Mettler Toledo International (MTD) Operating Expenses (2009 - 2026)
Mettler Toledo International's Operating Expenses came in at $321.77 million for Q2 2026, up 7.2% from $300.14 million a year earlier and up 1.5% from the prior quarter.
Mettler Toledo International (MTD) Operating Expenses (2009 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Mettler Toledo International reported Operating Expenses of $1.26 billion, up 8.6% year-over-year; for FY2025, it was $1.22 billion, up 6.1% from FY2024.
- Operating Expenses carries a five-year compound annual growth rate of 4.6% (FY2020 to FY2025).
- Going back by year, Operating Expenses was $1.15 billion in FY2024 (+2.1%), $1.12 billion in FY2023 (-0.3%), $1.13 billion in FY2022 (+0.6%) and $1.12 billion in FY2021 (+15.3%).
- The Q2 2026 figure represents the highest quarterly Operating Expenses in data going back to Q2 2009.
- Year-over-year, Operating Expenses has increased for 11 consecutive quarters, with growth averaging 5.6% over the last eight quarters.
- The fastest year-over-year change in Operating Expenses over five years came in Q3 2021 (growth of 16.1%), and the weakest in Q4 2022 (a decline of 5.3%).
- Business Quant data shows MTD's Operating Expenses at $316.87 million (Q1 2026), $317 million (Q4 2025) and $305.51 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Caterpillar | 367.91 Bn | 339.61 Bn | 7.76 Bn | 16.25 Bn |
| 2 | Amphenol | 215.11 Bn | 209.81 Bn | 3.55 Bn | 963.40 Mn |
| 3 | Deere | 167.41 Bn | 176.17 Bn | 4.66 Bn | 10.73 Bn |
| 4 | Eaton | 166.85 Bn | 164.08 Bn | 2.86 Bn | 1.46 Bn |
| 5 | Parker-Hannifin | 121.33 Bn | 119.46 Bn | 2.25 Bn | 874.00 Mn |
| 6 | Vertiv Holdings | 93.43 Bn | 84.05 Bn | 1.23 Bn | 490.50 Mn |
| 7 | Emerson Electric | 90.26 Bn | 83.02 Bn | 2.66 Bn | 1.34 Bn |
| 8 | 3M | 82.47 Bn | 63.93 Bn | 2.68 Bn | 5.52 Bn |
| 9 | Illinois Tool Works | 75.21 Bn | 71.77 Bn | 1.90 Bn | - |
| 10 | Mettler Toledo International | 33.63 Bn | 33.39 Bn | 650.22 Mn | 321.77 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 321.77 Mn |
| Mar 31, 2026 | 316.87 Mn |
| Dec 31, 2025 | 317.00 Mn |
| Sep 30, 2025 | 305.51 Mn |
| Jun 30, 2025 | 300.14 Mn |
| Mar 31, 2025 | 292.91 Mn |
| Dec 31, 2024 | 289.54 Mn |
| Sep 30, 2024 | 278.53 Mn |
| Jun 30, 2024 | 286.90 Mn |
| Mar 31, 2024 | 290.47 Mn |
| Dec 31, 2023 | 282.92 Mn |
| Sep 30, 2023 | 270.96 Mn |
| Jun 30, 2023 | 283.86 Mn |
| Mar 31, 2023 | 284.39 Mn |
| Dec 31, 2022 | 275.28 Mn |
| Sep 30, 2022 | 279.51 Mn |
| Jun 30, 2022 | 288.00 Mn |
| Mar 31, 2022 | 282.35 Mn |
| Dec 31, 2021 | 290.58 Mn |
| Sep 30, 2021 | 283.66 Mn |
Mettler Toledo International 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=MTD&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "MTD", "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=MTD&period=max&api_key=YOUR_API_KEY");
const data = await res.json();