Merit Medical Systems (MMSI) Operating Expenses (2010 - 2026)
Merit Medical Systems' Operating Expenses was $154.76 million in Q2 2026, up 12.5% from $137.61 million a year earlier and up 10.0% from the prior quarter.
Merit Medical Systems (MMSI) Operating Expenses (2010 - 2026) Analysis & Trends
On a trailing twelve-month basis, Merit Medical Systems' Operating Expenses was $580.36 million through Jun 30, 2026, up 10.5% year-over-year; for FY2025, it came in at $553.55 million, up 13.5% from FY2024.
- Operating Expenses has now increased for five consecutive years, with a five-year compound annual growth rate of 6.6% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $487.64 million in FY2024 (+6.0%), $459.93 million in FY2023 (+6.6%), $431.54 million in FY2022 (+1.7%) and $424.42 million in FY2021 (+5.4%).
- The Q2 2026 figure marks the highest quarterly Operating Expenses in data going back to Q2 2010.
- Compared with a year earlier, Operating Expenses has increased for eight straight quarters, with growth averaging 13.1% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q3 2025 (growth of 19.6%); the worst was Q2 2024 (a decline of 7.1%).
- Per Business Quant data, MMSI's Operating Expenses in the three quarters before Q2 2026 was $140.64 million (Q1 2026), $141.16 million (Q4 2025) and $143.8 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 251.30 Bn | 230.45 Bn | 4.88 Bn | 9.91 Bn |
| 2 | Abbott Laboratories | 174.70 Bn | 145.78 Bn | 7.27 Bn | 10.90 Bn |
| 3 | Danaher | 158.94 Bn | 142.76 Bn | 3.61 Bn | 2.48 Bn |
| 4 | Intuitive Surgical | 145.87 Bn | 125.42 Bn | 1.96 Bn | 988.50 Mn |
| 5 | Medtronic | 111.49 Bn | 77.36 Bn | 6.34 Bn | 4.06 Bn |
| 6 | Stryker | 106.96 Bn | 93.08 Bn | 4.50 Bn | 2.84 Bn |
| 7 | Boston Scientific | 63.62 Bn | 58.63 Bn | 3.85 Bn | 2.67 Bn |
| 8 | Edwards Lifesciences | 50.80 Bn | 34.92 Bn | 1.35 Bn | 840.10 Mn |
| 9 | Becton Dickinson | 49.59 Bn | 46.74 Bn | 2.32 Bn | 4.32 Bn |
| 10 | Merit Medical Systems | 5.25 Bn | 3.47 Bn | 215.17 Mn | 154.76 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 154.76 Mn |
| Mar 31, 2026 | 140.64 Mn |
| Dec 31, 2025 | 141.16 Mn |
| Sep 30, 2025 | 143.80 Mn |
| Jun 30, 2025 | 137.61 Mn |
| Mar 31, 2025 | 130.99 Mn |
| Dec 31, 2024 | 136.42 Mn |
| Sep 30, 2024 | 120.27 Mn |
| Jun 30, 2024 | 115.15 Mn |
| Mar 31, 2024 | 115.79 Mn |
| Dec 31, 2023 | 116.92 Mn |
| Sep 30, 2023 | 107.06 Mn |
| Jun 30, 2023 | 123.97 Mn |
| Mar 31, 2023 | 111.98 Mn |
| Dec 31, 2022 | 104.14 Mn |
| Sep 30, 2022 | 109.92 Mn |
| Jun 30, 2022 | 111.81 Mn |
| Mar 31, 2022 | 105.67 Mn |
| Dec 31, 2021 | 106.91 Mn |
| Sep 30, 2021 | 104.56 Mn |
Merit Medical Systems 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=MMSI&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "MMSI", "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=MMSI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();