Rtx (RTX) Operating Expenses (2009 - 2026)
Rtx (RTX) posted Operating Expenses of $21.96 billion for Q2 2026, up 12.8% from $19.48 billion a year earlier and up 12.1% from the prior quarter.
Rtx (RTX) Operating Expenses (2009 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Rtx was $83.51 billion, up 10.3% year-over-year; for FY2025, it came in at $79.72 billion, up 7.6% from FY2024.
- Annual Operating Expenses has increased for seven consecutive years, with a five-year compound annual growth rate of 7.2% (FY2020 to FY2025).
- In prior years, Rtx's Operating Expenses was $74.07 billion in FY2024 (+13.2%), $65.45 billion in FY2023 (+6.1%), $61.69 billion in FY2022 (+3.4%) and $59.68 billion in FY2021 (+6.2%).
- The Q2 2026 figure stands as the highest quarterly Operating Expenses in data going back to Q2 2009.
- On a year-over-year basis, Operating Expenses has increased in each of the last 11 quarters, with growth averaging 10.2% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q3 2024, with growth of 22.4%; the weakest was Q4 2021, with a decline of 4.1%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $19.59 billion (Q1 2026), $21.95 billion (Q4 2025) and $20.02 billion (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | General Electric | 330.06 Bn | 284.06 Bn | 4.68 Bn | 10.86 Bn |
| 2 | Rtx | 252.10 Bn | 225.31 Bn | 5.13 Bn | 21.96 Bn |
| 3 | Boeing | 148.40 Bn | 55.10 Bn | 2.41 Bn | 2.35 Bn |
| 4 | Lockheed Martin | 118.20 Bn | 104.92 Bn | 2.45 Bn | - |
| 5 | Howmet Aerospace | 92.39 Bn | 87.99 Bn | 951.00 Mn | 156.00 Mn |
| 6 | General Dynamics | 89.92 Bn | 77.03 Bn | 2.18 Bn | 12.63 Bn |
| 7 | Motorola Solutions | 73.84 Bn | 70.20 Bn | 1.68 Bn | 756.00 Mn |
| 8 | Northrop Grumman | 71.73 Bn | 60.97 Bn | 2.12 Bn | 9.78 Bn |
| 9 | Honeywell International | 66.60 Bn | 19.04 Bn | 3.65 Bn | 1.87 Bn |
| 10 | TransDigm | 60.79 Bn | 48.88 Bn | 1.63 Bn | 332.00 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 21.96 Bn |
| Mar 31, 2026 | 19.59 Bn |
| Dec 31, 2025 | 21.95 Bn |
| Sep 30, 2025 | 20.02 Bn |
| Jun 30, 2025 | 19.48 Bn |
| Mar 31, 2025 | 18.28 Bn |
| Dec 31, 2024 | 19.77 Bn |
| Sep 30, 2024 | 18.20 Bn |
| Jun 30, 2024 | 18.30 Bn |
| Mar 31, 2024 | 17.81 Bn |
| Dec 31, 2023 | 18.12 Bn |
| Sep 30, 2023 | 14.86 Bn |
| Jun 30, 2023 | 16.85 Bn |
| Mar 31, 2023 | 15.62 Bn |
| Dec 31, 2022 | 16.63 Bn |
| Sep 30, 2022 | 15.48 Bn |
| Jun 30, 2022 | 14.98 Bn |
| Mar 31, 2022 | 14.66 Bn |
| Dec 31, 2021 | 15.66 Bn |
| Sep 30, 2021 | 14.99 Bn |
Rtx 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=RTX&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "RTX", "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=RTX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();