Hyperscale Data, Inc. (GPUS-PD) Total Liabilities (2010 - 2026)
Hyperscale Data's Total Liabilities came in at $243.51 million for Q2 2026, up 18.4% from $205.61 million a year earlier and up 12.4% from the prior quarter.
Hyperscale Data, Inc. (GPUS-PD) Total Liabilities (2010 - 2026) Analysis & Trends
At the end of FY2025, Hyperscale Data's Total Liabilities was $187.85 million, down 14.1% from FY2024.
- Total Liabilities has declined in each of the last three years, though with a five-year compound annual growth rate of 47.9% (FY2020 to FY2025).
- Going back by year, Total Liabilities was $218.68 million in FY2024 (-9.8%), $242.51 million in FY2023 (-28.1%), $337.53 million in FY2022 (+28.9%) and $261.83 million in FY2021 (+887.6%).
- The Q2 2026 figure represents the highest quarterly Total Liabilities since Q2 2024.
- Year-over-year, Total Liabilities increased in two of the last eight quarters, with an average decline of 7.5%.
- The fastest year-over-year change in Total Liabilities over five years came in Q4 2021 (growth of 887.6%), and the weakest in Q3 2021 (a decline of 36.8%).
- Business Quant data shows GPUS-PD's Total Liabilities at $216.65 million (Q1 2026), $187.85 million (Q4 2025) and $184.67 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 243.51 Mn |
| Mar 31, 2026 | 216.65 Mn |
| Dec 31, 2025 | 187.85 Mn |
| Sep 30, 2025 | 184.67 Mn |
| Jun 30, 2025 | 205.61 Mn |
| Mar 31, 2025 | 211.76 Mn |
| Dec 31, 2024 | 218.68 Mn |
| Sep 30, 2024 | 229.25 Mn |
| Jun 30, 2024 | 244.50 Mn |
| Mar 31, 2024 | 234.76 Mn |
| Dec 31, 2023 | 242.51 Mn |
| Sep 30, 2023 | 259.40 Mn |
| Jun 30, 2023 | 256.89 Mn |
| Mar 31, 2023 | 336.56 Mn |
| Dec 31, 2022 | 337.53 Mn |
| Sep 30, 2022 | 272.14 Mn |
| Jun 30, 2022 | 250.87 Mn |
| Mar 31, 2022 | 210.47 Mn |
| Dec 31, 2021 | 261.83 Mn |
| Sep 30, 2021 | 24.74 Mn |
Hyperscale Data, Inc. 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=GPUS-PD&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "GPUS-PD", "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=GPUS-PD&period=max&api_key=YOUR_API_KEY");
const data = await res.json();