Bloom Energy (BE) Operating Expenses (2017 - 2026)
Bloom Energy's Operating Expenses came in at $173.34 million for Q2 2026, up 56.7% from $110.63 million a year earlier and up 13.0% from the prior quarter.
Bloom Energy (BE) Operating Expenses (2017 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Bloom Energy reported Operating Expenses of $622.88 million, up 47.8% year-over-year; for FY2025, it was $514.6 million, up 34.8% from FY2024.
- Operating Expenses carries a five-year compound annual growth rate of 15.9% (FY2020 to FY2025).
- Going back by year, Operating Expenses was $381.74 million in FY2024 (-6.1%), $406.7 million in FY2023 (-0.6%), $409.28 million in FY2022 (+31.1%) and $312.08 million in FY2021 (+26.6%).
- The Q2 2026 figure represents the highest quarterly Operating Expenses in data going back to Q1 2017.
- Year-over-year, Operating Expenses has increased for seven consecutive quarters, with growth averaging 34.1% over the last eight quarters.
- The fastest year-over-year change in Operating Expenses over five years came in Q3 2025 (growth of 62.7%), and the weakest in Q4 2023 (a decline of 29.0%).
- Business Quant data shows BE's Operating Expenses at $153.35 million (Q1 2026), $152.37 million (Q4 2025) and $143.83 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | GE Vernova | 256.40 Bn | 217.48 Bn | 2.36 Bn | 1.71 Bn |
| 2 | Bloom Energy | 85.45 Bn | 77.27 Bn | 355.57 Mn | 173.34 Mn |
| 3 | First Solar | 19.01 Bn | 9.97 Bn | 605.00 Mn | 154.62 Mn |
| 4 | BWX Technologies | 12.64 Bn | 10.94 Bn | 202.31 Mn | 811.92 Mn |
| 5 | Generac Holdings | 12.53 Bn | 11.36 Bn | 521.81 Mn | 311.38 Mn |
| 6 | Nextpower | 12.03 Bn | 7.92 Bn | 335.85 Mn | 144.95 Mn |
| 7 | EnerSys | 6.62 Bn | 4.81 Bn | 313.36 Mn | 151.24 Mn |
| 8 | Enphase Energy | 4.21 Bn | -653.40 Mn | 175.01 Mn | 123.50 Mn |
| 9 | Mirion Technologies | 3.51 Bn | 1.39 Bn | 133.10 Mn | 115.20 Mn |
| 10 | Nuscale Power | 3.18 Bn | 3.14 Bn | -152,000.00 | 45.30 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 173.34 Mn |
| Mar 31, 2026 | 153.35 Mn |
| Dec 31, 2025 | 152.37 Mn |
| Sep 30, 2025 | 143.83 Mn |
| Jun 30, 2025 | 110.63 Mn |
| Mar 31, 2025 | 107.78 Mn |
| Dec 31, 2024 | 114.61 Mn |
| Sep 30, 2024 | 88.39 Mn |
| Jun 30, 2024 | 91.65 Mn |
| Mar 31, 2024 | 87.09 Mn |
| Dec 31, 2023 | 79.45 Mn |
| Sep 30, 2023 | 98.49 Mn |
| Jun 30, 2023 | 110.81 Mn |
| Mar 31, 2023 | 117.95 Mn |
| Dec 31, 2022 | 111.95 Mn |
| Sep 30, 2022 | 103.54 Mn |
| Jun 30, 2022 | 100.20 Mn |
| Mar 31, 2022 | 93.60 Mn |
| Dec 31, 2021 | 82.21 Mn |
| Sep 30, 2021 | 80.77 Mn |
Bloom Energy 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=BE&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "BE", "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=BE&period=max&api_key=YOUR_API_KEY");
const data = await res.json();