Winmark (WINA) Operating Expenses (2010 - 2026)
Winmark (WINA) posted Operating Expenses of $7.51 million for Q2 2026, up 13.9% from $6.59 million a year earlier but down 4.6% from the prior quarter.
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Analysis
Winmark (WINA) Operating Expenses (2010 - 2026) Analysis & Trends
For the trailing twelve months through Jun 27, 2026, Operating Expenses at Winmark was $29.71 million, up 14.7% year-over-year; for FY2025, it came in at $28.36 million, up 13.7% from FY2024.
- Annual Operating Expenses shows a five-year compound annual growth rate of 6.0% (FY2020 to FY2025).
- In prior years, Winmark's Operating Expenses was $24.94 million in FY2024 (-0.7%), $25.11 million in FY2023 (+8.4%), $23.16 million in FY2022 (+3.9%) and $22.3 million in FY2021 (+5.2%).
- Quarterly Operating Expenses has run from a low of $5.38 million in Q3 2021 to a high of $7.87 million in Q1 2026 over five years.
- On a year-over-year basis, Operating Expenses has increased in each of the last six quarters, with growth averaging 7.9% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q4 2025, with growth of 22.2%; the weakest was Q4 2024, with a decline of 7.0%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $7.87 million (Q1 2026), $7.29 million (Q4 2025) and $7.05 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,842.80 Bn | 2,359.50 Bn | 104.83 Bn | 173.15 Bn |
| 2 | Home Depot | 312.39 Bn | 305.63 Bn | 16.12 Bn | 9.28 Bn |
| 3 | Tjx Companies | 161.60 Bn | 139.15 Bn | 5.07 Bn | 3.09 Bn |
| 4 | Lowes Companies | 109.80 Bn | 102.76 Bn | 8.58 Bn | 4.46 Bn |
| 5 | Ross Stores | 75.21 Bn | 58.14 Bn | 2.12 Bn | 1.02 Bn |
| 6 | O Reilly Automotive | 73.40 Bn | 72.49 Bn | 2.52 Bn | 1.53 Bn |
| 7 | Target | 69.95 Bn | 64.53 Bn | 8.94 Bn | 5.73 Bn |
| 8 | Autozone | 51.83 Bn | 50.74 Bn | 2.52 Bn | 1.60 Bn |
| 9 | Carvana | 43.36 Bn | 33.85 Bn | 1.38 Bn | 704.00 Mn |
| 10 | Winmark | 1.04 Bn | 954.90 Mn | 19.32 Mn | 7.33 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 26, 2026 | 7.33 Mn |
| Jun 27, 2026 | 7.51 Mn |
| Mar 28, 2026 | 7.87 Mn |
| Dec 27, 2025 | 7.29 Mn |
| Sep 27, 2025 | 7.05 Mn |
| Jun 28, 2025 | 6.59 Mn |
| Mar 29, 2025 | 7.43 Mn |
| Dec 28, 2024 | 5.97 Mn |
| Sep 28, 2024 | 5.92 Mn |
| Jun 29, 2024 | 6.24 Mn |
| Mar 30, 2024 | 6.82 Mn |
| Dec 30, 2023 | 6.41 Mn |
| Sep 30, 2023 | 6.25 Mn |
| Jul 1, 2023 | 5.81 Mn |
| Apr 1, 2023 | 6.64 Mn |
| Dec 31, 2022 | 6.49 Mn |
| Sep 24, 2022 | 5.67 Mn |
| Jun 25, 2022 | 5.46 Mn |
| Mar 26, 2022 | 5.54 Mn |
| Dec 25, 2021 | 6.01 Mn |
API Access
Winmark 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=WINA&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "WINA", "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=WINA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();