InMode (INMD) EV to EBITDA (2019 - 2026)
InMode's (INMD) EV to EBITDA stood at 7.31 in the quarter ended Jun 30, 2026, up 39.5% from 5.24 a year earlier and up 41.8% from the prior quarter.
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Analysis
InMode (INMD) EV to EBITDA (2019 - 2026) Analysis & Trends
On a TTM basis, InMode's EV to EBITDA came in at -10.02 as of Jun 30, 2026; for the year ended Dec 31, 2025, it was 6.33, down 14.0% from the prior year.
- Annual EV to EBITDA has declined for four straight years.
- Across earlier years, EV to EBITDA came in at 7.35 in the year ended Dec 31, 2024 (-3.8%), 7.64 in the year ended Dec 31, 2023 (-45.3%), 13.97 in the year ended Dec 31, 2022 (-59.1%) and 34.13 in the year ended Dec 31, 2021 (+57.8%).
- Quarterly EV to EBITDA has ranged from 5.16 in the quarter ended Mar 31, 2026 to 38.12 in the quarter ended Sep 30, 2021 over the past five years.
- On a year-over-year basis, EV to EBITDA rose in three of the last eight quarters, with an average decline of 8.6%.
- Peak year-over-year performance for EV to EBITDA in the last five years was growth of 113.5% in the quarter ended Sep 30, 2021, against a decline of 72.7% in the quarter ended Sep 30, 2022 at the low end.
- Per Business Quant, the preceding three quarters came in at 5.16 (quarter ended Mar 31, 2026), 6.33 (quarter ended Dec 31, 2025) and 7.53 (quarter ended Sep 30, 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 251.30 Bn | 230.45 Bn | 4.88 Bn |
| 2 | Abbott Laboratories | 174.70 Bn | 145.78 Bn | 7.27 Bn |
| 3 | Danaher | 158.94 Bn | 142.76 Bn | 3.61 Bn |
| 4 | Intuitive Surgical | 145.87 Bn | 125.42 Bn | 1.96 Bn |
| 5 | Medtronic | 111.49 Bn | 77.36 Bn | 6.34 Bn |
| 6 | Stryker | 106.96 Bn | 93.08 Bn | 4.50 Bn |
| 7 | Boston Scientific | 63.62 Bn | 58.63 Bn | 3.85 Bn |
| 8 | Edwards Lifesciences | 50.80 Bn | 34.92 Bn | 1.35 Bn |
| 9 | Becton Dickinson | 49.59 Bn | 46.74 Bn | 2.32 Bn |
| 10 | InMode | 900.96 Mn | -725.66 Mn | 71.52 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 7.31 |
| Mar 31, 2026 | 5.16 |
| Dec 31, 2025 | 6.33 |
| Sep 30, 2025 | 7.53 |
| Jun 30, 2025 | 5.24 |
| Mar 31, 2025 | 7.79 |
| Dec 31, 2024 | 7.35 |
| Sep 30, 2024 | 7.16 |
| Jun 30, 2024 | 8.22 |
| Mar 31, 2024 | 7.52 |
| Dec 31, 2023 | 7.88 |
| Sep 30, 2023 | 9.73 |
| Jun 30, 2023 | 11.88 |
| Mar 31, 2023 | 10.46 |
| Dec 31, 2022 | 14.12 |
| Sep 30, 2022 | 10.40 |
| Jun 30, 2022 | 8.00 |
| Mar 31, 2022 | 15.43 |
| Dec 31, 2021 | 34.13 |
| Sep 30, 2021 | 38.12 |
API Access
InMode EV to 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=ev-to-ebitda&ticker=INMD&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ev-to-ebitda", "ticker": "INMD", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=ev-to-ebitda&ticker=INMD&period=max&api_key=YOUR_API_KEY");
const data = await res.json();