Hyperscale Data (GPUS) Receivables - Net (2010 - 2026)
Hyperscale Data (GPUS) reported Receivables - Net of $17.0 million for Q1 2026, up 86.08% year-over-year from $9.2 million in Q1 2025, and up 17.09% on a QoQ basis from $14.5 million in Q4 2025.
Hyperscale Data (GPUS) has 17 years of Receivables - Net data on file, last reported at $17.0 million in Q1 2026.
- Quarterly Receivables - Net rose 86.08% year-over-year to $17.0 million in Q1 2026, while the trailing twelve-month figure through Mar 2026 was $17.0 million (up 86.08% YoY) and the FY2025 annual result came in at $14.5 million, up 962.67% from the prior year.
- Receivables - Net advanced to $17.0 million in Q1 2026 per GPUS's latest filing, from $14.5 million in the prior quarter.
- Across five years, Receivables - Net topped out at $24.7 million in Q3 2023 and bottomed at $1.2 million in Q3 2024.
- The 5-year median for Receivables - Net is $9.2 million (2025), against an average of $10.4 million.
- The widest annual swing landed in 2022, when Receivables - Net jumped 1508.19%; it then sank 95.26% in 2024.
- Tracing GPUS's Receivables - Net over 5 years: stood at $7.6 million in 2022, then plunged by 83.75% to $1.2 million in 2023, then climbed by 10.94% to $1.4 million in 2024, then surged by 962.67% to $14.5 million in 2025, then advanced by 17.09% to $17.0 million in 2026.
- Per Business Quant, the three latest GPUS Receivables - Net figures stand at $17.0 million (Q1 2026), $14.5 million (Q4 2025), and $6.7 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 | 17.03 Mn |
| Mar 31, 2026 | 17.03 Mn |
| Dec 31, 2025 | 14.55 Mn |
| Dec 31, 2025 | 14.55 Mn |
| Sep 30, 2025 | 6.69 Mn |
| Sep 30, 2025 | 6.69 Mn |
| Jun 30, 2025 | 2.69 Mn |
| Jun 30, 2025 | 2.69 Mn |
| Mar 31, 2025 | 9.15 Mn |
| Mar 31, 2025 | 9.15 Mn |
| Dec 31, 2024 | 1.37 Mn |
| Dec 31, 2024 | 1.37 Mn |
| Sep 30, 2024 | 6.82 Mn |
| Sep 30, 2024 | 6.82 Mn |
| Jun 30, 2024 | 1.36 Mn |
| Jun 30, 2024 | 1.36 Mn |
| Mar 31, 2024 | 11.58 Mn |
| Mar 31, 2024 | 11.58 Mn |
| Dec 31, 2023 | 6.74 Mn |
| Dec 31, 2023 | 6.74 Mn |
| Sep 30, 2023 | 24.65 Mn |
| Sep 30, 2023 | 24.65 Mn |
| Jun 30, 2023 | 13.53 Mn |
| Jun 30, 2023 | 13.53 Mn |
| Mar 31, 2023 | 14.48 Mn |
| Mar 31, 2023 | 14.48 Mn |
| Dec 31, 2022 | 19.32 Mn |
| Dec 31, 2022 | 19.32 Mn |
| Sep 30, 2022 | 19.23 Mn |
| Sep 30, 2022 | 19.23 Mn |
| Jun 30, 2022 | 18.08 Mn |
| Jun 30, 2022 | 18.08 Mn |
