Cintas (CTAS) Operating Expenses (2009 - 2026)
Cintas (CTAS) recorded Operating Expenses of $841.66 million in fiscal Q1 2027 (quarter ended Aug 31, 2026), up 12.4% from $748.7 million a year earlier and up 6.3% from the prior quarter.
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Analysis
Cintas (CTAS) Operating Expenses (2009 - 2026) Analysis & Trends
On a TTM basis, Cintas' Operating Expenses came in at $3.18 billion as of Aug 31, 2026, up 10.7% year-over-year; for FY2026 (ended May 31, 2026), it came in at $3.1 billion, up 10.2% from FY2025.
- Annual Operating Expenses has increased for five straight fiscal years, with a five-year compound annual growth rate of 10.0% (FY2021 to FY2026).
- Across earlier fiscal years, Operating Expenses came in at $2.81 billion in FY2025 (+7.5%), $2.62 billion in FY2024 (+10.4%), $2.37 billion in FY2023 (+15.9%) and $2.04 billion in FY2022 (+6.0%).
- The fiscal Q1 2027 figure is the highest quarterly Operating Expenses in data going back to fiscal Q1 2010.
- On a year-over-year basis, Operating Expenses has increased for 22 consecutive quarters, with growth averaging 9.2% over the last eight quarters.
- The year-over-year growth in Operating Expenses has ranged between 1.6% (fiscal Q3 2022) and 19.7% (fiscal Q3 2023) over the last five years.
- Per Business Quant, the preceding three fiscal quarters came in at $792.12 million (Q4 2026), $788.55 million (Q3 2026) and $756.77 million (Q2 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Accenture | 147.80 Bn | 107.08 Bn | 6.13 Bn | 15.54 Bn |
| 2 | Cintas | 88.17 Bn | 87.25 Bn | 1.55 Bn | 841.66 Mn |
| 3 | Iron Mountain | 34.25 Bn | 33.44 Bn | 1.07 Bn | 1.66 Bn |
| 4 | APi | 17.39 Bn | 14.43 Bn | 703.00 Mn | 528.00 Mn |
| 5 | Rollins | 16.15 Bn | 15.70 Bn | 569.95 Mn | 877.22 Mn |
| 6 | UL Solutions | 14.99 Bn | 13.75 Bn | 417.00 Mn | 267.00 Mn |
| 7 | Aramark | 14.70 Bn | 12.64 Bn | 430.34 Mn | 4.84 Bn |
| 8 | Gartner | 14.61 Bn | 8.30 Bn | 1.19 Bn | 1.30 Bn |
| 9 | Rentokil Initial | 10.62 Bn | 4.14 Bn | - | - |
| 10 | Tetra Tech | 9.05 Bn | 8.16 Bn | 243.21 Mn | 5.70 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Aug 31, 2026 | 841.66 Mn |
| May 31, 2026 | 792.12 Mn |
| Feb 28, 2026 | 788.55 Mn |
| Nov 30, 2025 | 756.77 Mn |
| Aug 31, 2025 | 748.70 Mn |
| May 31, 2025 | 728.54 Mn |
| Feb 28, 2025 | 709.49 Mn |
| Nov 30, 2024 | 685.31 Mn |
| Aug 31, 2024 | 691.10 Mn |
| May 31, 2024 | 667.86 Mn |
| Feb 29, 2024 | 667.05 Mn |
| Nov 30, 2023 | 641.87 Mn |
| Aug 31, 2023 | 641.02 Mn |
| May 31, 2023 | 617.98 Mn |
| Feb 28, 2023 | 587.22 Mn |
| Nov 30, 2022 | 577.51 Mn |
| Aug 31, 2022 | 587.99 Mn |
| May 31, 2022 | 541.76 Mn |
| Feb 28, 2022 | 490.55 Mn |
| Nov 30, 2021 | 503.91 Mn |
API Access
Cintas 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=CTAS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "CTAS", "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=CTAS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();