Walmart (WMT) Operating Expenses (2009 - 2026)
Walmart's Operating Expenses was $39.75 billion in fiscal Q2 2027 (quarter ended Jul 31, 2026), up 6.4% from $37.35 billion a year earlier and up 6.9% from the prior quarter.
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Analysis
Walmart (WMT) Operating Expenses (2009 - 2026) Analysis & Trends
On a trailing twelve-month basis, Walmart's Operating Expenses was $153.38 billion through Jul 31, 2026, up 6.8% year-over-year; for FY2026 (ended Jan 31, 2026), it came in at $147.94 billion, up 5.8% from FY2025.
- Operating Expenses has now increased for 17 consecutive fiscal years, with a five-year compound annual growth rate of 4.9% (FY2021 to FY2026).
- In earlier fiscal years, Operating Expenses was $139.88 billion in FY2025 (+6.8%), $130.97 billion in FY2024 (+3.0%), $127.14 billion in FY2023 (+7.9%) and $117.81 billion in FY2022 (+1.3%).
- The fiscal Q2 2027 figure marks the highest quarterly Operating Expenses in data going back to fiscal Q4 2009.
- Compared with a year earlier, Operating Expenses has increased for 11 straight quarters, with growth averaging 6.4% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was fiscal Q3 2023 (growth of 16.1%); the worst was fiscal Q3 2024 (a decline of 3.1%).
- Per Business Quant data, WMT's Operating Expenses in the three fiscal quarters before Q2 2027 was $37.2 billion (Q1 2027), $38.33 billion (Q4 2026) and $38.09 billion (Q3 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Walmart | 862.64 Bn | 825.34 Bn | 49.13 Bn | 39.75 Bn |
| 2 | Costco Wholesale | 409.33 Bn | 338.62 Bn | 9.01 Bn | 6.19 Bn |
| 3 | Sysco | 37.65 Bn | 31.90 Bn | 4.13 Bn | 3.15 Bn |
| 4 | Kroger | 35.26 Bn | 21.42 Bn | 7.86 Bn | 198.00 Mn |
| 5 | Dollar General | 27.43 Bn | 22.11 Bn | 3.68 Bn | 2.91 Bn |
| 6 | Caseys General Stores | 22.41 Bn | 20.40 Bn | 1.24 Bn | 754.11 Mn |
| 7 | Dollar Tree | 21.77 Bn | 18.40 Bn | 2.10 Bn | 1.43 Bn |
| 8 | US Foods Holding | 20.27 Bn | 20.06 Bn | 1.92 Bn | 1.48 Bn |
| 9 | Tractor Supply | 16.74 Bn | 15.90 Bn | 1.68 Bn | 1.02 Bn |
| 10 | Performance Food | 14.36 Bn | 14.14 Bn | 2.17 Bn | 1.85 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | 39.75 Bn |
| Apr 30, 2026 | 37.20 Bn |
| Jan 31, 2026 | 38.33 Bn |
| Oct 31, 2025 | 38.09 Bn |
| Jul 31, 2025 | 37.35 Bn |
| Apr 30, 2025 | 34.17 Bn |
| Jan 31, 2025 | 36.52 Bn |
| Oct 31, 2024 | 35.54 Bn |
| Jul 31, 2024 | 34.59 Bn |
| Apr 30, 2024 | 33.24 Bn |
| Jan 31, 2024 | 34.31 Bn |
| Oct 31, 2023 | 33.42 Bn |
| Jul 31, 2023 | 32.47 Bn |
| Apr 30, 2023 | 30.78 Bn |
| Jan 31, 2023 | 33.06 Bn |
| Oct 31, 2022 | 34.51 Bn |
| Jul 31, 2022 | 30.17 Bn |
| Apr 30, 2022 | 29.40 Bn |
| Jan 31, 2022 | 31.46 Bn |
| Oct 31, 2021 | 29.71 Bn |
API Access
Walmart 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=WMT&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "WMT", "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=WMT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();