Axe Compute (AGPU) Operating Expenses (2010 - 2019)
Axe Compute's Operating Expenses came in at $135,591 for FY2024, down 37.9% from $218,325 in FY2023.
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Analysis
Axe Compute (AGPU) Operating Expenses (2010 - 2019) Analysis & Trends
Going back to FY2010, Axe Compute's Operating Expenses data covers 12 years.
- The FY2024 figure represents the lowest annual Operating Expenses in data going back to FY2010.
- Per Business Quant, earlier years put Operating Expenses at $218,325 in FY2023 (-75.7%) and $898,369 in FY2022.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Microsoft | 3,781.98 Bn | 3,705.13 Bn | 60.48 Bn | 12.28 Bn |
| 2 | International Business Machines | 207.92 Bn | 158.82 Bn | 9.91 Bn | 7.29 Bn |
| 3 | Cloudflare | 114.07 Bn | 97.60 Bn | 499.52 Mn | 705.21 Mn |
| 4 | Equinix | 99.76 Bn | 88.32 Bn | 1.40 Bn | 1.96 Bn |
| 5 | Nebius | 58.67 Bn | 32.10 Bn | 448.70 Mn | 758.20 Mn |
| 6 | CoreWeave | 46.87 Bn | 33.97 Bn | 1.70 Bn | 2.62 Bn |
| 7 | Verisign | 25.50 Bn | 22.71 Bn | 384.60 Mn | 138.30 Mn |
| 8 | Nutanix | 18.59 Bn | 10.27 Bn | 651.35 Mn | 581.36 Mn |
| 9 | Akamai Technologies | 15.65 Bn | 9.06 Bn | 613.75 Mn | 1.02 Bn |
| 10 | Axe Compute | 239.18 Mn | 199.38 Mn | - | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Mar 31, 2019 | 2.34 Mn |
| Dec 31, 2018 | 6.47 Mn |
| Sep 30, 2018 | 723,939.00 |
| Jun 30, 2018 | 378,906.00 |
| Mar 31, 2018 | 1.79 Mn |
| Dec 31, 2017 | 5.48 Mn |
| Sep 30, 2017 | 192,536.00 |
| Jun 30, 2017 | 182,507.00 |
| Mar 31, 2017 | 200,494.00 |
| Dec 31, 2016 | 230,055.00 |
| Sep 30, 2016 | 292,856.00 |
| Jun 30, 2016 | 244,840.00 |
| Mar 31, 2016 | 390,366.00 |
| Dec 31, 2015 | 471,258.00 |
| Sep 30, 2015 | 202,799.00 |
| Jun 30, 2015 | 151,313.00 |
| Mar 31, 2015 | 21,317.00 |
| Dec 31, 2014 | 232,818.00 |
| Sep 30, 2014 | 183,154.00 |
| Jun 30, 2014 | 291,584.00 |
API Access
Axe Compute Operating Expenses 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=operating-expenses&ticker=AGPU&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "AGPU", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=AGPU&period=max&api_key=YOUR_API_KEY");
const data = await res.json();