Pdf Solutions (PDFS) Total Liabilities (2010 - 2026)
Pdf Solutions' Total Liabilities came in at $146.68 million for Q2 2026, up 9.8% from $133.61 million a year earlier but down 2.3% from the prior quarter.
Pdf Solutions (PDFS) Total Liabilities (2010 - 2026) Analysis & Trends
At the end of FY2025, Pdf Solutions' Total Liabilities was $147.68 million, up 113.2% from FY2024.
- Total Liabilities carries a five-year compound annual growth rate of 22.7% (FY2020 to FY2025).
- Going back by year, Total Liabilities was $69.25 million in FY2024 (+13.2%), $61.19 million in FY2023 (-10.9%), $68.66 million in FY2022 (+26.7%) and $54.18 million in FY2021 (+2.1%).
- The five-year range for quarterly Total Liabilities is $51.29 million (Q2 2022) to $150.1 million (Q1 2026).
- Year-over-year, Total Liabilities has increased for eight consecutive quarters, with growth averaging 62.2% over the last eight quarters.
- The fastest year-over-year change in Total Liabilities over five years came in Q1 2025 (growth of 129.6%), and the weakest in Q4 2023 (a decline of 10.9%).
- Business Quant data shows PDFS's Total Liabilities at $150.1 million (Q1 2026), $147.68 million (Q4 2025) and $142.02 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Nvidia | 5,515.53 Bn | 5,289.69 Bn | 72.14 Bn | 91.29 Bn |
| 2 | Taiwan Semiconductor Manufacturing | 2,348.76 Bn | 1,974.46 Bn | 27.22 Bn | 93.12 Bn |
| 3 | Broadcom | 1,668.85 Bn | 1,594.89 Bn | 20.46 Bn | 88.46 Bn |
| 4 | Micron Technology | 1,189.94 Bn | 1,128.71 Bn | 35.06 Bn | 33.39 Bn |
| 5 | Advanced Micro Devices | 992.04 Bn | 948.79 Bn | 6.20 Bn | 17.24 Bn |
| 6 | Asml Holding | 682.73 Bn | 638.57 Bn | 5.90 Bn | 36.03 Bn |
| 7 | Intel | 585.14 Bn | 469.87 Bn | 6.51 Bn | 99.30 Bn |
| 8 | Lam Research | 393.49 Bn | 370.29 Bn | 3.48 Bn | 11.06 Bn |
| 9 | Applied Materials | 386.29 Bn | 351.73 Bn | 4.59 Bn | 17.90 Bn |
| 10 | Pdf Solutions | 2.08 Bn | 1.86 Bn | 42.42 Mn | 146.68 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 146.68 Mn |
| Mar 31, 2026 | 150.10 Mn |
| Dec 31, 2025 | 147.68 Mn |
| Sep 30, 2025 | 142.02 Mn |
| Jun 30, 2025 | 133.61 Mn |
| Mar 31, 2025 | 140.99 Mn |
| Dec 31, 2024 | 69.25 Mn |
| Sep 30, 2024 | 66.89 Mn |
| Jun 30, 2024 | 65.85 Mn |
| Mar 31, 2024 | 61.41 Mn |
| Dec 31, 2023 | 61.19 Mn |
| Sep 30, 2023 | 60.89 Mn |
| Jun 30, 2023 | 66.10 Mn |
| Mar 31, 2023 | 65.86 Mn |
| Dec 31, 2022 | 68.66 Mn |
| Sep 30, 2022 | 62.77 Mn |
| Jun 30, 2022 | 51.29 Mn |
| Mar 31, 2022 | 52.01 Mn |
| Dec 31, 2021 | 54.18 Mn |
| Sep 30, 2021 | 51.77 Mn |
Pdf Solutions 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=PDFS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "PDFS", "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=PDFS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();