Magnachip Semiconductor (MX) Operating Expenses (2010 - 2026)
Magnachip Semiconductor (MX) recorded Operating Expenses of $18.62 million in Q2 2026, up 14.2% from $16.31 million a year earlier and up 29.7% from the prior quarter.
Magnachip Semiconductor (MX) Operating Expenses (2010 - 2026) Analysis & Trends
On a TTM basis, Magnachip Semiconductor's Operating Expenses came in at $69.29 million as of Jun 30, 2026, up 6.9% year-over-year; for FY2025, it was $67.25 million, up 3.9% from FY2024.
- Annual Operating Expenses has a five-year compound annual growth rate of -7.9% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $64.7 million in FY2024 (-40.8%), $109.28 million in FY2023 (+2.6%), $106.51 million in FY2022 (+51.9%) and $70.14 million in FY2021 (-30.8%).
- Quarterly Operating Expenses has ranged from -$25.27 million in Q4 2021 to $33.91 million in Q1 2023 over the past five years.
- On a year-over-year basis, Operating Expenses rose in three of the last eight quarters, with an average decline of 5.1%.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 29.8% in Q1 2023, against a decline of 53.6% in Q1 2024 at the low end.
- Per Business Quant, the preceding three quarters came in at $14.36 million (Q1 2026), $16.22 million (Q4 2025) and $20.08 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Nvidia | 5,234.47 Bn | 5,008.64 Bn | 72.14 Bn | 8.41 Bn |
| 2 | Taiwan Semiconductor Manufacturing | 2,203.85 Bn | 1,828.72 Bn | 27.22 Bn | 3.13 Bn |
| 3 | Broadcom | 1,595.70 Bn | 1,521.75 Bn | 20.46 Bn | 4.50 Bn |
| 4 | Micron Technology | 1,016.99 Bn | 922.63 Bn | 47.05 Bn | 2.77 Bn |
| 5 | Advanced Micro Devices | 878.86 Bn | 835.61 Bn | 6.20 Bn | 4.21 Bn |
| 6 | Asml Holding | 634.27 Bn | 589.96 Bn | 5.90 Bn | - |
| 7 | Intel | 470.44 Bn | 339.57 Bn | 6.51 Bn | 4.71 Bn |
| 8 | Lam Research | 332.09 Bn | 308.88 Bn | 3.48 Bn | 965.25 Mn |
| 9 | Applied Materials | 322.22 Bn | 287.66 Bn | 4.59 Bn | 1.51 Bn |
| 10 | Magnachip Semiconductor | 93.39 Mn | -311.57 Mn | 8.65 Mn | 18.62 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 18.62 Mn |
| Mar 31, 2026 | 14.36 Mn |
| Dec 31, 2025 | 16.22 Mn |
| Sep 30, 2025 | 20.08 Mn |
| Jun 30, 2025 | 16.31 Mn |
| Mar 31, 2025 | 14.64 Mn |
| Dec 31, 2024 | 17.90 Mn |
| Sep 30, 2024 | 15.99 Mn |
| Jun 30, 2024 | 15.51 Mn |
| Mar 31, 2024 | 15.75 Mn |
| Dec 31, 2023 | 27.46 Mn |
| Sep 30, 2023 | 23.72 Mn |
| Jun 30, 2023 | 24.19 Mn |
| Mar 31, 2023 | 33.91 Mn |
| Dec 31, 2022 | 26.22 Mn |
| Sep 30, 2022 | 27.23 Mn |
| Jun 30, 2022 | 26.94 Mn |
| Mar 31, 2022 | 26.12 Mn |
| Dec 31, 2021 | -25.27 Mn |
| Sep 30, 2021 | 26.59 Mn |
Magnachip Semiconductor 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=MX&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "MX", "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=MX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();