General Electric (GE) Operating Expenses (2009 - 2026)
General Electric (GE) recorded Operating Expenses of $10.86 billion in Q2 2026, up 21.6% from $8.93 billion a year earlier and up 6.7% from the prior quarter.
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Analysis
General Electric (GE) Operating Expenses (2009 - 2026) Analysis & Trends
On a TTM basis, General Electric's Operating Expenses came in at $41.46 billion as of Jun 30, 2026, up 19.4% year-over-year; for FY2025, it came in at $37.34 billion, up 12.0% from FY2024.
- Annual Operating Expenses has increased for three straight years, though with a five-year compound annual growth rate of -14.4% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $33.35 billion in FY2024 (+5.4%), $31.63 billion in FY2023 (+11.2%), $28.43 billion in FY2022 (-56.2%) and $64.86 billion in FY2021 (-20.2%).
- The Q2 2026 figure is the highest quarterly Operating Expenses since Q1 2023.
- On a year-over-year basis, Operating Expenses has increased for eight consecutive quarters, with growth averaging 13.5% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 27.4% in Q1 2026, against a decline of 58.0% in Q4 2021 at the low end.
- Per Business Quant, the preceding three quarters came in at $10.18 billion (Q1 2026), $10.47 billion (Q4 2025) and $9.95 billion (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | General Electric | 324.09 Bn | 278.09 Bn | 4.68 Bn | 10.86 Bn |
| 2 | Rtx | 250.22 Bn | 223.44 Bn | 5.13 Bn | 21.96 Bn |
| 3 | Boeing | 147.08 Bn | 53.78 Bn | 2.41 Bn | 2.35 Bn |
| 4 | Lockheed Martin | 117.51 Bn | 104.24 Bn | 2.45 Bn | - |
| 5 | Howmet Aerospace | 90.46 Bn | 86.07 Bn | 951.00 Mn | 156.00 Mn |
| 6 | General Dynamics | 89.77 Bn | 76.88 Bn | 2.18 Bn | 12.63 Bn |
| 7 | Motorola Solutions | 73.88 Bn | 70.24 Bn | 1.68 Bn | 756.00 Mn |
| 8 | Northrop Grumman | 68.68 Bn | 57.92 Bn | 2.12 Bn | 9.78 Bn |
| 9 | Honeywell International | 66.86 Bn | 19.30 Bn | 3.65 Bn | 1.87 Bn |
| 10 | TransDigm | 59.83 Bn | 47.91 Bn | 1.63 Bn | 332.00 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 10.86 Bn |
| Mar 31, 2026 | 10.18 Bn |
| Dec 31, 2025 | 10.47 Bn |
| Sep 30, 2025 | 9.95 Bn |
| Jun 30, 2025 | 8.93 Bn |
| Mar 31, 2025 | 7.99 Bn |
| Dec 31, 2024 | 8.82 Bn |
| Sep 30, 2024 | 8.97 Bn |
| Jun 30, 2024 | 7.58 Bn |
| Mar 31, 2024 | 7.97 Bn |
| Dec 31, 2023 | 8.74 Bn |
| Sep 30, 2023 | 8.12 Bn |
| Jun 30, 2023 | 7.74 Bn |
| Mar 31, 2023 | 14.08 Bn |
| Dec 31, 2022 | -14.22 Bn |
| Sep 30, 2022 | 14.88 Bn |
| Jun 30, 2022 | 13.87 Bn |
| Mar 31, 2022 | 13.90 Bn |
| Dec 31, 2021 | 9.00 Bn |
| Sep 30, 2021 | 18.34 Bn |
API Access
General Electric 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=GE&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "GE", "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=GE&period=max&api_key=YOUR_API_KEY");
const data = await res.json();