Conmed (CNMD) EBITDA (2010 - 2026)
Conmed (CNMD) recorded EBITDA of $55.45 million in Q2 2026, down 2.3% from $56.73 million a year earlier but up 25.3% from the prior quarter.
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Analysis
Conmed (CNMD) EBITDA (2010 - 2026) Analysis & Trends
On a TTM basis, Conmed's EBITDA came in at $185.66 million as of Jun 30, 2026, down 24.3% year-over-year; for FY2025, it came in at $176.9 million, down 35.0% from FY2024.
- Annual EBITDA has a five-year compound annual growth rate of 8.3% (FY2020 to FY2025).
- Across earlier years, EBITDA came in at $272.18 million in FY2024 (+41.4%), $192.48 million in FY2023 (+37.9%), $139.57 million in FY2022 (-22.7%) and $180.46 million in FY2021 (+52.1%).
- Quarterly EBITDA has ranged from $16.64 million in Q4 2022 to $83.68 million in Q3 2024 over the past five years.
- On a year-over-year basis, EBITDA rose in three of the last eight quarters, with an average decline of 3.6%.
- Peak year-over-year performance for EBITDA in the last five years was growth of 309.7% in Q4 2023, against a decline of 69.6% in Q4 2022 at the low end.
- Per Business Quant, the preceding three quarters came in at $44.25 million (Q1 2026), $55.47 million (Q4 2025) and $30.49 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 251.30 Bn | 230.45 Bn | 4.88 Bn | 2.90 Bn |
| 2 | Abbott Laboratories | 174.70 Bn | 145.78 Bn | 7.27 Bn | 2.75 Bn |
| 3 | Danaher | 158.94 Bn | 142.76 Bn | 3.61 Bn | 1.79 Bn |
| 4 | Intuitive Surgical | 145.87 Bn | 125.42 Bn | 1.96 Bn | 1.19 Bn |
| 5 | Medtronic | 111.49 Bn | 77.36 Bn | 6.34 Bn | 2.49 Bn |
| 6 | Stryker | 106.96 Bn | 93.08 Bn | 4.50 Bn | 1.96 Bn |
| 7 | Boston Scientific | 63.62 Bn | 58.63 Bn | 3.85 Bn | 1.53 Bn |
| 8 | Edwards Lifesciences | 50.80 Bn | 34.92 Bn | 1.35 Bn | 555.90 Mn |
| 9 | Becton Dickinson | 49.59 Bn | 46.74 Bn | 2.32 Bn | 1.23 Bn |
| 10 | Conmed | 1.40 Bn | 1.25 Bn | 197.46 Mn | 55.45 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 55.45 Mn |
| Mar 31, 2026 | 44.25 Mn |
| Dec 31, 2025 | 55.47 Mn |
| Sep 30, 2025 | 30.49 Mn |
| Jun 30, 2025 | 56.73 Mn |
| Mar 31, 2025 | 34.21 Mn |
| Dec 31, 2024 | 70.51 Mn |
| Sep 30, 2024 | 83.68 Mn |
| Jun 30, 2024 | 64.95 Mn |
| Mar 31, 2024 | 53.05 Mn |
| Dec 31, 2023 | 68.19 Mn |
| Sep 30, 2023 | 48.17 Mn |
| Jun 30, 2023 | 45.48 Mn |
| Mar 31, 2023 | 30.63 Mn |
| Dec 31, 2022 | 16.64 Mn |
| Sep 30, 2022 | 41.88 Mn |
| Jun 30, 2022 | 41.78 Mn |
| Mar 31, 2022 | 39.28 Mn |
| Dec 31, 2021 | 54.69 Mn |
| Sep 30, 2021 | 43.92 Mn |
API Access
Conmed EBITDA 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=ebitda&ticker=CNMD&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "ticker": "CNMD", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=ebitda&ticker=CNMD&period=max&api_key=YOUR_API_KEY");
const data = await res.json();