Stabilis Solutions (SLNG) Operating Expenses (2010 - 2026)
Stabilis Solutions (SLNG) reported Operating Expenses of $16.7 million for Q2 2026, down 6.1% from $17.78 million a year earlier but up 13.9% from the prior quarter.
Stabilis Solutions (SLNG) Operating Expenses (2010 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Stabilis Solutions' Operating Expenses came in at $64.95 million, down 7.5% year-over-year; for FY2025, it was $70.76 million, up 1.2% from FY2024.
- Operating Expenses has a five-year compound annual growth rate of 7.4% (FY2020 to FY2025).
- By year, Operating Expenses came in at $69.91 million in FY2024 (-5.4%), $73.93 million in FY2023 (-26.4%), $100.39 million in FY2022 (+28.3%) and $78.25 million in FY2021 (+58.0%).
- Five-year quarterly Operating Expenses spans a low of $14.06 million in Q4 2025 and a high of $29.28 million in Q4 2022.
- Year over year, Operating Expenses has now declined in each of the last three quarters, with an average decline of 3.0% over the last eight quarters.
- The high point for year-over-year Operating Expenses in five years was Q3 2021 (growth of 94.9%); the low point was Q4 2023 (a decline of 42.2%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $14.66 million (Q1 2026), $14.06 million (Q4 2025) and $19.53 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Enbridge | 104.58 Bn | 100.18 Bn | 4.84 Bn | 19.09 Bn |
| 2 | Williams Companies | 86.03 Bn | 84.75 Bn | 2.54 Bn | 1.87 Bn |
| 3 | Enterprise Products Partners | 80.00 Bn | 78.39 Bn | - | 16.13 Bn |
| 4 | Kinder Morgan | 74.74 Bn | 74.44 Bn | 3.07 Bn | 3.13 Bn |
| 5 | Energy Transfer | 69.45 Bn | 62.63 Bn | 7.40 Bn | 30.76 Bn |
| 6 | Tc Energy | 64.24 Bn | 60.32 Bn | 2.81 Bn | -1.06 Bn |
| 7 | Targa Resources | 62.85 Bn | 62.33 Bn | 2.14 Bn | 354.10 Mn |
| 8 | Cheniere Energy | 59.18 Bn | 54.01 Bn | 5.29 Bn | 1.44 Bn |
| 9 | Mplx | 59.17 Bn | 52.74 Bn | 2.91 Bn | 1.93 Bn |
| 10 | Stabilis Solutions | 85.73 Mn | 60.35 Mn | 2.35 Mn | 16.70 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 16.70 Mn |
| Mar 31, 2026 | 14.66 Mn |
| Dec 31, 2025 | 14.06 Mn |
| Sep 30, 2025 | 19.53 Mn |
| Jun 30, 2025 | 17.78 Mn |
| Mar 31, 2025 | 19.40 Mn |
| Dec 31, 2024 | 15.66 Mn |
| Sep 30, 2024 | 17.36 Mn |
| Jun 30, 2024 | 18.50 Mn |
| Mar 31, 2024 | 18.39 Mn |
| Dec 31, 2023 | 16.91 Mn |
| Sep 30, 2023 | 15.79 Mn |
| Jun 30, 2023 | 15.40 Mn |
| Mar 31, 2023 | 25.83 Mn |
| Dec 31, 2022 | 29.28 Mn |
| Sep 30, 2022 | 24.80 Mn |
| Jun 30, 2022 | 25.69 Mn |
| Mar 31, 2022 | 20.63 Mn |
| Dec 31, 2021 | 23.39 Mn |
| Sep 30, 2021 | 22.32 Mn |
Stabilis Solutions 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=SLNG&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "SLNG", "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=SLNG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();