Microsoft (MSFT) Accumulated Expenses (2009 - 2026)
Microsoft's (MSFT) quarterly Accumulated Expenses came in at $14.9 billion in Q2 2026, up 9.02% year-over-year from $13.7 billion in Q2 2025, and up 32.61% quarter-over-quarter from $11.3 billion in Q1 2026.
Microsoft (MSFT) Accumulated Expenses (2009 - 2026) Analysis & Trends
Microsoft has disclosed Accumulated Expenses across 18 years of filings, most recently posting $14.9 billion for Q2 2026.
- In Q2 2026, Accumulated Expenses rose 9.02% year-over-year to $14.9 billion; the TTM figure through Jun 2026 stood at $14.9 billion (up 9.02% YoY), while the FY2026 annual figure was $14.9 billion, up 9.02% from the prior year.
- Accumulated Expenses came in at $14.9 billion for Q2 2026 at Microsoft, up from $11.3 billion in the prior quarter.
- In the past five years, Accumulated Expenses ranged from a high of $14.9 billion in Q2 2026 to a low of $7.0 billion in Q3 2023.
- Average Accumulated Expenses over 5 years is $10.2 billion, with a median of $10.3 billion recorded in 2023.
- Year-over-year, Accumulated Expenses slipped 5.6% in 2023 and gained 19.11% in 2024.
- Over 5 years, Accumulated Expenses stood at $9.0 billion in 2022, then dropped by 2.4% to $8.8 billion in 2023, then rose by 4.12% to $9.2 billion in 2024, then increased by 10.1% to $10.1 billion in 2025, then surged by 47.93% to $14.9 billion in 2026.
- Per Business Quant data, the three most recent Accumulated Expenses figures were $14.9 billion in Q2 2026, $11.3 billion in Q1 2026, and $10.1 billion in Q4 2025.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Microsoft | 3,717.88 Bn | 3,585.13 Bn | 60.48 Bn |
| 2 | International Business Machines | 219.37 Bn | 208.10 Bn | 9.91 Bn |
| 3 | Cloudflare | 113.46 Bn | 109.29 Bn | 499.52 Mn |
| 4 | Equinix | 102.39 Bn | 100.19 Bn | 1.40 Bn |
| 5 | Nebius | 57.34 Bn | 49.30 Bn | 448.70 Mn |
| 6 | CoreWeave | 47.88 Bn | 42.34 Bn | 1.70 Bn |
| 7 | Verisign | 26.51 Bn | 25.48 Bn | 384.60 Mn |
| 8 | Nutanix | 18.85 Bn | 16.49 Bn | 651.35 Mn |
| 9 | Akamai Technologies | 17.01 Bn | 13.65 Bn | 613.75 Mn |
| 10 | DigitalOcean Holdings | 14.83 Bn | 14.06 Bn | 154.66 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 14.95 Bn |
| Mar 31, 2026 | 11.27 Bn |
| Dec 31, 2025 | 10.10 Bn |
| Sep 30, 2025 | 9.20 Bn |
| Jun 30, 2025 | 13.71 Bn |
| Mar 31, 2025 | 10.58 Bn |
| Dec 31, 2024 | 9.18 Bn |
| Sep 30, 2024 | 8.33 Bn |
| Jun 30, 2024 | 12.56 Bn |
| Mar 31, 2024 | 10.43 Bn |
| Dec 31, 2023 | 8.81 Bn |
| Sep 30, 2023 | 6.99 Bn |
| Jun 30, 2023 | 11.01 Bn |
| Mar 31, 2023 | 10.41 Bn |
| Dec 31, 2022 | 9.03 Bn |
| Sep 30, 2022 | 7.41 Bn |
| Jun 30, 2022 | 10.66 Bn |
| Mar 31, 2022 | 9.07 Bn |
| Dec 31, 2021 | 7.78 Bn |
| Sep 30, 2021 | 6.89 Bn |
Microsoft 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=MSFT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "MSFT", "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=MSFT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();