Hyperscale Data (GPUS) Inventory (2010 - 2026)
Hyperscale Data (GPUS) reported Inventory of $5.2 million for Q1 2026, up 253.77% year-over-year from $1.5 million in Q1 2025, and up 7.19% on a QoQ basis from $4.8 million in Q4 2025.
Hyperscale Data (GPUS) has 17 years of Inventory data on file, last reported at $5.2 million in Q1 2026.
- Quarterly Inventory rose 253.77% year-over-year to $5.2 million in Q1 2026, while the trailing twelve-month figure through Mar 2026 was $5.2 million (up 253.77% YoY) and the FY2025 annual result came in at $4.8 million, up 164.83% from the prior year.
- Inventory rose to $5.2 million in Q1 2026 per GPUS's latest filing, from $4.8 million in the prior quarter.
- Across five years, Inventory topped out at $28.8 million in Q3 2022 and bottomed at $1.5 million in Q1 2025.
- The 5-year median for Inventory is $7.1 million (2022), against an average of $10.5 million.
- The widest annual swing landed in 2022, when Inventory jumped 650.86%; it then plunged 91.89% in 2024.
- Tracing GPUS's Inventory over 5 years: stood at $22.0 million in 2022, then tumbled by 91.88% to $1.8 million in 2023, then advanced by 1.51% to $1.8 million in 2024, then jumped by 164.83% to $4.8 million in 2025, then grew by 7.19% to $5.2 million in 2026.
- Per Business Quant, the three latest GPUS Inventory figures stand at $5.2 million (Q1 2026), $4.8 million (Q4 2025), and $1.7 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Inventory (Qtr) |
|---|---|---|---|---|---|
| 1 | General Electric | 316.77 Bn | 306.03 Bn | 9.11 Bn | 12.37 Bn |
| 2 | Rtx | 238.61 Bn | 233.51 Bn | 9.08 Bn | 14.15 Bn |
| 3 | Boeing | 172.59 Bn | 151.68 Bn | 2.55 Bn | 87.23 Bn |
| 4 | Lockheed Martin | 122.59 Bn | 120.70 Bn | 2.08 Bn | 4.25 Bn |
| 5 | Howmet Aerospace | 102.88 Bn | 100.44 Bn | 854.00 Mn | 1.98 Bn |
| 6 | General Dynamics | 92.64 Bn | 88.99 Bn | 9.09 Bn | 9.18 Bn |
| 7 | Rocket Lab | 82.19 Bn | 80.92 Bn | 76.49 Mn | 183.15 Mn |
| 8 | Northrop Grumman | 78.95 Bn | 76.86 Bn | 3.45 Bn | 1.45 Bn |
| 9 | TransDigm | 70.63 Bn | 66.75 Bn | 1.51 Bn | 2.40 Bn |
| 10 | Hyperscale Data | 62.25 Mn | 31.87 Mn | 15.07 Mn | 5.16 Mn |
Historic Data
Download Data| Date | Value |
|---|---|
| Mar 31, 2026 | 5.16 Mn |
| Dec 31, 2025 | 4.81 Mn |
| Sep 30, 2025 | 1.74 Mn |
| Jun 30, 2025 | 1.50 Mn |
| Mar 31, 2025 | 1.46 Mn |
| Dec 31, 2024 | 1.82 Mn |
| Sep 30, 2024 | 1.82 Mn |
| Jun 30, 2024 | 7.50 Mn |
| Mar 31, 2024 | 7.60 Mn |
| Dec 31, 2023 | 1.79 Mn |
| Sep 30, 2023 | 22.48 Mn |
| Jun 30, 2023 | 21.00 Mn |
| Mar 31, 2023 | 20.20 Mn |
| Dec 31, 2022 | 22.04 Mn |
| Sep 30, 2022 | 28.85 Mn |
| Jun 30, 2022 | 20.83 Mn |
| Mar 31, 2022 | 7.14 Mn |
| Dec 31, 2021 | 5.48 Mn |
| Sep 30, 2021 | 3.84 Mn |
| Jun 30, 2021 | 2.90 Mn |
| Mar 31, 2021 | 3.48 Mn |
| Dec 31, 2020 | 3.37 Mn |
| Sep 30, 2020 | 2.67 Mn |
| Jun 30, 2020 | 2.49 Mn |
| Mar 31, 2020 | 2.40 Mn |
| Dec 31, 2019 | 2.48 Mn |
| Sep 30, 2019 | 2.72 Mn |
| Jun 30, 2019 | 2.73 Mn |
| Mar 31, 2019 | 2.86 Mn |
| Dec 31, 2018 | 3.26 Mn |
| Sep 30, 2018 | 3.73 Mn |
| Mar 31, 2018 | 2.24 Mn |
| Dec 31, 2017 | 1.99 Mn |
| Sep 30, 2017 | 1.86 Mn |
| Jun 30, 2017 | 1.61 Mn |
| Mar 31, 2017 | 937,000.00 |
| Dec 31, 2016 | 1.12 Mn |
| Sep 30, 2016 | 1.19 Mn |
| Jun 30, 2016 | 1.20 Mn |
| Mar 31, 2016 | 1.43 Mn |
| Dec 31, 2015 | 1.54 Mn |
| Sep 30, 2015 | 1.92 Mn |
| Jun 30, 2015 | 1.91 Mn |
| Mar 31, 2015 | 1.87 Mn |
| Dec 31, 2014 | 1.65 Mn |
| Sep 30, 2014 | 1.83 Mn |
| Jun 30, 2014 | 1.44 Mn |
| Mar 31, 2014 | 1.70 Mn |
| Dec 31, 2013 | 1.75 Mn |
| Sep 30, 2013 | 1.82 Mn |
| Jun 30, 2013 | 1.79 Mn |
| Mar 31, 2013 | 1.81 Mn |
| Dec 31, 2012 | 2.01 Mn |
| Sep 30, 2012 | 2.17 Mn |
| Jun 30, 2012 | 1.89 Mn |
| Mar 31, 2012 | 2.01 Mn |
| Dec 31, 2011 | 2.33 Mn |
| Sep 30, 2011 | 1.85 Mn |
| Jun 30, 2011 | 1.75 Mn |
| Dec 31, 2010 | 1.77 Mn |