.20 Bn | 4.21 Bn |
| 6 | Asml Holding | 640.55 Bn | 596.23 Bn | 5.90 Bn | - |
| 7 | Intel | 470.49 Bn | 339.62 Bn | 6.51 Bn | 4.71 Bn |
| 8 | Lam Research | 342.11 Bn | 318.91 Bn | 3.48 Bn | 965.25 Mn |
| 9 | Applied Materials | 328.25 Bn | 293.69 Bn | 4.59 Bn | 1.51 Bn |
| 10 | Diodes | 3.88 Bn | 2.26 Bn | 147.57 Mn | 114.28 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 114.28 Mn |
| Mar 31, 2026 | 109.03 Mn |
| Dec 31, 2025 | 108.73 Mn |
| Sep 30, 2025 | 108.92 Mn |
| Jun 30, 2025 | 105.94 Mn |
| Mar 31, 2025 | 103.40 Mn |
| Dec 31, 2024 | 98.97 Mn |
| Sep 30, 2024 | 96.13 Mn |
| Jun 30, 2024 | 103.68 Mn |
| Mar 31, 2024 | 86.64 Mn |
| Dec 31, 2023 | 91.77 Mn |
| Sep 30, 2023 | 102.00 Mn |
| Jun 30, 2023 | 105.81 Mn |
| Mar 31, 2023 | 108.03 Mn |
| Dec 31, 2022 | 109.75 Mn |
| Sep 30, 2022 | 105.37 Mn |
| Jun 30, 2022 | 100.29 Mn |
| Mar 31, 2022 | 103.64 Mn |
| Dec 31, 2021 | 104.70 Mn |
| Sep 30, 2021 | 103.98 Mn |
API Access
Diodes 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=DIOD&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "DIOD", "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=DIOD&period=max&api_key=YOUR_API_KEY");
const data = await res.json();