Sprouts Farmers Market (SFM) Operating Expenses (2012 - 2026)
Sprouts Farmers Market (SFM) posted Operating Expenses of $682.63 million for Q2 2026, up 5.8% from $645.13 million a year earlier and up 3.6% from the prior quarter.
Sprouts Farmers Market (SFM) Operating Expenses (2012 - 2026) Analysis & Trends
For the trailing twelve months through Jun 28, 2026, Operating Expenses at Sprouts Farmers Market was $2.65 billion, up 7.5% year-over-year; for FY2025, it was $2.73 billion, up 12.4% from FY2024.
- Annual Operating Expenses has increased for three consecutive years, with a four-year compound annual growth rate of 8.2% (FY2021 to FY2025).
- In prior years, Sprouts Farmers Market's Operating Expenses was $2.43 billion in FY2024 (+13.7%), $2.14 billion in FY2023 (+7.9%), $1.98 billion in FY2022 and $1.99 billion in FY2021.
- The Q2 2026 figure stands as the highest quarterly Operating Expenses since Q4 2017.
- On a year-over-year basis, Operating Expenses has increased in each of the last ten quarters, with growth averaging 12.1% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q4 2024, with growth of 19.7%; the weakest was Q4 2023, with a decline of 7.7%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $658.78 million (Q1 2026), $653.01 million (Q4 2025) and $653.33 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Walmart | 824.47 Bn | 787.18 Bn | 49.13 Bn | 39.75 Bn |
| 2 | Costco Wholesale | 403.75 Bn | 333.05 Bn | 9.01 Bn | 6.19 Bn |
| 3 | Sysco | 37.36 Bn | 31.61 Bn | 4.13 Bn | 3.15 Bn |
| 4 | Kroger | 34.63 Bn | 20.79 Bn | 7.86 Bn | 198.00 Mn |
| 5 | Dollar General | 26.38 Bn | 21.06 Bn | 3.68 Bn | 2.91 Bn |
| 6 | Caseys General Stores | 22.49 Bn | 20.48 Bn | 1.24 Bn | 754.11 Mn |
| 7 | Dollar Tree | 21.40 Bn | 18.02 Bn | 2.10 Bn | 1.43 Bn |
| 8 | US Foods Holding | 19.94 Bn | 19.74 Bn | 1.92 Bn | 1.48 Bn |
| 9 | Tractor Supply | 16.33 Bn | 15.49 Bn | 1.68 Bn | 1.02 Bn |
| 10 | Sprouts Farmers Market | 6.22 Bn | 5.16 Bn | 900.65 Mn | 682.63 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 28, 2026 | 682.63 Mn |
| Mar 29, 2026 | 658.78 Mn |
| Dec 28, 2025 | 653.01 Mn |
| Sep 28, 2025 | 653.33 Mn |
| Jun 29, 2025 | 645.13 Mn |
| Mar 30, 2025 | 623.23 Mn |
| Dec 29, 2024 | 614.88 Mn |
| Sep 29, 2024 | 580.33 Mn |
| Jun 30, 2024 | 556.37 Mn |
| Mar 31, 2024 | 539.77 Mn |
| Dec 31, 2023 | 513.48 Mn |
| Oct 1, 2023 | 502.80 Mn |
| Jul 2, 2023 | 497.97 Mn |
| Apr 2, 2023 | 486.20 Mn |
| Jan 1, 2023 | 556.15 Mn |
| Oct 2, 2022 | 460.83 Mn |
| Jul 3, 2022 | 462.11 Mn |
| Apr 3, 2022 | 459.91 Mn |
| Oct 3, 2021 | 423.42 Mn |
| Jul 4, 2021 | 436.42 Mn |
Sprouts Farmers Market 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=SFM&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "SFM", "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=SFM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();