Super Micro Computer (SMCI) Accumulated Expenses (2011 - 2026)
Super Micro Computer's Accumulated Expenses came in at $1.03 billion for fiscal Q4 2026 (quarter ended Jun 30, 2026), up 82.6% from $565.64 million a year earlier and up 24.4% from the prior quarter.
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Analysis
Super Micro Computer (SMCI) Accumulated Expenses (2011 - 2026) Analysis & Trends
Going back to fiscal Q4 2011, Super Micro Computer's Accumulated Expenses data covers 58 quarters.
- Accumulated Expenses has increased in each of the last three fiscal years, with a five-year compound annual growth rate of 42.0% (FY2021 to FY2026).
- Going back by fiscal year, Accumulated Expenses was $565.64 million in FY2025 (+117.8%), $259.67 million in FY2024 (+58.5%), $163.87 million in FY2023 (-22.9%) and $212.42 million in FY2022 (+18.8%).
- The fiscal Q4 2026 figure represents the highest quarterly Accumulated Expenses in data going back to fiscal Q4 2011.
- Year-over-year, Accumulated Expenses has increased for 11 consecutive quarters, with growth averaging 76.2% over the last eight quarters.
- The fastest year-over-year change in Accumulated Expenses over five years came in fiscal Q3 2026 (growth of 140.8%), and the weakest in fiscal Q1 2024 (a decline of 28.6%).
- Business Quant data shows SMCI's Accumulated Expenses at $830.01 million (Q3 2026), $548.18 million (Q2 2026) and $313.39 million (Q1 2026) in the three fiscal quarters before Q4 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Apple | 5,028.22 Bn | 4,775.71 Bn | 54.77 Bn |
| 2 | Cisco Systems | 420.88 Bn | 356.80 Bn | 11.06 Bn |
| 3 | Dell Technologies | 293.18 Bn | 248.94 Bn | 9.83 Bn |
| 4 | Arista Networks | 230.46 Bn | 183.91 Bn | 1.91 Bn |
| 5 | Sandisk | 201.65 Bn | 190.18 Bn | 7.58 Bn |
| 6 | Sony | 148.11 Bn | 85.38 Bn | 6.53 Bn |
| 7 | Seagate Technology Holdings | 144.57 Bn | 139.56 Bn | 1.90 Bn |
| 8 | Western Digital | 121.56 Bn | 109.69 Bn | 2.03 Bn |
| 9 | Hewlett Packard Enterprise | 74.47 Bn | 52.35 Bn | 4.93 Bn |
| 10 | Super Micro Computer | 19.31 Bn | 2.21 Bn | 1.94 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.03 Bn |
| Mar 31, 2026 | 830.01 Mn |
| Dec 31, 2025 | 548.18 Mn |
| Sep 30, 2025 | 313.39 Mn |
| Jun 30, 2025 | 565.64 Mn |
| Mar 31, 2025 | 344.68 Mn |
| Dec 31, 2024 | 229.15 Mn |
| Sep 30, 2024 | 308.78 Mn |
| Jun 30, 2024 | 259.67 Mn |
| Mar 31, 2024 | 290.37 Mn |
| Dec 31, 2023 | 214.46 Mn |
| Sep 30, 2023 | 152.50 Mn |
| Jun 30, 2023 | 163.87 Mn |
| Mar 31, 2023 | 155.22 Mn |
| Dec 31, 2022 | 169.87 Mn |
| Sep 30, 2022 | 213.52 Mn |
| Jun 30, 2022 | 212.42 Mn |
| Mar 31, 2022 | 181.45 Mn |
| Dec 31, 2021 | 171.01 Mn |
| Sep 30, 2021 | 175.22 Mn |
API Access
Super Micro Computer Accumulated 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=accumulated-expenses&ticker=SMCI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "SMCI", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=accumulated-expenses&ticker=SMCI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();