Ufp Technologies (UFPT) Total Liabilities (2010 - 2026)
Ufp Technologies' Total Liabilities was $219.48 million in Q2 2026, down 11.9% from $249.17 million a year earlier and down 6.9% from the prior quarter.
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Analysis
Ufp Technologies (UFPT) Total Liabilities (2010 - 2026) Analysis & Trends
At the end of FY2025, Total Liabilities at Ufp Technologies came in at $231.2 million, down 19.2% from FY2024.
- Total Liabilities shows a five-year compound annual growth rate of 54.4% (FY2020 to FY2025).
- In earlier years, Total Liabilities was $286.24 million in FY2024 (+142.5%), $118.05 million in FY2023 (-16.1%), $140.65 million in FY2022 (+0.7%) and $139.69 million in FY2021 (+430.9%).
- The Q2 2026 figure marks the lowest quarterly Total Liabilities since Q2 2024.
- Compared with a year earlier, Total Liabilities has declined for four straight quarters, with growth averaging 61.3% over the last eight quarters.
- The best year-over-year quarter for Total Liabilities over five years was Q2 2022 (growth of 506.2%); the worst was Q2 2023 (a decline of 26.7%).
- Per Business Quant data, UFPT's Total Liabilities in the three quarters before Q2 2026 was $235.81 million (Q1 2026), $231.2 million (Q4 2025) and $248.91 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 249.71 Bn | 228.86 Bn | 4.88 Bn | 60.49 Bn |
| 2 | Abbott Laboratories | 171.00 Bn | 142.08 Bn | 7.27 Bn | 57.45 Bn |
| 3 | Danaher | 155.79 Bn | 139.61 Bn | 3.61 Bn | 39.78 Bn |
| 4 | Intuitive Surgical | 143.91 Bn | 123.46 Bn | 1.96 Bn | 2.58 Bn |
| 5 | Medtronic | 110.42 Bn | 76.29 Bn | 6.34 Bn | 42.46 Bn |
| 6 | Stryker | 105.71 Bn | 91.82 Bn | 4.50 Bn | 23.94 Bn |
| 7 | Boston Scientific | 63.26 Bn | 58.27 Bn | 3.85 Bn | 20.04 Bn |
| 8 | Edwards Lifesciences | 49.80 Bn | 33.91 Bn | 1.35 Bn | 3.14 Bn |
| 9 | Becton Dickinson | 48.78 Bn | 45.93 Bn | 2.32 Bn | 26.32 Bn |
| 10 | Ufp Technologies | 2.30 Bn | 2.23 Bn | 50.92 Mn | 219.48 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 219.48 Mn |
| Mar 31, 2026 | 235.81 Mn |
| Dec 31, 2025 | 231.20 Mn |
| Sep 30, 2025 | 248.91 Mn |
| Jun 30, 2025 | 249.17 Mn |
| Mar 31, 2025 | 281.97 Mn |
| Dec 31, 2024 | 286.24 Mn |
| Sep 30, 2024 | 309.36 Mn |
| Jun 30, 2024 | 112.22 Mn |
| Mar 31, 2024 | 112.66 Mn |
| Dec 31, 2023 | 118.05 Mn |
| Sep 30, 2023 | 127.43 Mn |
| Jun 30, 2023 | 137.71 Mn |
| Mar 31, 2023 | 144.30 Mn |
| Dec 31, 2022 | 140.65 Mn |
| Sep 30, 2022 | 162.16 Mn |
| Jun 30, 2022 | 187.76 Mn |
| Mar 31, 2022 | 164.27 Mn |
| Dec 31, 2021 | 139.69 Mn |
| Sep 30, 2021 | 29.93 Mn |
API Access
Ufp Technologies 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=UFPT&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "UFPT", "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=UFPT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();