LogicMark (LGMK) Operating Expenses (2012 - 2026)
LogicMark (LGMK) reported Operating Expenses of $3.96 million for Q2 2026, down 2.4% from $4.06 million a year earlier but up 5.9% from the prior quarter.
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Analysis
LogicMark (LGMK) Operating Expenses (2012 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, LogicMark's Operating Expenses came in at $15.17 million, up 0.1% year-over-year; for FY2025, it was $15.53 million, up 8.7% from FY2024.
- Operating Expenses has a five-year compound annual growth rate of 13.5% (FY2020 to FY2025).
- By year, Operating Expenses came in at $14.29 million in FY2024 (-35.0%), $21.99 million in FY2023 (+55.5%), $14.14 million in FY2022 (+6.0%) and $13.33 million in FY2021 (+61.4%).
- Five-year quarterly Operating Expenses spans a low of $1.62 million in Q3 2021 and a high of $10.99 million in Q4 2023.
- Year over year, Operating Expenses gained in five of the last eight quarters, with an average decline of 5.0%.
- The high point for year-over-year Operating Expenses in five years was Q4 2021 (growth of 246.0%); the low point was Q4 2024 (a decline of 66.4%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $3.74 million (Q1 2026), $3.81 million (Q4 2025) and $3.66 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 249.09 Bn | 228.12 Bn | 4.88 Bn | 9.91 Bn |
| 2 | Abbott Laboratories | 180.55 Bn | 150.98 Bn | 7.27 Bn | 10.90 Bn |
| 3 | Danaher | 160.58 Bn | 144.39 Bn | 3.61 Bn | 2.48 Bn |
| 4 | Intuitive Surgical | 157.75 Bn | 138.04 Bn | 2.08 Bn | 1.49 Bn |
| 5 | Medtronic | 122.52 Bn | 87.77 Bn | 6.34 Bn | 4.06 Bn |
| 6 | Stryker | 118.16 Bn | 104.28 Bn | 4.50 Bn | 2.84 Bn |
| 7 | Boston Scientific | 66.98 Bn | 61.75 Bn | 3.85 Bn | 2.67 Bn |
| 8 | Becton Dickinson | 54.80 Bn | 51.94 Bn | 2.32 Bn | 4.32 Bn |
| 9 | Edwards Lifesciences | 51.55 Bn | 35.55 Bn | 1.35 Bn | 840.10 Mn |
| 10 | LogicMark | 1.17 Mn | -26.52 Mn | 2.37 Mn | 3.96 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 3.96 Mn |
| Mar 31, 2026 | 3.74 Mn |
| Dec 31, 2025 | 3.81 Mn |
| Sep 30, 2025 | 3.66 Mn |
| Jun 30, 2025 | 4.06 Mn |
| Mar 31, 2025 | 4.01 Mn |
| Dec 31, 2024 | 3.69 Mn |
| Sep 30, 2024 | 3.40 Mn |
| Jun 30, 2024 | 3.63 Mn |
| Mar 31, 2024 | 3.57 Mn |
| Dec 31, 2023 | 10.99 Mn |
| Sep 30, 2023 | 3.38 Mn |
| Jun 30, 2023 | 3.88 Mn |
| Mar 31, 2023 | 3.75 Mn |
| Dec 31, 2022 | 3.68 Mn |
| Sep 30, 2022 | 3.84 Mn |
| Jun 30, 2022 | 3.13 Mn |
| Mar 31, 2022 | 3.49 Mn |
| Dec 31, 2021 | 7.56 Mn |
| Sep 30, 2021 | 1.62 Mn |
API Access
LogicMark 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=LGMK&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "LGMK", "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=LGMK&period=max&api_key=YOUR_API_KEY");
const data = await res.json();