Ufp Technologies (UFPT) Cost of Revenue (2010 - 2026)
Ufp Technologies (UFPT) recorded Cost of Revenue of $123.05 million in Q2 2026, up 14.3% from $107.63 million a year earlier and up 12.0% from the prior quarter.
Ufp Technologies (UFPT) Cost of Revenue (2010 - 2026) Analysis & Trends
On a TTM basis, Ufp Technologies' Cost of Revenue came in at $451.64 million as of Jun 30, 2026, up 7.7% year-over-year; for FY2025, it came in at $432.39 million, up 20.9% from FY2024.
- Annual Cost of Revenue has increased for five straight years, with a five-year compound annual growth rate of 26.3% (FY2020 to FY2025).
- Across earlier years, Cost of Revenue came in at $357.73 million in FY2024 (+24.3%), $287.85 million in FY2023 (+9.2%), $263.53 million in FY2022 (+69.8%) and $155.21 million in FY2021 (+15.2%).
- The Q2 2026 figure is the highest quarterly Cost of Revenue in data going back to Q2 2010.
- On a year-over-year basis, Cost of Revenue has increased for 22 consecutive quarters, with growth averaging 23.6% over the last eight quarters.
- Across the past five years, year-over-year growth in Cost of Revenue ran from 0.5% in Q2 2023 to 88.0% in Q2 2022.
- Per Business Quant, the preceding three quarters came in at $109.84 million (Q1 2026), $106.95 million (Q4 2025) and $111.81 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Cost of Rev (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 242.18 Bn | 221.33 Bn | 4.88 Bn | 7.11 Bn |
| 2 | Abbott Laboratories | 168.71 Bn | 139.79 Bn | 7.27 Bn | 5.33 Bn |
| 3 | Danaher | 150.46 Bn | 134.27 Bn | 3.61 Bn | 2.65 Bn |
| 4 | Intuitive Surgical | 138.71 Bn | 118.26 Bn | 1.96 Bn | 931.90 Mn |
| 5 | Medtronic | 110.54 Bn | 76.41 Bn | 6.34 Bn | 3.42 Bn |
| 6 | Stryker | 105.66 Bn | 91.78 Bn | 4.50 Bn | 2.09 Bn |
| 7 | Boston Scientific | 61.74 Bn | 56.75 Bn | 3.85 Bn | 1.59 Bn |
| 8 | Edwards Lifesciences | 49.09 Bn | 33.21 Bn | 1.35 Bn | 392.40 Mn |
| 9 | Becton Dickinson | 48.16 Bn | 45.31 Bn | 2.32 Bn | 2.67 Bn |
| 10 | Ufp Technologies | 2.33 Bn | 2.26 Bn | 50.92 Mn | 123.05 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 123.05 Mn |
| Mar 31, 2026 | 109.84 Mn |
| Dec 31, 2025 | 106.95 Mn |
| Sep 30, 2025 | 111.81 Mn |
| Jun 30, 2025 | 107.63 Mn |
| Mar 31, 2025 | 106.00 Mn |
| Dec 31, 2024 | 102.01 Mn |
| Sep 30, 2024 | 103.64 Mn |
| Jun 30, 2024 | 77.15 Mn |
| Mar 31, 2024 | 74.93 Mn |
| Dec 31, 2023 | 75.37 Mn |
| Sep 30, 2023 | 73.03 Mn |
| Jun 30, 2023 | 70.39 Mn |
| Mar 31, 2023 | 69.05 Mn |
| Dec 31, 2022 | 67.96 Mn |
| Sep 30, 2022 | 71.45 Mn |
| Jun 30, 2022 | 70.02 Mn |
| Mar 31, 2022 | 54.11 Mn |
| Dec 31, 2021 | 43.27 Mn |
| Sep 30, 2021 | 38.71 Mn |
Ufp Technologies Cost of Revenue 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=cost-of-revenue&ticker=UFPT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "cost-of-revenue", "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=cost-of-revenue&ticker=UFPT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();