Hyperscale Data (GPUS) Total Liabilities (2010 - 2026)
Hyperscale Data's Total Liabilities was $243.51 million in Q2 2026, up 18.4% from $205.61 million a year earlier and up 12.4% from the prior quarter.
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Analysis
Hyperscale Data (GPUS) Total Liabilities (2010 - 2026) Analysis & Trends
At the end of FY2025, Total Liabilities at Hyperscale Data came in at $187.85 million, down 14.1% from FY2024.
- Total Liabilities has now declined for three consecutive years, though with a five-year compound annual growth rate of 47.9% (FY2020 to FY2025).
- In earlier years, 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 marks the highest quarterly Total Liabilities since Q2 2024.
- Compared with a year earlier, Total Liabilities was higher in two of the last eight quarters, with an average decline of 7.5%.
- The best year-over-year quarter for Total Liabilities over five years was Q4 2021 (growth of 887.6%); the worst was Q3 2021 (a decline of 36.8%).
- Per Business Quant data, GPUS's Total Liabilities in the three quarters before Q2 2026 was $216.65 million (Q1 2026), $187.85 million (Q4 2025) and $184.67 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Coinbase Global | 50.59 Bn | 7.40 Bn | - | 13.38 Bn |
| 2 | PayPal Holdings | 46.79 Bn | 5.01 Bn | - | 62.92 Bn |
| 3 | Block | 44.05 Bn | 15.31 Bn | 3.17 Bn | 17.11 Bn |
| 4 | Iren | 31.74 Bn | 19.34 Bn | 103.89 Mn | 11.60 Bn |
| 5 | Corpay | 26.01 Bn | 16.21 Bn | - | 24.64 Bn |
| 6 | Fiserv | 24.47 Bn | 21.17 Bn | 2.90 Bn | 53.96 Bn |
| 7 | Global Payments | 22.51 Bn | 952.73 Mn | 2.03 Bn | 39.81 Bn |
| 8 | Bitmine Immersion Technologies | 15.56 Bn | 12.94 Bn | 40.81 Mn | 30.13 Mn |
| 9 | Guidewire Software | 11.90 Bn | 8.47 Bn | 269.68 Mn | 1.38 Bn |
| 10 | Hyperscale Data | 80.79 Mn | -111.20 Mn | 8.80 Mn | 243.51 Mn |
Historic Data
Download Data
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 |
API Access
Hyperscale Data 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&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "GPUS", "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&period=max&api_key=YOUR_API_KEY");
const data = await res.json();