Glaukos (GKOS) Operating Expenses (2014 - 2026)
Glaukos' Operating Expenses was $168.86 million in Q2 2026, up 40.8% from $119.91 million a year earlier and up 23.2% from the prior quarter.
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Analysis
Glaukos (GKOS) Operating Expenses (2014 - 2026) Analysis & Trends
On a trailing twelve-month basis, Glaukos' Operating Expenses was $565.37 million through Jun 30, 2026, up 32.3% year-over-year; for FY2025, it came in at $482.36 million, up 17.1% from FY2024.
- Operating Expenses has now increased for 12 consecutive years, with a five-year compound annual growth rate of 13.4% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $411.82 million in FY2024 (+12.0%), $367.84 million in FY2023 (+24.2%), $296.2 million in FY2022 (+13.8%) and $260.26 million in FY2021 (+1.3%).
- The Q2 2026 figure marks the highest quarterly Operating Expenses in data going back to Q1 2014.
- Compared with a year earlier, Operating Expenses has increased for five straight quarters, with growth averaging 19.8% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q1 2023 (growth of 117.6%); the worst was Q1 2022 (a decline of 35.3%).
- Per Business Quant data, GKOS's Operating Expenses in the three quarters before Q2 2026 was $137.09 million (Q1 2026), $138.35 million (Q4 2025) and $121.07 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 250.84 Bn | 229.99 Bn | 4.88 Bn | 9.91 Bn |
| 2 | Abbott Laboratories | 174.73 Bn | 145.82 Bn | 7.27 Bn | 10.90 Bn |
| 3 | Danaher | 159.85 Bn | 143.67 Bn | 3.61 Bn | 2.48 Bn |
| 4 | Intuitive Surgical | 146.79 Bn | 126.35 Bn | 1.96 Bn | 988.50 Mn |
| 5 | Medtronic | 114.54 Bn | 80.41 Bn | 6.34 Bn | 4.06 Bn |
| 6 | Stryker | 105.67 Bn | 91.79 Bn | 4.50 Bn | 2.84 Bn |
| 7 | Boston Scientific | 63.93 Bn | 58.94 Bn | 3.85 Bn | 2.67 Bn |
| 8 | Becton Dickinson | 50.12 Bn | 47.27 Bn | 2.32 Bn | 4.32 Bn |
| 9 | Edwards Lifesciences | 50.06 Bn | 34.17 Bn | 1.35 Bn | 840.10 Mn |
| 10 | Glaukos | 9.33 Bn | 8.92 Bn | 151.59 Mn | 168.86 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 168.86 Mn |
| Mar 31, 2026 | 137.09 Mn |
| Dec 31, 2025 | 138.35 Mn |
| Sep 30, 2025 | 121.07 Mn |
| Jun 30, 2025 | 119.91 Mn |
| Mar 31, 2025 | 103.03 Mn |
| Dec 31, 2024 | 105.53 Mn |
| Sep 30, 2024 | 98.75 Mn |
| Jun 30, 2024 | 103.11 Mn |
| Mar 31, 2024 | 104.43 Mn |
| Dec 31, 2023 | 102.10 Mn |
| Sep 30, 2023 | 87.55 Mn |
| Jun 30, 2023 | 89.37 Mn |
| Mar 31, 2023 | 88.82 Mn |
| Dec 31, 2022 | 87.74 Mn |
| Sep 30, 2022 | 76.02 Mn |
| Jun 30, 2022 | 91.61 Mn |
| Mar 31, 2022 | 40.83 Mn |
| Dec 31, 2021 | 74.24 Mn |
| Sep 30, 2021 | 48.32 Mn |
API Access
Glaukos 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=GKOS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "GKOS", "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=GKOS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();