Marzetti (MZTI) Operating Expenses (2009 - 2026)
Marzetti (MZTI) posted Operating Expenses of $56.3 million for fiscal Q4 2026 (quarter ended Jun 30, 2026), down 16.2% from $67.18 million a year earlier and down 7.2% from the prior quarter.
Powered by 
Analysis
Marzetti (MZTI) Operating Expenses (2009 - 2026) Analysis & Trends
For FY2026 (ended Jun 30, 2026), Marzetti's Operating Expenses came in at $238.58 million, up 1.4% from FY2025.
- Annual Operating Expenses shows a five-year compound annual growth rate of 2.9% (FY2021 to FY2026).
- In prior fiscal years, Marzetti's Operating Expenses was $235.33 million in FY2025 (+1.0%), $232.94 million in FY2024 (-5.7%), $247.06 million in FY2023 (-0.1%) and $247.28 million in FY2022 (+19.7%).
- The fiscal Q4 2026 figure stands as the lowest quarterly Operating Expenses since fiscal Q3 2025.
- On a year-over-year basis, Operating Expenses increased in six of the last eight quarters, with growth averaging 2.3%.
- The strongest year-over-year quarter for Operating Expenses in the past five years was fiscal Q3 2022, with growth of 45.3%; the weakest was fiscal Q4 2024, with a decline of 31.5%.
- According to Business Quant data, Operating Expenses for the three prior fiscal quarters was $60.64 million (Q3 2026), $62.08 million (Q2 2026) and $59.56 million (Q1 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Unilever | 132.43 Bn | 107.80 Bn | - | - |
| 2 | Mondelez International | 73.80 Bn | 67.12 Bn | 3.99 Bn | 2.01 Bn |
| 3 | Hershey | 31.86 Bn | 28.11 Bn | 1.26 Bn | 628.91 Mn |
| 4 | Kraft Heinz | 26.96 Bn | 13.49 Bn | 2.03 Bn | 8.46 Bn |
| 5 | General Mills | 17.20 Bn | 14.85 Bn | 1.49 Bn | 853.60 Mn |
| 6 | J M Smucker | 12.70 Bn | 12.49 Bn | 979.60 Mn | 411.10 Mn |
| 7 | Mccormick | 12.49 Bn | 12.36 Bn | 778.20 Mn | 441.80 Mn |
| 8 | Hormel Foods | 10.97 Bn | 7.66 Bn | 471.52 Mn | 323.50 Mn |
| 9 | Chewy | 7.31 Bn | 4.59 Bn | 1.01 Bn | 919.20 Mn |
| 10 | Marzetti | 2.71 Bn | 2.08 Bn | 113.99 Mn | 56.30 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 56.30 Mn |
| Mar 31, 2026 | 60.64 Mn |
| Dec 31, 2025 | 62.08 Mn |
| Sep 30, 2025 | 59.56 Mn |
| Jun 30, 2025 | 67.18 Mn |
| Mar 31, 2025 | 56.09 Mn |
| Dec 31, 2024 | 57.11 Mn |
| Sep 30, 2024 | 54.96 Mn |
| Jun 30, 2024 | 55.93 Mn |
| Mar 31, 2024 | 69.35 Mn |
| Dec 31, 2023 | 55.71 Mn |
| Sep 30, 2023 | 51.95 Mn |
| Jun 30, 2023 | 81.70 Mn |
| Mar 31, 2023 | 64.83 Mn |
| Dec 31, 2022 | 50.78 Mn |
| Sep 30, 2022 | 49.76 Mn |
| Jun 30, 2022 | 64.71 Mn |
| Mar 31, 2022 | 77.25 Mn |
| Dec 31, 2021 | 53.47 Mn |
| Sep 30, 2021 | 51.86 Mn |
API Access
Marzetti 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=MZTI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "MZTI", "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=MZTI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();