| Mar 31, 2022 | 6.98 Mn |
| Mar 31, 2022 | 6.98 Mn |
| Dec 31, 2021 | 6.46 Mn |
| Dec 31, 2021 | 6.46 Mn |
| Sep 30, 2021 | 1.20 Mn |
| Sep 30, 2021 | 1.20 Mn |
| Jun 30, 2021 | 1.20 Mn |
| Jun 30, 2021 | 1.20 Mn |
| Mar 31, 2021 | 3.51 Mn |
| Mar 31, 2021 | 3.51 Mn |
| Dec 31, 2020 | 3.85 Mn |
| Dec 31, 2020 | 3.85 Mn |
| Sep 30, 2020 | 3.03 Mn |
| Sep 30, 2020 | 3.03 Mn |
| Jun 30, 2020 | 1.20 Mn |
| Jun 30, 2020 | 1.20 Mn |
| Mar 31, 2020 | 1.20 Mn |
| Mar 31, 2020 | 1.20 Mn |
| Dec 31, 2019 | 2.44 Mn |
| Dec 31, 2019 | 2.44 Mn |
| Sep 30, 2019 | 2.47 Mn |
| Sep 30, 2019 | 2.47 Mn |
| Jun 30, 2019 | 1.24 Mn |
| Jun 30, 2019 | 1.24 Mn |
| Mar 31, 2019 | 3.92 Mn |
| Mar 31, 2019 | 3.92 Mn |
| Dec 31, 2018 | 3.89 Mn |
| Dec 31, 2018 | 3.89 Mn |
| Sep 30, 2018 | 5,000.00 |
| Sep 30, 2018 | 5,000.00 |
| Jun 30, 2018 | 5,000.00 |
| Jun 30, 2018 | 5,000.00 |
| Mar 31, 2018 | 1.97 Mn |
| Mar 31, 2018 | 1.97 Mn |
| Dec 31, 2017 | 1.90 Mn |
| Dec 31, 2017 | 1.90 Mn |
| Sep 30, 2017 | 2.89 Mn |
| Sep 30, 2017 | 2.89 Mn |
| Jun 30, 2017 | 1.25 Mn |
| Jun 30, 2017 | 1.25 Mn |
| Mar 31, 2017 | 1.03 Mn |
| Mar 31, 2017 | 1.03 Mn |
| Dec 31, 2016 | 1.44 Mn |
| Dec 31, 2016 | 1.44 Mn |
| Sep 30, 2016 | 1.11 Mn |
| Sep 30, 2016 | 1.11 Mn |
| Jun 30, 2016 | 1.21 Mn |
| Jun 30, 2016 | 1.21 Mn |
| Mar 31, 2016 | 1.26 Mn |
| Mar 31, 2016 | 1.26 Mn |
| Dec 31, 2015 | 1.24 Mn |
| Dec 31, 2015 | 1.24 Mn |
| Sep 30, 2015 | 979,000.00 |
| Sep 30, 2015 | 979,000.00 |
| Jun 30, 2015 | 1.05 Mn |
| Jun 30, 2015 | 1.05 Mn |
| Mar 31, 2015 | 1.03 Mn |
| Mar 31, 2015 | 1.03 Mn |
| Dec 31, 2014 | 1.55 Mn |
| Dec 31, 2014 | 1.55 Mn |
| Sep 30, 2014 | 2.05 Mn |
| Sep 30, 2014 | 2.05 Mn |
| Jun 30, 2014 | 1.63 Mn |
| Jun 30, 2014 | 1.63 Mn |
| Mar 31, 2014 | 1.49 Mn |
| Mar 31, 2014 | 1.49 Mn |
| Dec 31, 2013 | 2.16 Mn |
| Dec 31, 2013 | 2.16 Mn |
| Sep 30, 2013 | 2.32 Mn |
| Sep 30, 2013 | 2.32 Mn |
| Jun 30, 2013 | 2.05 Mn |
| Jun 30, 2013 | 2.05 Mn |
| Mar 31, 2013 | 2.04 Mn |
| Mar 31, 2013 | 2.04 Mn |
| Dec 31, 2012 | 1.39 Mn |
| Dec 31, 2012 | 1.39 Mn |
| Sep 30, 2012 | 1.75 Mn |
| Sep 30, 2012 | 1.75 Mn |
| Jun 30, 2012 | 2.33 Mn |
| Jun 30, 2012 | 2.33 Mn |
| Mar 31, 2012 | 1.52 Mn |
| Mar 31, 2012 | 1.52 Mn |
| Dec 31, 2011 | 1.85 Mn |
| Dec 31, 2011 | 1.85 Mn |
| Sep 30, 2011 | 2.51 Mn |
| Sep 30, 2011 | 2.51 Mn |
| Jun 30, 2011 | 2.09 Mn |
| Jun 30, 2011 | 2.09 Mn |
| Dec 31, 2010 | 2.40 Mn |
| Dec 31, 2010 | 2.40 Mn |