Cintas (CTAS) Accumulated Expenses (2010 - 2026)
Cintas' (CTAS) quarterly Accumulated Expenses came in at $889.2 million in Q2 2026, up 1.61% year-over-year from $875.1 million in Q2 2025, and up 7.0% quarter-over-quarter from $831.0 million in Q1 2026.
Cintas (CTAS) Accumulated Expenses (2010 - 2026) Analysis & Trends
Cintas has disclosed Accumulated Expenses across 17 years of filings, most recently posting $889.2 million for Q2 2026.
- In Q2 2026, Accumulated Expenses rose 1.61% year-over-year to $889.2 million; the TTM figure through May 2026 stood at $889.2 million (up 1.61% YoY), while the FY2026 annual figure was $889.2 million, up 1.61% from the prior year.
- Accumulated Expenses came in at $889.2 million for Q2 2026 at Cintas, up from $831.0 million in the prior quarter.
- In the past five years, Accumulated Expenses ranged from a high of $889.2 million in Q2 2026 to a low of $543.6 million in Q3 2022.
- Average Accumulated Expenses over 5 years is $706.5 million, with a median of $718.8 million recorded in 2024.
- Year-over-year, Accumulated Expenses declined 8.24% in 2022 and climbed 21.75% in 2024.
- Over 5 years, Accumulated Expenses stood at $556.2 million in 2022, then grew by 11.34% to $619.3 million in 2023, then advanced by 21.75% to $754.0 million in 2024, then gained by 5.8% to $797.7 million in 2025, then grew by 11.47% to $889.2 million in 2026.
- Per Business Quant data, the three most recent Accumulated Expenses figures were $889.2 million in Q2 2026, $831.0 million in Q1 2026, and $797.7 million in Q4 2025.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Cintas | 79.09 Bn | 78.80 Bn | 1.48 Bn |
| 2 | Iron Mountain | 34.02 Bn | 34.14 Bn | 1.07 Bn |
| 3 | APi | 16.16 Bn | 15.31 Bn | 703.00 Mn |
| 4 | Rollins | 15.61 Bn | 15.50 Bn | 569.95 Mn |
| 5 | Aramark | 14.88 Bn | 14.45 Bn | 430.34 Mn |
| 6 | FirstService | 5.90 Bn | 6.24 Bn | 480.66 Mn |
| 7 | Unifirst | 4.73 Bn | 4.56 Bn | 234.73 Mn |
| 8 | Geo | 4.20 Bn | 3.95 Bn | - |
| 9 | CoreCivic | 3.49 Bn | 3.38 Bn | - |
| 10 | Abm Industries | 2.92 Bn | 2.81 Bn | 286.10 Mn |
Historic Data
| Date | Value |
|---|---|
| May 31, 2026 | 889.20 Mn |
| Feb 28, 2026 | 831.04 Mn |
| Nov 30, 2025 | 797.71 Mn |
| Aug 31, 2025 | 779.67 Mn |
| May 31, 2025 | 875.08 Mn |
| Feb 28, 2025 | 825.03 Mn |
| Nov 30, 2024 | 753.99 Mn |
| Aug 31, 2024 | 717.09 Mn |
| May 31, 2024 | 761.28 Mn |
| Feb 29, 2024 | 720.55 Mn |
| Nov 30, 2023 | 619.29 Mn |
| Aug 31, 2023 | 592.37 Mn |
| May 31, 2023 | 632.50 Mn |
| Feb 28, 2023 | 610.86 Mn |
| Nov 30, 2022 | 556.21 Mn |
| Aug 31, 2022 | 543.57 Mn |
| May 31, 2022 | 588.95 Mn |
| Feb 28, 2022 | 622.80 Mn |
| Nov 30, 2021 | 597.17 Mn |
| Aug 31, 2021 | 592.38 Mn |
Cintas Accumulated 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=accumulated-expenses&ticker=CTAS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-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=accumulated-expenses&ticker=CTAS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();