Butterfly Network (BFLY) Operating Expenses (2020 - 2026)
Butterfly Network (BFLY) recorded Operating Expenses of $36.95 million in Q2 2026, up 19.2% from $30.99 million a year earlier and up 14.9% from the prior quarter.
Butterfly Network (BFLY) Operating Expenses (2020 - 2026) Analysis & Trends
On a TTM basis, Butterfly Network's Operating Expenses came in at $138.42 million as of Jun 30, 2026, up 12.2% year-over-year; for FY2025, it was $132.15 million, up 7.2% from FY2024.
- Annual Operating Expenses has a five-year compound annual growth rate of 5.6% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $123.24 million in FY2024 (-24.1%), $162.47 million in FY2023 (-30.1%), $232.48 million in FY2022 (+10.8%) and $209.78 million in FY2021 (+109.0%).
- Quarterly Operating Expenses has ranged from $29.48 million in Q3 2024 to $59.03 million in Q2 2022 over the past five years.
- On a year-over-year basis, Operating Expenses has increased for five consecutive quarters, with growth averaging 1.3% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 129.7% in Q3 2021, against a decline of 41.6% in Q4 2023 at the low end.
- Per Business Quant, the preceding three quarters came in at $32.16 million (Q1 2026), $37.93 million (Q4 2025) and $31.38 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 251.93 Bn | 230.96 Bn | 4.88 Bn | 9.91 Bn |
| 2 | Abbott Laboratories | 181.29 Bn | 151.72 Bn | 7.27 Bn | 10.90 Bn |
| 3 | Danaher | 158.18 Bn | 141.99 Bn | 3.61 Bn | 2.48 Bn |
| 4 | Intuitive Surgical | 153.47 Bn | 132.89 Bn | 1.96 Bn | 988.50 Mn |
| 5 | Medtronic | 118.97 Bn | 84.22 Bn | 6.34 Bn | 4.06 Bn |
| 6 | Stryker | 114.72 Bn | 100.84 Bn | 4.50 Bn | 2.84 Bn |
| 7 | Boston Scientific | 66.18 Bn | 60.95 Bn | 3.85 Bn | 2.67 Bn |
| 8 | Becton Dickinson | 52.49 Bn | 49.64 Bn | 2.32 Bn | 4.32 Bn |
| 9 | Edwards Lifesciences | 50.32 Bn | 34.33 Bn | 1.35 Bn | 840.10 Mn |
| 10 | Butterfly Network | 1.96 Bn | 1.40 Bn | 23.29 Mn | 36.95 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 36.95 Mn |
| Mar 31, 2026 | 32.16 Mn |
| Dec 31, 2025 | 37.93 Mn |
| Sep 30, 2025 | 31.38 Mn |
| Jun 30, 2025 | 30.99 Mn |
| Mar 31, 2025 | 31.85 Mn |
| Dec 31, 2024 | 31.05 Mn |
| Sep 30, 2024 | 29.48 Mn |
| Jun 30, 2024 | 29.82 Mn |
| Mar 31, 2024 | 32.90 Mn |
| Dec 31, 2023 | 34.19 Mn |
| Sep 30, 2023 | 41.95 Mn |
| Jun 30, 2023 | 42.19 Mn |
| Mar 31, 2023 | 44.14 Mn |
| Dec 31, 2022 | 58.56 Mn |
| Sep 30, 2022 | 57.02 Mn |
| Jun 30, 2022 | 59.03 Mn |
| Mar 31, 2022 | 57.88 Mn |
| Dec 31, 2021 | 52.85 Mn |
| Sep 30, 2021 | 51.87 Mn |
Butterfly Network 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=BFLY&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "BFLY", "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=BFLY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();