GXO Logistics (GXO) Operating Expenses (2020 - 2026)
GXO Logistics' Operating Expenses was $389 million in Q2 2026, up 9.9% from $354 million a year earlier and up 1.0% from the prior quarter.
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Analysis
GXO Logistics (GXO) Operating Expenses (2020 - 2026) Analysis & Trends
On a trailing twelve-month basis, GXO Logistics' Operating Expenses was $1.53 billion through Jun 30, 2026, up 8.0% year-over-year; for FY2025, it came in at $1.47 billion, up 5.6% from FY2024.
- Operating Expenses has now increased for six consecutive years, with a five-year compound annual growth rate of 18.1% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $1.39 billion in FY2024 (+6.1%), $1.31 billion in FY2023 (+11.4%), $1.18 billion in FY2022 (+64.2%) and $718 million in FY2021 (+12.2%).
- The Q2 2026 figure marks the highest quarterly Operating Expenses in data going back to Q2 2020.
- Compared with a year earlier, Operating Expenses has increased for ten straight quarters, with growth averaging 15.8% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q4 2024 (growth of 55.0%); the worst was Q4 2023 (a decline of 13.5%).
- Per Business Quant data, GXO's Operating Expenses in the three quarters before Q2 2026 was $385 million (Q1 2026), $384 million (Q4 2025) and $375 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Union Pacific | 170.50 Bn | 165.03 Bn | - | 4.10 Bn |
| 2 | Csx | 88.86 Bn | 85.07 Bn | - | 2.43 Bn |
| 3 | United Parcel Service | 82.91 Bn | 59.81 Bn | - | 21.90 Bn |
| 4 | Canadian Pacific Kansas City | 76.79 Bn | 75.81 Bn | - | 1.95 Bn |
| 5 | Norfolk Southern | 72.78 Bn | 67.42 Bn | - | 2.34 Bn |
| 6 | Fedex | 69.54 Bn | 35.48 Bn | - | 23.46 Bn |
| 7 | Delta Air Lines | 48.82 Bn | 31.01 Bn | - | 18.73 Bn |
| 8 | Old Dominion Freight Line | 38.83 Bn | 38.10 Bn | - | 1.09 Bn |
| 9 | United Airlines Holdings | 31.02 Bn | -25.36 Bn | - | 16.58 Bn |
| 10 | GXO Logistics | 5.46 Bn | 2.71 Bn | 508.00 Mn | 389.00 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 389.00 Mn |
| Mar 31, 2026 | 385.00 Mn |
| Dec 31, 2025 | 384.00 Mn |
| Sep 30, 2025 | 375.00 Mn |
| Jun 30, 2025 | 354.00 Mn |
| Mar 31, 2025 | 358.00 Mn |
| Dec 31, 2024 | 358.00 Mn |
| Sep 30, 2024 | 349.00 Mn |
| Jun 30, 2024 | 348.00 Mn |
| Mar 31, 2024 | 338.00 Mn |
| Dec 31, 2023 | 231.00 Mn |
| Sep 30, 2023 | 265.00 Mn |
| Jun 30, 2023 | 248.00 Mn |
| Mar 31, 2023 | 279.00 Mn |
| Dec 31, 2022 | 267.00 Mn |
| Sep 30, 2022 | 227.00 Mn |
| Jun 30, 2022 | 221.00 Mn |
| Mar 31, 2022 | 203.00 Mn |
| Dec 31, 2021 | 194.00 Mn |
| Sep 30, 2021 | 173.00 Mn |
API Access
GXO Logistics 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=GXO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "GXO", "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=GXO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();