Hyperscale Data (GPUS) Revenue (2010 - 2026)
Hyperscale Data (GPUS) posted Revenue of $34.84 million for Q2 2026, up 34.8% from $25.86 million a year earlier but down 21.0% from the prior quarter.
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Analysis
Hyperscale Data (GPUS) Revenue (2010 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Revenue at Hyperscale Data was $130.16 million, up 28.4% year-over-year; for FY2025, it came in at $102.11 million, down 4.3% from FY2024.
- Annual Revenue shows a five-year compound annual growth rate of 33.7% (FY2020 to FY2025).
- In prior years, Hyperscale Data's Revenue was $106.66 million in FY2024 (-20.9%), $134.85 million in FY2023 (+14.6%), $117.64 million in FY2022 (+124.5%) and $52.4 million in FY2021 (+119.5%).
- Quarterly Revenue has run from a low of $7.82 million in Q4 2021 to a high of $47.41 million in Q2 2023 over five years.
- On a year-over-year basis, Revenue has increased in each of the last three quarters, with growth averaging 9.2% over the last eight quarters.
- The strongest year-over-year quarter for Revenue in the past five years was Q3 2021, with growth of 442.5%; the weakest was Q2 2022, with a decline of 72.0%.
- According to Business Quant data, Revenue for the three prior quarters was $44.08 million (Q1 2026), $26.91 million (Q4 2025) and $24.33 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Revenue (Qtr) |
|---|---|---|---|---|---|
| 1 | Coinbase Global | 50.59 Bn | 7.40 Bn | - | 1.22 Bn |
| 2 | PayPal Holdings | 46.79 Bn | 5.01 Bn | - | 8.68 Bn |
| 3 | Block | 44.05 Bn | 15.31 Bn | 3.17 Bn | 6.62 Bn |
| 4 | Iren | 31.74 Bn | 19.34 Bn | 103.89 Mn | 137.23 Mn |
| 5 | Corpay | 26.01 Bn | 16.21 Bn | - | 1.34 Bn |
| 6 | Fiserv | 24.47 Bn | 21.17 Bn | 2.90 Bn | 5.29 Bn |
| 7 | Global Payments | 22.51 Bn | 952.73 Mn | 2.03 Bn | 3.32 Bn |
| 8 | Bitmine Immersion Technologies | 15.56 Bn | 12.94 Bn | 40.81 Mn | 46.54 Mn |
| 9 | Guidewire Software | 11.90 Bn | 8.47 Bn | 269.68 Mn | 411.09 Mn |
| 10 | Hyperscale Data | 80.79 Mn | -111.20 Mn | 8.80 Mn | 34.84 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 34.84 Mn |
| Mar 31, 2026 | 44.08 Mn |
| Dec 31, 2025 | 26.91 Mn |
| Sep 30, 2025 | 24.33 Mn |
| Jun 30, 2025 | 25.86 Mn |
| Mar 31, 2025 | 25.02 Mn |
| Dec 31, 2024 | 19.44 Mn |
| Sep 30, 2024 | 31.06 Mn |
| Jun 30, 2024 | 17.79 Mn |
| Mar 31, 2024 | 38.37 Mn |
| Dec 31, 2023 | 30.61 Mn |
| Sep 30, 2023 | 43.09 Mn |
| Jun 30, 2023 | 47.41 Mn |
| Mar 31, 2023 | 28.94 Mn |
| Dec 31, 2022 | 30.48 Mn |
| Sep 30, 2022 | 44.27 Mn |
| Jun 30, 2022 | 17.37 Mn |
| Mar 31, 2022 | 32.83 Mn |
| Dec 31, 2021 | 7.82 Mn |
| Sep 30, 2021 | 30.79 Mn |
API Access
Hyperscale Data Revenue 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=revenue&ticker=GPUS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "revenue", "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=revenue&ticker=GPUS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();