G Willi Food International (WILCF) Operating Expenses (2010 - 2026)
G Willi Food International (WILCF) recorded Operating Expenses of $2.94 million in the quarter ended Jun 30, 2026, up 24.1% from $2.37 million a year earlier and up 15.8% from the prior quarter.
G Willi Food International (WILCF) Operating Expenses (2010 - 2026) Analysis & Trends
On a TTM basis, G Willi Food International's Operating Expenses came in at $9.74 million as of Jun 30, 2026, up 5.9% year-over-year; for the year ended Dec 31, 2025, it came in at -$31,000.
- Across earlier years, Operating Expenses came in at $3.13 million in the year ended Dec 31, 2024 (-88.7%), $27.63 million in the year ended Dec 31, 2023 (+2.3%), $27.02 million in the year ended Dec 31, 2022 (+6.9%) and $25.27 million in the year ended Dec 31, 2021 (-10.5%).
- The figure for the quarter ended Jun 30, 2026 is the highest quarterly Operating Expenses since the quarter ended Mar 31, 2024.
- On a year-over-year basis, Operating Expenses has increased for three consecutive quarters, with an average decline of 19.5% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 24.1% in the quarter ended Jun 30, 2026, against a decline of 70.7% in the quarter ended Dec 31, 2024 at the low end.
- Per Business Quant, the preceding three quarters came in at $2.54 million (quarter ended Mar 31, 2026), $2.64 million (quarter ended Dec 31, 2025) and $1.62 million (quarter ended Sep 30, 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Walmart | 936.41 Bn | 892.84 Bn | 49.13 Bn | 39.75 Bn |
| 2 | Costco Wholesale | 440.73 Bn | 364.01 Bn | 12.19 Bn | 8.39 Bn |
| 3 | Sysco | 39.69 Bn | 33.94 Bn | 4.13 Bn | 3.15 Bn |
| 4 | Kroger | 38.21 Bn | 24.36 Bn | 7.86 Bn | 198.00 Mn |
| 5 | Dollar General | 29.54 Bn | 24.22 Bn | 3.68 Bn | 2.91 Bn |
| 6 | Caseys General Stores | 25.34 Bn | 23.33 Bn | 1.24 Bn | 754.11 Mn |
| 7 | Dollar Tree | 23.81 Bn | 20.43 Bn | 2.10 Bn | 1.43 Bn |
| 8 | US Foods Holding | 22.49 Bn | 22.29 Bn | 1.92 Bn | 1.48 Bn |
| 9 | Tractor Supply | 17.20 Bn | 16.37 Bn | 1.68 Bn | 1.02 Bn |
| 10 | G Willi Food International | 345.02 Mn | 182.02 Mn | 18.94 Mn | 2.94 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 2.94 Mn |
| Mar 31, 2026 | 2.54 Mn |
| Dec 31, 2025 | 2.64 Mn |
| Sep 30, 2025 | 1.62 Mn |
| Jun 30, 2025 | 2.37 Mn |
| Mar 31, 2025 | 2.39 Mn |
| Dec 31, 2024 | 1.30 Mn |
| Sep 30, 2024 | 2.11 Mn |
| Jun 30, 2024 | 2.00 Mn |
| Mar 31, 2024 | 6.26 Mn |
| Dec 31, 2023 | 7.96 Mn |
| Sep 30, 2023 | 5.59 Mn |
| Jun 30, 2023 | 6.74 Mn |
| Mar 31, 2023 | 7.34 Mn |
| Dec 31, 2022 | 8.57 Mn |
| Sep 30, 2022 | 6.01 Mn |
| Jun 30, 2022 | 6.41 Mn |
| Mar 31, 2022 | 6.86 Mn |
| Sep 30, 2021 | 5.85 Mn |
| Jun 30, 2021 | 6.01 Mn |
G Willi Food International 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=WILCF&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "WILCF", "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=WILCF&period=max&api_key=YOUR_API_KEY");
const data = await res.json();