Butterfly Network (BFLY) Total Liabilities (2020 - 2026)
Butterfly Network's Total Liabilities was $93.6 million in Q2 2026, up 16.3% from $80.47 million a year earlier but down 1.2% from the prior quarter.
Butterfly Network (BFLY) Total Liabilities (2020 - 2026) Analysis & Trends
At the end of FY2025, Total Liabilities at Butterfly Network came in at $100.55 million, up 15.2% from FY2024.
- Total Liabilities shows a five-year compound annual growth rate of -27.7% (FY2020 to FY2025).
- In earlier years, Total Liabilities was $87.25 million in FY2024 (+3.6%), $84.22 million in FY2023 (-8.7%), $92.21 million in FY2022 (-25.8%) and $124.27 million in FY2021 (-75.6%).
- Quarterly Total Liabilities has moved between $76.8 million (Q3 2023) and $129.06 million (Q3 2021) over five years.
- Compared with a year earlier, Total Liabilities has increased for five straight quarters, with growth averaging 8.4% over the last eight quarters.
- The best year-over-year quarter for Total Liabilities over five years was Q1 2026 (growth of 20.3%); the worst was Q3 2021 (a decline of 83.0%).
- Per Business Quant data, BFLY's Total Liabilities in the three quarters before Q2 2026 was $94.7 million (Q1 2026), $100.55 million (Q4 2025) and $86.17 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 251.93 Bn | 230.96 Bn | 4.88 Bn | 60.49 Bn |
| 2 | Abbott Laboratories | 181.29 Bn | 151.72 Bn | 7.27 Bn | 57.45 Bn |
| 3 | Danaher | 158.18 Bn | 141.99 Bn | 3.61 Bn | 39.78 Bn |
| 4 | Intuitive Surgical | 153.47 Bn | 132.89 Bn | 1.96 Bn | 2.58 Bn |
| 5 | Medtronic | 118.97 Bn | 84.22 Bn | 6.34 Bn | 42.46 Bn |
| 6 | Stryker | 114.72 Bn | 100.84 Bn | 4.50 Bn | 23.94 Bn |
| 7 | Boston Scientific | 66.18 Bn | 60.95 Bn | 3.85 Bn | 20.04 Bn |
| 8 | Becton Dickinson | 52.49 Bn | 49.64 Bn | 2.32 Bn | 26.32 Bn |
| 9 | Edwards Lifesciences | 50.32 Bn | 34.33 Bn | 1.35 Bn | 3.14 Bn |
| 10 | Butterfly Network | 1.96 Bn | 1.40 Bn | 23.29 Mn | 93.60 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 93.60 Mn |
| Mar 31, 2026 | 94.70 Mn |
| Dec 31, 2025 | 100.55 Mn |
| Sep 30, 2025 | 86.17 Mn |
| Jun 30, 2025 | 80.47 Mn |
| Mar 31, 2025 | 78.72 Mn |
| Dec 31, 2024 | 87.25 Mn |
| Sep 30, 2024 | 83.44 Mn |
| Jun 30, 2024 | 78.79 Mn |
| Mar 31, 2024 | 80.28 Mn |
| Dec 31, 2023 | 84.22 Mn |
| Sep 30, 2023 | 76.80 Mn |
| Jun 30, 2023 | 86.88 Mn |
| Mar 31, 2023 | 85.53 Mn |
| Dec 31, 2022 | 92.21 Mn |
| Sep 30, 2022 | 99.62 Mn |
| Jun 30, 2022 | 109.95 Mn |
| Mar 31, 2022 | 122.76 Mn |
| Dec 31, 2021 | 124.27 Mn |
| Sep 30, 2021 | 129.06 Mn |
Butterfly Network Total Liabilities 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=total-liabilities&ticker=BFLY&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "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=total-liabilities&ticker=BFLY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();