Proto Labs (PRLB) Total Liabilities (2011 - 2026)
Proto Labs (PRLB) reported Total Liabilities of $106.22 million for Q3 2026, up 15.3% from $92.14 million a year earlier and up 6.7% from the prior quarter.
Proto Labs (PRLB) Total Liabilities (2011 - 2026) Analysis & Trends
At the end of FY2025, Proto Labs posted Total Liabilities of $89.48 million, up 22.0% from FY2024.
- Total Liabilities has a five-year compound annual growth rate of -2.2% (FY2020 to FY2025).
- By year, Total Liabilities came in at $73.36 million in FY2024 (-4.8%), $77.06 million in FY2023 (-26.3%), $104.52 million in FY2022 (+4.4%) and $100.09 million in FY2021 (+0.2%).
- The Q3 2026 figure ranks as the highest quarterly Total Liabilities since Q1 2023.
- Year over year, Total Liabilities has now increased in each of the last six quarters, with growth averaging 13.5% over the last eight quarters.
- The high point for year-over-year Total Liabilities in five years was Q2 2026 (growth of 26.8%); the low point was Q4 2023 (a decline of 26.3%).
- Per Business Quant data, the three quarters before Q3 2026 came in at $99.57 million (Q2 2026), $95.44 million (Q1 2026) and $89.48 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Caterpillar | 267.46 Bn | 238.77 Bn | 7.35 Bn | 85.36 Bn |
| 2 | Amphenol | 197.37 Bn | 192.21 Bn | 4.02 Bn | 29.76 Bn |
| 3 | Deere | 185.36 Bn | 194.13 Bn | 4.66 Bn | 79.61 Bn |
| 4 | Eaton | 137.64 Bn | 134.62 Bn | 3.11 Bn | 36.43 Bn |
| 5 | Parker-Hannifin | 121.80 Bn | 119.79 Bn | 2.26 Bn | 25.86 Bn |
| 6 | 3M | 97.84 Bn | 80.25 Bn | 2.78 Bn | 35.36 Bn |
| 7 | Emerson Electric | 93.37 Bn | 85.86 Bn | 2.74 Bn | 21.06 Bn |
| 8 | Illinois Tool Works | 81.86 Bn | 78.53 Bn | 1.91 Bn | 13.36 Bn |
| 9 | Vertiv Holdings | 74.77 Bn | 63.62 Bn | 1.64 Bn | 12.67 Bn |
| 10 | Proto Labs | 1.62 Bn | 1.06 Bn | 68.66 Mn | 106.22 Mn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 106.22 Mn |
| Jun 30, 2026 | 99.57 Mn |
| Mar 31, 2026 | 95.44 Mn |
| Dec 31, 2025 | 89.48 Mn |
| Sep 30, 2025 | 92.14 Mn |
| Jun 30, 2025 | 78.55 Mn |
| Mar 31, 2025 | 80.65 Mn |
| Dec 31, 2024 | 73.36 Mn |
| Sep 30, 2024 | 73.79 Mn |
| Jun 30, 2024 | 72.97 Mn |
| Mar 31, 2024 | 82.49 Mn |
| Dec 31, 2023 | 77.06 Mn |
| Sep 30, 2023 | 99.32 Mn |
| Jun 30, 2023 | 94.53 Mn |
| Mar 31, 2023 | 108.24 Mn |
| Dec 31, 2022 | 104.52 Mn |
| Sep 30, 2022 | 96.09 Mn |
| Jun 30, 2022 | 97.95 Mn |
| Mar 31, 2022 | 102.72 Mn |
| Dec 31, 2021 | 100.09 Mn |
Proto Labs 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=PRLB&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "PRLB", "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=PRLB&period=max&api_key=YOUR_API_KEY");
const data = await res.json();