Quanome Technologies (QNME) Operating Expenses (2023 - 2026)
Quanome Technologies' Operating Expenses was $7.34 million in fiscal Q4 2026 (quarter ended Jun 30, 2026), up 579.9% from $1.08 million a year earlier and up 187.0% from the prior quarter.
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Analysis
Quanome Technologies (QNME) Operating Expenses (2023 - 2026) Analysis & Trends
For FY2026 (ended Jun 30, 2026), Operating Expenses at Quanome Technologies came in at $13.51 million, up 344.2% from FY2025.
- Operating Expenses shows a three-year compound annual growth rate of 80.0% (FY2023 to FY2026).
- In earlier fiscal years, Operating Expenses was $3.04 million in FY2025 (-28.3%), $4.24 million in FY2024 (+83.1%) and $2.32 million in FY2023.
- The fiscal Q4 2026 figure marks the highest quarterly Operating Expenses in data going back to fiscal Q1 2024.
- Compared with a year earlier, Operating Expenses has increased for four straight quarters, with growth averaging 135.9% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was fiscal Q4 2026 (growth of 579.9%); the worst was fiscal Q3 2025 (a decline of 24.3%).
- Per Business Quant data, QNME's Operating Expenses in the three fiscal quarters before Q4 2026 was $2.56 million (Q3 2026), $3.4 million (Q2 2026) and $2.38 million (Q1 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Union Pacific | 177.43 Bn | 171.95 Bn | - | 4.10 Bn |
| 2 | Csx | 95.92 Bn | 91.14 Bn | - | 2.45 Bn |
| 3 | United Parcel Service | 85.95 Bn | 62.85 Bn | - | 21.90 Bn |
| 4 | Canadian Pacific Kansas City | 80.52 Bn | 79.54 Bn | - | 1.95 Bn |
| 5 | Norfolk Southern | 75.79 Bn | 70.43 Bn | - | 2.34 Bn |
| 6 | Fedex | 71.86 Bn | 37.80 Bn | - | 23.46 Bn |
| 7 | Delta Air Lines | 51.80 Bn | 33.98 Bn | - | 18.73 Bn |
| 8 | Old Dominion Freight Line | 39.47 Bn | 38.73 Bn | - | 1.09 Bn |
| 9 | United Airlines Holdings | 33.07 Bn | -24.62 Bn | - | 16.43 Bn |
| 10 | Quanome Technologies | 11.19 Mn | 3.04 Mn | 540,115.00 | 7.34 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 7.34 Mn |
| Mar 31, 2026 | 2.56 Mn |
| Dec 31, 2025 | 3.40 Mn |
| Sep 30, 2025 | 2.38 Mn |
| Jun 30, 2025 | 1.08 Mn |
| Mar 31, 2025 | 707,608.00 |
| Dec 31, 2024 | 1.96 Mn |
| Sep 30, 2024 | 1.85 Mn |
| Jun 30, 2024 | 1.34 Mn |
| Mar 31, 2024 | 935,088.00 |
| Dec 31, 2023 | 982,522.00 |
| Sep 30, 2023 | 981,051.00 |
API Access
Quanome Technologies 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=QNME&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "QNME", "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=QNME&period=max&api_key=YOUR_API_KEY");
const data = await res.json();