Ondas (ONDS) Operating Expenses (2016 - 2026)
Ondas' Operating Expenses was $199.08 million in Q2 2026, compared with $12.58 million a year earlier and up 195.7% from the prior quarter.
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Analysis
Ondas (ONDS) Operating Expenses (2016 - 2026) Analysis & Trends
On a trailing twelve-month basis, Ondas' Operating Expenses was $320.57 million through Jun 30, 2026, up 654.5% year-over-year; for FY2025, it came in at $78.54 million, up 124.7% from FY2024.
- Operating Expenses shows a five-year compound annual growth rate of 44.5% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $34.95 million in FY2024 (-24.2%), $46.11 million in FY2023 (-34.6%), $70.54 million in FY2022 (+269.9%) and $19.07 million in FY2021 (+53.1%).
- The Q2 2026 figure marks the highest quarterly Operating Expenses in data going back to Q2 2016.
- Compared with a year earlier, Operating Expenses was higher in six of the last seven quarters, with growth averaging 136.0%.
- The best year-over-year quarter for Operating Expenses over five years was Q1 2026 (growth of 470.7%); the worst was Q4 2023 (a decline of 58.7%).
- Per Business Quant data, ONDS's Operating Expenses in the three quarters before Q2 2026 was $67.33 million (Q1 2026), $36.05 million (Q4 2025) and $18.11 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | General Electric | 330.21 Bn | 284.21 Bn | 4.68 Bn | 10.86 Bn |
| 2 | Rtx | 252.88 Bn | 226.09 Bn | 5.13 Bn | 21.96 Bn |
| 3 | Boeing | 145.76 Bn | 52.46 Bn | 2.41 Bn | 2.35 Bn |
| 4 | Lockheed Martin | 119.56 Bn | 106.28 Bn | 2.45 Bn | - |
| 5 | Howmet Aerospace | 91.38 Bn | 86.98 Bn | 951.00 Mn | 156.00 Mn |
| 6 | General Dynamics | 90.40 Bn | 77.51 Bn | 2.18 Bn | 12.63 Bn |
| 7 | Motorola Solutions | 74.81 Bn | 71.18 Bn | 1.68 Bn | 756.00 Mn |
| 8 | Northrop Grumman | 71.85 Bn | 61.10 Bn | 2.12 Bn | 9.78 Bn |
| 9 | Honeywell International | 67.04 Bn | 19.48 Bn | 3.65 Bn | 1.87 Bn |
| 10 | Ondas | 4.07 Bn | 210.18 Mn | 36.13 Mn | 199.08 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 199.08 Mn |
| Mar 31, 2026 | 67.33 Mn |
| Dec 31, 2025 | 36.05 Mn |
| Sep 30, 2025 | 18.11 Mn |
| Jun 30, 2025 | 12.58 Mn |
| Mar 31, 2025 | 11.80 Mn |
| Dec 31, 2024 | 9.40 Mn |
| Sep 30, 2024 | 8.71 Mn |
| Jun 30, 2024 | 8.11 Mn |
| Mar 31, 2024 | 8.73 Mn |
| Dec 31, 2023 | 14.37 Mn |
| Sep 30, 2023 | 6.49 Mn |
| Jun 30, 2023 | 11.57 Mn |
| Mar 31, 2023 | 13.68 Mn |
| Dec 31, 2022 | 34.79 Mn |
| Sep 30, 2022 | 13.95 Mn |
| Jun 30, 2022 | 11.69 Mn |
| Mar 31, 2022 | 10.11 Mn |
| Dec 31, 2021 | 7.21 Mn |
| Sep 30, 2021 | 4.93 Mn |
API Access
Ondas 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=ONDS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "ONDS", "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=ONDS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();