Harvard Bioscience (HBIO) Operating Expenses (2010 - 2026)
Harvard Bioscience (HBIO) posted Operating Expenses of $13.61 million for Q2 2026, up 10.2% from $12.35 million a year earlier and up 1.4% from the prior quarter.
Harvard Bioscience (HBIO) Operating Expenses (2010 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Harvard Bioscience was $51.31 million, down 50.1% year-over-year; for FY2025, it came in at $98.49 million, up 61.5% from FY2024.
- Annual Operating Expenses shows a five-year compound annual growth rate of 11.2% (FY2020 to FY2025).
- In prior years, Harvard Bioscience's Operating Expenses was $60.98 million in FY2024 (-5.0%), $64.18 million in FY2023 (-5.3%), $67.75 million in FY2022 (+3.3%) and $65.59 million in FY2021 (+13.4%).
- The Q2 2026 figure stands as the highest quarterly Operating Expenses since Q1 2025.
- On a year-over-year basis, Operating Expenses increased in two of the last eight quarters, with growth averaging 15.7%.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q1 2025, with growth of 262.7%; the weakest was Q1 2026, with a decline of 78.3%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $13.42 million (Q1 2026), $12.46 million (Q4 2025) and $11.82 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 257.99 Bn | 237.02 Bn | 4.88 Bn | 9.91 Bn |
| 2 | Abbott Laboratories | 175.01 Bn | 145.44 Bn | 7.27 Bn | 10.90 Bn |
| 3 | Danaher | 164.93 Bn | 148.74 Bn | 3.61 Bn | 2.48 Bn |
| 4 | Intuitive Surgical | 151.84 Bn | 131.26 Bn | 1.96 Bn | 988.50 Mn |
| 5 | Medtronic | 119.05 Bn | 84.30 Bn | 6.34 Bn | 4.06 Bn |
| 6 | Stryker | 113.89 Bn | 100.00 Bn | 4.50 Bn | 2.84 Bn |
| 7 | Boston Scientific | 65.37 Bn | 60.13 Bn | 3.85 Bn | 2.67 Bn |
| 8 | Becton Dickinson | 53.36 Bn | 50.51 Bn | 2.32 Bn | 4.32 Bn |
| 9 | Edwards Lifesciences | 50.83 Bn | 34.83 Bn | 1.35 Bn | 840.10 Mn |
| 10 | Harvard Bioscience | 38.15 Mn | 9.12 Mn | 12.63 Mn | 13.61 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 13.61 Mn |
| Mar 31, 2026 | 13.42 Mn |
| Dec 31, 2025 | 12.46 Mn |
| Sep 30, 2025 | 11.82 Mn |
| Jun 30, 2025 | 12.35 Mn |
| Mar 31, 2025 | 61.85 Mn |
| Dec 31, 2024 | 14.00 Mn |
| Sep 30, 2024 | 14.64 Mn |
| Jun 30, 2024 | 15.29 Mn |
| Mar 31, 2024 | 17.05 Mn |
| Dec 31, 2023 | 16.04 Mn |
| Sep 30, 2023 | 15.66 Mn |
| Jun 30, 2023 | 15.88 Mn |
| Mar 31, 2023 | 16.60 Mn |
| Dec 31, 2022 | 16.29 Mn |
| Sep 30, 2022 | 15.93 Mn |
| Jun 30, 2022 | 12.64 Mn |
| Mar 31, 2022 | 22.89 Mn |
| Dec 31, 2021 | 17.86 Mn |
| Sep 30, 2021 | 15.76 Mn |
Harvard Bioscience 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=HBIO&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "HBIO", "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=HBIO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();