Hyperscale Data (GPUS) Cost of Revenue (2010 - 2026)
Hyperscale Data (GPUS) posted Cost of Revenue of $26.05 million for Q2 2026, up 32.0% from $19.73 million a year earlier but down 10.2% from the prior quarter.
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Analysis
Hyperscale Data (GPUS) Cost of Revenue (2010 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Cost of Revenue at Hyperscale Data was $96.13 million, up 19.9% year-over-year; for FY2025, it came in at $80.54 million, down 2.3% from FY2024.
- Annual Cost of Revenue shows a five-year compound annual growth rate of 37.5% (FY2020 to FY2025).
- In prior years, Hyperscale Data's Cost of Revenue was $82.45 million in FY2024 (-25.1%), $110.06 million in FY2023 (+64.4%), $66.96 million in FY2022 (+180.6%) and $23.86 million in FY2021 (+45.9%).
- Quarterly Cost of Revenue has run from a low of $5.27 million in Q3 2021 to a high of $34.36 million in Q3 2023 over five years.
- On a year-over-year basis, Cost of Revenue has increased in each of the last three quarters, with growth averaging 0.2% over the last eight quarters.
- The strongest year-over-year quarter for Cost of Revenue in the past five years was Q3 2022, with growth of 382.8%; the weakest was Q4 2024, with a decline of 39.1%.
- According to Business Quant data, Cost of Revenue for the three prior quarters was $29.01 million (Q1 2026), $23.01 million (Q4 2025) and $18.06 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Cost of Rev (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 | 3.45 Bn |
| 4 | Iren | 31.78 Bn | 19.37 Bn | 103.89 Mn | 33.34 Mn |
| 5 | Corpay | 25.91 Bn | 16.11 Bn | - | - |
| 6 | Fiserv | 23.59 Bn | 20.29 Bn | 2.90 Bn | 2.40 Bn |
| 7 | Global Payments | 20.83 Bn | -735.18 Mn | 2.03 Bn | 1.29 Bn |
| 8 | Bitmine Immersion Technologies | 15.23 Bn | 12.61 Bn | 40.81 Mn | 5.73 Mn |
| 9 | Guidewire Software | 12.47 Bn | 9.03 Bn | 269.68 Mn | 141.41 Mn |
| 10 | Hyperscale Data | 80.79 Mn | -111.20 Mn | 8.80 Mn | 26.05 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 26.05 Mn |
| Mar 31, 2026 | 29.01 Mn |
| Dec 31, 2025 | 23.01 Mn |
| Sep 30, 2025 | 18.06 Mn |
| Jun 30, 2025 | 19.73 Mn |
| Mar 31, 2025 | 19.74 Mn |
| Dec 31, 2024 | 18.17 Mn |
| Sep 30, 2024 | 22.52 Mn |
| Jun 30, 2024 | 21.58 Mn |
| Mar 31, 2024 | 20.18 Mn |
| Dec 31, 2023 | 29.86 Mn |
| Sep 30, 2023 | 34.36 Mn |
| Jun 30, 2023 | 29.52 Mn |
| Mar 31, 2023 | 26.46 Mn |
| Dec 31, 2022 | 23.77 Mn |
| Sep 30, 2022 | 25.45 Mn |
| Jun 30, 2022 | 12.37 Mn |
| Mar 31, 2022 | 10.49 Mn |
| Dec 31, 2021 | 7.20 Mn |
| Sep 30, 2021 | 5.27 Mn |
API Access
Hyperscale Data Cost of 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=cost-of-revenue&ticker=GPUS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "cost-of-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=cost-of-revenue&ticker=GPUS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();