Hyperscale Data (GPUS) Revenue (2010 - 2026)
Hyperscale Data (GPUS) reported Revenue of $44.1 million for Q1 2026, up 76.17% year-over-year from $25.0 million in Q1 2025, and up 63.82% on a QoQ basis from $26.9 million in Q4 2025.
Hyperscale Data (GPUS) has 17 years of Revenue data on file, last reported at $44.1 million in Q1 2026.
- Quarterly Revenue rose 76.17% year-over-year to $44.1 million in Q1 2026, while the trailing twelve-month figure through Mar 2026 was $121.2 million (up 29.85% YoY) and the FY2025 annual result came in at $102.1 million, down 4.27% from the prior year.
- Revenue improved to $44.1 million in Q1 2026 per GPUS's latest filing, from $26.9 million in the prior quarter.
- Across five years, Revenue topped out at $47.4 million in Q2 2023 and bottomed at $17.4 million in Q2 2022.
- The 5-year median for Revenue is $30.5 million (2022), against an average of $31.0 million.
- Peak annual rise in Revenue reached 289.72% in 2022, while the deepest fall reached 72.05% in 2022.
- Tracing GPUS's Revenue over 5 years: stood at $30.5 million in 2022, then advanced by 0.43% to $30.6 million in 2023, then slumped by 36.48% to $19.4 million in 2024, then jumped by 38.39% to $26.9 million in 2025, then surged by 63.82% to $44.1 million in 2026.
- Per Business Quant, the three latest GPUS Revenue figures stand at $44.1 million (Q1 2026), $26.9 million (Q4 2025), and $24.3 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Revenue (Qtr) |
|---|---|---|---|---|---|
| 1 | General Electric | 316.77 Bn | 306.03 Bn | 9.11 Bn | 12.39 Bn |
| 2 | Rtx | 238.61 Bn | 233.51 Bn | 9.08 Bn | 22.08 Bn |
| 3 | Boeing | 172.59 Bn | 151.68 Bn | 2.55 Bn | 22.22 Bn |
| 4 | Lockheed Martin | 122.59 Bn | 120.70 Bn | 2.08 Bn | 18.02 Bn |
| 5 | Howmet Aerospace | 102.88 Bn | 100.44 Bn | 854.00 Mn | 2.31 Bn |
| 6 | General Dynamics | 92.64 Bn | 88.99 Bn | 9.09 Bn | 13.48 Bn |
| 7 | Rocket Lab | 82.19 Bn | 80.92 Bn | 76.49 Mn | 200.35 Mn |
| 8 | Northrop Grumman | 78.95 Bn | 76.86 Bn | 3.45 Bn | 9.88 Bn |
| 9 | TransDigm | 70.63 Bn | 66.75 Bn | 1.51 Bn | 2.54 Bn |
| 10 | Hyperscale Data | 62.25 Mn | 31.87 Mn | 15.07 Mn | 44.08 Mn |
Historic Data
Download Data| Date | Value |
|---|---|
| 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 |
| Jun 30, 2021 | 62.13 Mn |
| Mar 31, 2021 | 13.25 Mn |
| Dec 31, 2020 | 7.19 Mn |
| Sep 30, 2020 | 5.68 Mn |
| Jun 30, 2020 | 5.40 Mn |
| Mar 31, 2020 | 5.61 Mn |
| Dec 31, 2019 | 6.26 Mn |
| Sep 30, 2019 | 5.34 Mn |
| Jun 30, 2019 | 4.99 Mn |
| Mar 31, 2019 | 5.77 Mn |
| Dec 31, 2018 | 6.17 Mn |
| Sep 30, 2018 | 8.34 Mn |
| Jun 30, 2018 | 7.44 Mn |
| Mar 31, 2018 | 5.20 Mn |
| Dec 31, 2017 | 3.50 Mn |
| Sep 30, 2017 | 3.22 Mn |
| Jun 30, 2017 | 1.82 Mn |
| Mar 31, 2017 | 1.63 Mn |
| Dec 31, 2016 | 1.99 Mn |
| Sep 30, 2016 | 1.83 Mn |
| Jun 30, 2016 | 2.06 Mn |
| Mar 31, 2016 | 1.71 Mn |
| Dec 31, 2015 | 2.30 Mn |
| Sep 30, 2015 | 1.42 Mn |
| Jun 30, 2015 | 2.15 Mn |
| Mar 31, 2015 | 1.90 Mn |
| Dec 31, 2014 | 2.11 Mn |
| Sep 30, 2014 | 2.23 Mn |
| Jun 30, 2014 | 2.64 Mn |
| Mar 31, 2014 | 2.04 Mn |
| Dec 31, 2013 | 2.27 Mn |
| Sep 30, 2013 | 2.09 Mn |
| Jun 30, 2013 | 2.23 Mn |
| Mar 31, 2013 | 2.19 Mn |
| Dec 31, 2012 | 1.73 Mn |
| Sep 30, 2012 | 1.68 Mn |
| Jun 30, 2012 | 2.94 Mn |
| Mar 31, 2012 | 2.24 Mn |
| Dec 31, 2011 | 2.06 Mn |
| Sep 30, 2011 | 3.02 Mn |
| Jun 30, 2011 | 3.17 Mn |
| Mar 31, 2011 | 2.98 Mn |
| Dec 31, 2010 | 3.07 Mn |
| Sep 30, 2010 | 3.19 Mn |
| Jun 30, 2010 | 2.17 Mn |