Fuel Tech (FTEK) Operating Expenses (2010 - 2026)
Fuel Tech (FTEK) recorded Operating Expenses of $8.05 million in Q2 2026, up 17.2% from $6.87 million a year earlier and up 4.9% from the prior quarter.
Fuel Tech (FTEK) Operating Expenses (2010 - 2026) Analysis & Trends
On a TTM basis, Fuel Tech's Operating Expenses came in at $31.88 million as of Jun 30, 2026, up 7.6% year-over-year; for FY2025, it came in at $30.36 million, up 1.8% from FY2024.
- Annual Operating Expenses has increased for four straight years, with a five-year compound annual growth rate of 2.5% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $29.84 million in FY2024 (+0.3%), $29.74 million in FY2023 (+4.5%), $28.47 million in FY2022 (+10.6%) and $25.75 million in FY2021 (-4.2%).
- Quarterly Operating Expenses has ranged from $6.52 million in Q1 2022 to $8.67 million in Q4 2025 over the past five years.
- On a year-over-year basis, Operating Expenses has increased for three consecutive quarters, with growth averaging 4.6% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 22.1% in Q3 2021, against a decline of 16.3% in Q1 2024 at the low end.
- Per Business Quant, the preceding three quarters came in at $7.68 million (Q1 2026), $8.67 million (Q4 2025) and $7.49 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Ecolab | 77.03 Bn | 68.81 Bn | 1.95 Bn | 1.14 Bn |
| 2 | Xylem | 23.64 Bn | 19.13 Bn | 963.00 Mn | 573.00 Mn |
| 3 | Veralto | 23.04 Bn | 15.69 Bn | 902.00 Mn | 587.00 Mn |
| 4 | Badger Meter | 3.58 Bn | 2.86 Bn | 90.77 Mn | 51.40 Mn |
| 5 | Ceco Environmental | 3.02 Bn | 2.85 Bn | 86.47 Mn | 109.35 Mn |
| 6 | NWPX Infrastructure | 993.21 Mn | 954.68 Mn | 34.36 Mn | 13.21 Mn |
| 7 | Energy Recovery | 341.34 Mn | 16.50 Mn | 8.96 Mn | 14.84 Mn |
| 8 | Cadiz | 329.91 Mn | 298.36 Mn | -24,000.00 | 9.81 Mn |
| 9 | AirJoule Technologies | 286.05 Mn | 165.68 Mn | - | 5.04 Mn |
| 10 | Fuel Tech | 50.57 Mn | -41.36 Mn | 2.68 Mn | 8.05 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 8.05 Mn |
| Mar 31, 2026 | 7.68 Mn |
| Dec 31, 2025 | 8.67 Mn |
| Sep 30, 2025 | 7.49 Mn |
| Jun 30, 2025 | 6.87 Mn |
| Mar 31, 2025 | 7.33 Mn |
| Dec 31, 2024 | 7.40 Mn |
| Sep 30, 2024 | 8.03 Mn |
| Jun 30, 2024 | 7.76 Mn |
| Mar 31, 2024 | 6.65 Mn |
| Dec 31, 2023 | 7.15 Mn |
| Sep 30, 2023 | 7.86 Mn |
| Jun 30, 2023 | 6.79 Mn |
| Mar 31, 2023 | 7.95 Mn |
| Dec 31, 2022 | 7.27 Mn |
| Sep 30, 2022 | 7.83 Mn |
| Jun 30, 2022 | 6.85 Mn |
| Mar 31, 2022 | 6.52 Mn |
| Dec 31, 2021 | 6.67 Mn |
| Sep 30, 2021 | 6.98 Mn |
Fuel Tech 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=FTEK&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "FTEK", "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=FTEK&period=max&api_key=YOUR_API_KEY");
const data = await res.json();