Ipg Photonics (IPGP) Operating Expenses (2010 - 2026)
Ipg Photonics' Operating Expenses was $107.99 million in Q2 2026, up 15.5% from $93.47 million a year earlier and up 0.7% from the prior quarter.
Ipg Photonics (IPGP) Operating Expenses (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, Ipg Photonics' Operating Expenses was $402.13 million through Jun 30, 2026, down 28.9% year-over-year; for FY2025, it came in at $368.36 million, down 32.6% from FY2024.
- Operating Expenses shows a five-year compound annual growth rate of 1.6% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $546.41 million in FY2024 (+76.4%), $309.73 million in FY2023 (-19.7%), $385.91 million in FY2022 (+17.5%) and $328.52 million in FY2021 (-3.5%).
- The Q2 2026 figure marks the highest quarterly Operating Expenses since Q3 2024.
- Compared with a year earlier, Operating Expenses has increased for three straight quarters, with growth averaging 37.9% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q3 2024 (growth of 298.3%); the worst was Q3 2025 (a decline of 70.4%).
- Per Business Quant data, IPGP's Operating Expenses in the three quarters before Q2 2026 was $107.24 million (Q1 2026), $95.76 million (Q4 2025) and $91.15 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Caterpillar | 372.79 Bn | 344.49 Bn | 7.76 Bn | 16.25 Bn |
| 2 | Amphenol | 207.98 Bn | 202.68 Bn | 3.55 Bn | 963.40 Mn |
| 3 | Deere | 181.02 Bn | 189.78 Bn | 4.66 Bn | 10.73 Bn |
| 4 | Eaton | 166.86 Bn | 164.09 Bn | 2.86 Bn | 1.46 Bn |
| 5 | Parker-Hannifin | 120.45 Bn | 118.58 Bn | 2.25 Bn | 874.00 Mn |
| 6 | Vertiv Holdings | 92.94 Bn | 83.56 Bn | 1.23 Bn | 490.50 Mn |
| 7 | Emerson Electric | 86.56 Bn | 79.32 Bn | 2.66 Bn | 1.34 Bn |
| 8 | 3M | 84.72 Bn | 66.18 Bn | 2.68 Bn | 5.52 Bn |
| 9 | Illinois Tool Works | 73.32 Bn | 69.88 Bn | 1.90 Bn | - |
| 10 | Ipg Photonics | 3.33 Bn | -64.39 Mn | 112.52 Mn | 107.99 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 107.99 Mn |
| Mar 31, 2026 | 107.24 Mn |
| Dec 31, 2025 | 95.76 Mn |
| Sep 30, 2025 | 91.15 Mn |
| Jun 30, 2025 | 93.47 Mn |
| Mar 31, 2025 | 87.99 Mn |
| Dec 31, 2024 | 76.39 Mn |
| Sep 30, 2024 | 307.44 Mn |
| Jun 30, 2024 | 84.15 Mn |
| Mar 31, 2024 | 78.44 Mn |
| Dec 31, 2023 | 85.39 Mn |
| Sep 30, 2023 | 77.20 Mn |
| Jun 30, 2023 | 75.63 Mn |
| Mar 31, 2023 | 71.51 Mn |
| Dec 31, 2022 | 149.30 Mn |
| Sep 30, 2022 | 57.26 Mn |
| Jun 30, 2022 | 100.67 Mn |
| Mar 31, 2022 | 78.68 Mn |
| Dec 31, 2021 | 81.20 Mn |
| Sep 30, 2021 | 83.89 Mn |
Ipg Photonics 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=IPGP&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "IPGP", "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=IPGP&period=max&api_key=YOUR_API_KEY");
const data = await res.json();