Hyperscale Data (GPUS) Prepaid Assets (2010 - 2026)
Hyperscale Data (GPUS) reported Prepaid Assets of $16.3 million for Q1 2026, up 564.64% year-over-year from $2.4 million in Q1 2025, and up 10.49% on a QoQ basis from $14.7 million in Q4 2025.
Hyperscale Data (GPUS) has 17 years of Prepaid Assets data on file, last reported at $16.3 million in Q1 2026.
- Quarterly Prepaid Assets rose 564.64% year-over-year to $16.3 million in Q1 2026, while the trailing twelve-month figure through Mar 2026 was $16.3 million (up 564.64% YoY) and the FY2025 annual result came in at $14.7 million, up 382.07% from the prior year.
- Prepaid Assets advanced to $16.3 million in Q1 2026 per GPUS's latest filing, from $14.7 million in the prior quarter.
- Across five years, Prepaid Assets topped out at $16.7 million in Q2 2023 and bottomed at $2.4 million in Q1 2025.
- The 5-year median for Prepaid Assets is $8.0 million (2024), against an average of $8.9 million.
- The widest annual swing landed in 2025, when Prepaid Assets slumped 69.52%; it then surged 564.64% in 2026.
- Tracing GPUS's Prepaid Assets over 5 years: stood at $5.1 million in 2022, then rose by 3.41% to $5.2 million in 2023, then plunged by 41.76% to $3.1 million in 2024, then jumped by 382.07% to $14.7 million in 2025, then climbed by 10.49% to $16.3 million in 2026.
- Per Business Quant, the three latest GPUS Prepaid Assets figures stand at $16.3 million (Q1 2026), $14.7 million (Q4 2025), and $4.0 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | General Electric | 316.77 Bn | 306.03 Bn | 9.11 Bn |
| 2 | Rtx | 238.61 Bn | 233.51 Bn | 9.08 Bn |
| 3 | Boeing | 172.59 Bn | 151.68 Bn | 2.55 Bn |
| 4 | Lockheed Martin | 122.59 Bn | 120.70 Bn | 2.08 Bn |
| 5 | Howmet Aerospace | 102.88 Bn | 100.44 Bn | 854.00 Mn |
| 6 | General Dynamics | 92.64 Bn | 88.99 Bn | 9.09 Bn |
| 7 | Rocket Lab | 82.19 Bn | 80.92 Bn | 76.49 Mn |
| 8 | Northrop Grumman | 78.95 Bn | 76.86 Bn | 3.45 Bn |
| 9 | TransDigm | 70.63 Bn | 66.75 Bn | 1.51 Bn |
| 10 | Hyperscale Data | 62.25 Mn | 31.87 Mn | 15.07 Mn |
Historic Data
Download Data| Date | Value |
|---|---|
| Mar 31, 2026 | 16.28 Mn |
| Dec 31, 2025 | 14.73 Mn |
| Sep 30, 2025 | 3.96 Mn |
| Jun 30, 2025 | 2.56 Mn |
| Mar 31, 2025 | 2.45 Mn |
| Dec 31, 2024 | 3.06 Mn |
| Sep 30, 2024 | 4.24 Mn |
| Jun 30, 2024 | 8.29 Mn |
| Mar 31, 2024 | 8.04 Mn |
| Dec 31, 2023 | 5.25 Mn |
| Sep 30, 2023 | 8.71 Mn |
| Jun 30, 2023 | 16.75 Mn |
| Mar 31, 2023 | 16.18 Mn |
| Dec 31, 2022 | 5.07 Mn |
| Sep 30, 2022 | 14.44 Mn |
| Jun 30, 2022 | 13.73 Mn |
| Mar 31, 2022 | 8.00 Mn |
| Dec 31, 2021 | 15.44 Mn |
| Sep 30, 2021 | 7.99 Mn |
| Jun 30, 2021 | 5.37 Mn |
| Mar 31, 2021 | 2.92 Mn |
| Dec 31, 2020 | 2.99 Mn |
| Sep 30, 2020 | 2.04 Mn |
| Jun 30, 2020 | 1.11 Mn |
| Mar 31, 2020 | 1.19 Mn |
| Dec 31, 2019 | 1.32 Mn |
| Sep 30, 2019 | 706,967.00 |
| Jun 30, 2019 | 803,880.00 |
| Mar 31, 2019 | 802,429.00 |
| Dec 31, 2018 | 775,981.00 |
| Sep 30, 2018 | 2.05 Mn |
| Mar 31, 2018 | 2.70 Mn |
| Dec 31, 2017 | 1.41 Mn |
| Sep 30, 2017 | 603,000.00 |
| Jun 30, 2017 | 359,000.00 |
| Mar 31, 2017 | 272,000.00 |
| Dec 31, 2016 | 285,000.00 |
| Sep 30, 2016 | 239,000.00 |
| Jun 30, 2016 | 127,000.00 |
| Mar 31, 2016 | 180,000.00 |
| Dec 31, 2015 | 187,000.00 |
| Sep 30, 2015 | 229,000.00 |
| Jun 30, 2015 | 224,000.00 |
| Mar 31, 2015 | 238,000.00 |
| Dec 31, 2014 | 178,000.00 |
| Sep 30, 2014 | 212,000.00 |
| Jun 30, 2014 | 228,000.00 |
| Mar 31, 2014 | 205,000.00 |
| Dec 31, 2013 | 167,000.00 |
| Sep 30, 2013 | 186,000.00 |
| Jun 30, 2013 | 224,000.00 |
| Mar 31, 2013 | 186,000.00 |
| Dec 31, 2012 | 139,000.00 |
| Sep 30, 2012 | 143,000.00 |
| Jun 30, 2012 | 146,000.00 |
| Mar 31, 2012 | 135,000.00 |
| Dec 31, 2011 | 108,000.00 |
| Sep 30, 2011 | 145,000.00 |
| Jun 30, 2011 | 134,000.00 |
| Dec 31, 2010 | 157,000.00 |