Ufp Technologies (UFPT) Total Current Liabilities (2010 - 2026)
Ufp Technologies (UFPT) recorded Total Current Liabilities of $78.3 million in Q2 2026, up 13.2% from $69.2 million a year earlier and up 1.7% from the prior quarter.
Ufp Technologies (UFPT) Total Current Liabilities (2010 - 2026) Analysis & Trends
At the end of FY2025, Ufp Technologies reported Total Current Liabilities of $74.86 million, down 1.9% from FY2024.
- Annual Total Current Liabilities has a five-year compound annual growth rate of 37.7% (FY2020 to FY2025).
- Across earlier years, Total Current Liabilities came in at $76.3 million in FY2024 (+31.1%), $58.21 million in FY2023 (+4.0%), $55.96 million in FY2022 (+44.3%) and $38.78 million in FY2021 (+156.2%).
- Quarterly Total Current Liabilities has ranged from $18.76 million in Q3 2021 to $82.23 million in Q3 2025 over the past five years.
- On a year-over-year basis, Total Current Liabilities rose in six of the last eight quarters, with growth averaging 21.0%.
- Peak year-over-year performance for Total Current Liabilities in the last five years was growth of 206.0% in Q3 2022, against a decline of 3.6% in Q1 2026 at the low end.
- Per Business Quant, the preceding three quarters came in at $77.01 million (Q1 2026), $74.86 million (Q4 2025) and $82.23 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 249.71 Bn | 228.86 Bn | 4.88 Bn | 15.07 Bn |
| 2 | Abbott Laboratories | 171.00 Bn | 142.08 Bn | 7.27 Bn | 17.81 Bn |
| 3 | Danaher | 155.79 Bn | 139.61 Bn | 3.61 Bn | 8.11 Bn |
| 4 | Intuitive Surgical | 143.91 Bn | 123.46 Bn | 1.96 Bn | 1.92 Bn |
| 5 | Medtronic | 110.42 Bn | 76.29 Bn | 6.34 Bn | 11.80 Bn |
| 6 | Stryker | 105.71 Bn | 91.82 Bn | 4.50 Bn | 6.68 Bn |
| 7 | Boston Scientific | 63.26 Bn | 58.27 Bn | 3.85 Bn | 6.43 Bn |
| 8 | Edwards Lifesciences | 49.80 Bn | 33.91 Bn | 1.35 Bn | 1.51 Bn |
| 9 | Becton Dickinson | 48.78 Bn | 45.93 Bn | 2.32 Bn | 9.40 Bn |
| 10 | Ufp Technologies | 2.30 Bn | 2.23 Bn | 50.92 Mn | 78.30 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 78.30 Mn |
| Mar 31, 2026 | 77.01 Mn |
| Dec 31, 2025 | 74.86 Mn |
| Sep 30, 2025 | 82.23 Mn |
| Jun 30, 2025 | 69.20 Mn |
| Mar 31, 2025 | 79.87 Mn |
| Dec 31, 2024 | 76.30 Mn |
| Sep 30, 2024 | 78.35 Mn |
| Jun 30, 2024 | 51.79 Mn |
| Mar 31, 2024 | 52.44 Mn |
| Dec 31, 2023 | 58.21 Mn |
| Sep 30, 2023 | 56.59 Mn |
| Jun 30, 2023 | 52.99 Mn |
| Mar 31, 2023 | 52.19 Mn |
| Dec 31, 2022 | 55.96 Mn |
| Sep 30, 2022 | 57.40 Mn |
| Jun 30, 2022 | 53.38 Mn |
| Mar 31, 2022 | 38.82 Mn |
| Dec 31, 2021 | 38.78 Mn |
| Sep 30, 2021 | 18.76 Mn |
Ufp Technologies Total Current 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-current-liabilities&ticker=UFPT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-current-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-current-liabilities&ticker=UFPT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();