SurgePays (SURG) Operating Expenses (2010 - 2026)
SurgePays (SURG) posted Operating Expenses of $21.26 million for Q2 2026, up 16.0% from $18.33 million a year earlier but down 21.8% from the prior quarter.
SurgePays (SURG) Operating Expenses (2010 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at SurgePays was $103.06 million, up 21.0% year-over-year; for FY2025, it was $91.1 million, down 12.7% from FY2024.
- Annual Operating Expenses has declined for three consecutive years, though with a five-year compound annual growth rate of 7.1% (FY2020 to FY2025).
- In prior years, SurgePays' Operating Expenses was $104.35 million in FY2024 (-11.8%), $118.28 million in FY2023 (-2.2%), $120.91 million in FY2022 (+111.9%) and $57.05 million in FY2021 (-11.6%).
- Quarterly Operating Expenses has run from a low of $14.25 million in Q4 2021 to a high of $37.18 million in Q3 2022 over five years.
- On a year-over-year basis, Operating Expenses increased in three of the last eight quarters, with an average decline of 0.7%.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q3 2022, with growth of 139.2%; the weakest was Q1 2025, with a decline of 38.8%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $27.18 million (Q1 2026), $28.98 million (Q4 2025) and $25.63 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Verizon Communications | 191.08 Bn | 155.48 Bn | 27.03 Bn | 27.07 Bn |
| 2 | T-Mobile US | 175.17 Bn | 159.92 Bn | 14.76 Bn | 17.30 Bn |
| 3 | At&T | 167.81 Bn | 115.76 Bn | 25.82 Bn | 24.52 Bn |
| 4 | Grupo Televisa, S.A.B | 146.22 Bn | 134.85 Bn | 318.12 Mn | -117.85 Mn |
| 5 | Comcast | 76.40 Bn | 40.65 Bn | - | 24.78 Bn |
| 6 | Chunghwa Telecom | 35.35 Bn | 31.20 Bn | 728.80 Mn | 309.31 Mn |
| 7 | EchoStar | 26.08 Bn | 17.22 Bn | 1.65 Bn | 3.06 Bn |
| 8 | AST SpaceMobile | 23.11 Bn | 23.62 Bn | 7.95 Mn | 329.10 Mn |
| 9 | Bce | 18.79 Bn | 17.12 Bn | - | -2.51 Bn |
| 10 | SurgePays | 3.98 Mn | -5.40 Mn | -425,171.00 | 21.26 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 21.26 Mn |
| Mar 31, 2026 | 27.18 Mn |
| Dec 31, 2025 | 28.98 Mn |
| Sep 30, 2025 | 25.63 Mn |
| Jun 30, 2025 | 18.33 Mn |
| Mar 31, 2025 | 18.16 Mn |
| Dec 31, 2024 | 29.66 Mn |
| Sep 30, 2024 | 19.05 Mn |
| Jun 30, 2024 | 25.96 Mn |
| Mar 31, 2024 | 29.68 Mn |
| Dec 31, 2023 | 31.45 Mn |
| Sep 30, 2023 | 27.07 Mn |
| Jun 30, 2023 | 29.68 Mn |
| Mar 31, 2023 | 30.07 Mn |
| Dec 31, 2022 | 32.68 Mn |
| Sep 30, 2022 | 37.18 Mn |
| Jun 30, 2022 | 28.85 Mn |
| Mar 31, 2022 | 22.19 Mn |
| Dec 31, 2021 | 14.25 Mn |
| Sep 30, 2021 | 15.54 Mn |
SurgePays 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=SURG&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "SURG", "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=SURG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();