International Business Machines (IBM) Accumulated Expenses (2009 - 2026)
International Business Machines (IBM) posted Accumulated Expenses of $3.53 billion for Q3 2026, up 1.6% from $3.48 billion a year earlier and up 3.2% from the prior quarter.
Powered by 
Analysis
International Business Machines (IBM) Accumulated Expenses (2009 - 2026) Analysis & Trends
At the end of FY2025, International Business Machines' Accumulated Expenses came in at $4.12 billion, up 11.0% from FY2024.
- Annual Accumulated Expenses shows a five-year compound annual growth rate of -6.1% (FY2020 to FY2025).
- In prior years, International Business Machines' Accumulated Expenses was $3.71 billion in FY2024 (+5.3%), $3.52 billion in FY2023 (-14.4%), $4.11 billion in FY2022 (+5.6%) and $3.89 billion in FY2021 (-30.9%).
- Quarterly Accumulated Expenses has run from a low of $3.2 billion in Q2 2024 to a high of $4.12 billion in Q4 2025 over five years.
- On a year-over-year basis, Accumulated Expenses increased in six of the last eight quarters, with growth averaging 3.5%.
- The strongest year-over-year quarter for Accumulated Expenses in the past five years was Q2 2025, with growth of 23.1%; the weakest was Q1 2022, with a decline of 35.9%.
- According to Business Quant data, Accumulated Expenses for the three prior quarters was $3.43 billion (Q2 2026), $3.58 billion (Q1 2026) and $4.12 billion (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Microsoft | 3,890.86 Bn | 3,826.35 Bn | 62.56 Bn |
| 2 | International Business Machines | 233.55 Bn | 188.83 Bn | 9.71 Bn |
| 3 | Cloudflare | 109.18 Bn | 91.62 Bn | 557.23 Mn |
| 4 | Equinix | 104.31 Bn | 92.20 Bn | 1.31 Bn |
| 5 | CoreWeave | 29.43 Bn | 14.28 Bn | 2.48 Bn |
| 6 | Nebius | 29.32 Bn | 122.11 Mn | 761.10 Mn |
| 7 | Verisign | 28.11 Bn | 25.46 Bn | 393.20 Mn |
| 8 | Nutanix | 16.34 Bn | 8.02 Bn | 651.35 Mn |
| 9 | GoDaddy | 13.97 Bn | 9.35 Bn | 843.00 Mn |
| 10 | Akamai Technologies | 12.30 Bn | 3.31 Bn | 617.27 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 3.53 Bn |
| Jun 30, 2026 | 3.43 Bn |
| Mar 31, 2026 | 3.58 Bn |
| Dec 31, 2025 | 4.12 Bn |
| Sep 30, 2025 | 3.48 Bn |
| Jun 30, 2025 | 3.93 Bn |
| Mar 31, 2025 | 3.53 Bn |
| Dec 31, 2024 | 3.71 Bn |
| Sep 30, 2024 | 3.47 Bn |
| Jun 30, 2024 | 3.20 Bn |
| Mar 31, 2024 | 3.61 Bn |
| Dec 31, 2023 | 3.52 Bn |
| Sep 30, 2023 | 3.31 Bn |
| Jun 30, 2023 | 3.65 Bn |
| Mar 31, 2023 | 3.87 Bn |
| Dec 31, 2022 | 4.11 Bn |
| Sep 30, 2022 | 3.70 Bn |
| Jun 30, 2022 | 3.68 Bn |
| Mar 31, 2022 | 3.70 Bn |
| Dec 31, 2021 | 3.89 Bn |
API Access
International Business Machines 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=IBM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "IBM", "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=IBM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();