Hyperscale Data (GPUS) Change in Accured Expenses (2016 - 2026)
Hyperscale Data (GPUS) posted Change in Accured Expenses of $1.34 million for Q2 2026, up 227.1% from $409,000 a year earlier but down 93.8% from the prior quarter.
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Analysis
Hyperscale Data (GPUS) Change in Accured Expenses (2016 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Change in Accured Expenses at Hyperscale Data was $9.04 million, up 2.6% year-over-year; for FY2025, it was -$11.3 million.
- In prior years, Hyperscale Data's Change in Accured Expenses was $2.41 million in FY2024 (-84.5%), $15.57 million in FY2023 (+64.4%), $9.47 million in FY2022 (+480.7%) and $1.63 million in FY2021.
- Quarterly Change in Accured Expenses has run from a low of -$8.56 million in Q4 2025 to a high of $21.62 million in Q1 2026 over five years.
- On a year-over-year basis, Change in Accured Expenses increased in three of the last four quarters, with growth averaging 264.8%.
- The strongest year-over-year quarter for Change in Accured Expenses in the past five years was Q1 2026, with growth of 881.0%; the weakest was Q2 2025, with a decline of 89.2%.
- According to Business Quant data, Change in Accured Expenses for the three prior quarters was $21.62 million (Q1 2026), -$8.56 million (Q4 2025) and -$5.35 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Coinbase Global | 48.27 Bn | 5.08 Bn | - | - |
| 2 | PayPal Holdings | 45.51 Bn | 3.74 Bn | - | - |
| 3 | Block | 44.67 Bn | 15.93 Bn | 3.17 Bn | - |
| 4 | Iren | 31.78 Bn | 19.37 Bn | 103.89 Mn | 31.16 Mn |
| 5 | Corpay | 25.91 Bn | 16.11 Bn | - | 1.26 Bn |
| 6 | Fiserv | 23.59 Bn | 20.29 Bn | 2.90 Bn | 140.00 Mn |
| 7 | Global Payments | 20.83 Bn | -735.18 Mn | 2.03 Bn | -70.94 Mn |
| 8 | Bitmine Immersion Technologies | 15.23 Bn | 12.61 Bn | 40.81 Mn | -4.53 Mn |
| 9 | Guidewire Software | 12.47 Bn | 9.03 Bn | 269.68 Mn | 29.77 Mn |
| 10 | Hyperscale Data | 80.79 Mn | -111.20 Mn | 8.80 Mn | 1.34 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.34 Mn |
| Mar 31, 2026 | 21.62 Mn |
| Dec 31, 2025 | -8.56 Mn |
| Sep 30, 2025 | -5.35 Mn |
| Jun 30, 2025 | 409,000.00 |
| Mar 31, 2025 | 2.20 Mn |
| Dec 31, 2024 | -1.06 Mn |
| Sep 30, 2024 | 7.26 Mn |
| Jun 30, 2024 | 3.78 Mn |
| Mar 31, 2024 | -7.58 Mn |
| Dec 31, 2023 | 2.23 Mn |
| Sep 30, 2023 | 5.19 Mn |
| Jun 30, 2023 | 11.95 Mn |
| Mar 31, 2023 | -3.80 Mn |
| Dec 31, 2022 | 1.94 Mn |
| Sep 30, 2022 | 2.82 Mn |
| Jun 30, 2022 | -255,000.00 |
| Mar 31, 2022 | 4.96 Mn |
| Dec 31, 2021 | 2.71 Mn |
| Sep 30, 2021 | -1.17 Mn |
API Access
Hyperscale Data Change in Accured Expenses 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=change-in-accured-expenses&ticker=GPUS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "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=change-in-accured-expenses&ticker=GPUS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();