International Business Machines (IBM) Total Liabilities (2009 - 2026)
International Business Machines (IBM) reported Total Liabilities of $117.56 billion for Q2 2026, down 2.8% from $121 billion a year earlier and down 4.6% from the prior quarter.
International Business Machines (IBM) Total Liabilities (2009 - 2026) Analysis & Trends
At the end of FY2025, International Business Machines posted Total Liabilities of $119.14 billion, up 8.5% from FY2024.
- Total Liabilities has a five-year compound annual growth rate of -2.5% (FY2020 to FY2025).
- By year, Total Liabilities came in at $109.78 billion in FY2024 (-2.5%), $112.63 billion in FY2023 (+7.0%), $105.22 billion in FY2022 (-6.9%) and $113.01 billion in FY2021 (-16.4%).
- The Q2 2026 figure ranks as the lowest quarterly Total Liabilities since Q4 2024.
- Year over year, Total Liabilities gained in six of the last eight quarters, with growth averaging 4.1%.
- The high point for year-over-year Total Liabilities in five years was Q2 2025 (growth of 10.3%); the low point was Q4 2021 (a decline of 16.4%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $123.17 billion (Q1 2026), $119.14 billion (Q4 2025) and $118.32 billion (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Microsoft | 3,843.70 Bn | 3,766.85 Bn | 60.48 Bn | 315.99 Bn |
| 2 | International Business Machines | 209.74 Bn | 160.64 Bn | 9.91 Bn | 117.56 Bn |
| 3 | Cloudflare | 112.41 Bn | 95.94 Bn | 499.52 Mn | 4.85 Bn |
| 4 | Equinix | 101.21 Bn | 89.76 Bn | 1.40 Bn | 26.69 Bn |
| 5 | Nebius | 61.44 Bn | 34.87 Bn | 448.70 Mn | 17.62 Bn |
| 6 | CoreWeave | 49.38 Bn | 36.47 Bn | 1.70 Bn | 72.05 Bn |
| 7 | Verisign | 26.06 Bn | 23.28 Bn | 384.60 Mn | 4.06 Bn |
| 8 | Nutanix | 19.56 Bn | 11.24 Bn | 651.35 Mn | 4.37 Bn |
| 9 | Akamai Technologies | 15.64 Bn | 9.05 Bn | 613.75 Mn | 10.32 Bn |
| 10 | DigitalOcean Holdings | 14.71 Bn | 12.71 Bn | 154.66 Mn | 2.19 Bn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 117.56 Bn |
| Mar 31, 2026 | 123.17 Bn |
| Dec 31, 2025 | 119.14 Bn |
| Sep 30, 2025 | 118.32 Bn |
| Jun 30, 2025 | 121.00 Bn |
| Mar 31, 2025 | 118.71 Bn |
| Dec 31, 2024 | 109.78 Bn |
| Sep 30, 2024 | 109.81 Bn |
| Jun 30, 2024 | 109.75 Bn |
| Mar 31, 2024 | 113.84 Bn |
| Dec 31, 2023 | 112.63 Bn |
| Sep 30, 2023 | 106.17 Bn |
| Jun 30, 2023 | 109.94 Bn |
| Mar 31, 2023 | 111.97 Bn |
| Dec 31, 2022 | 105.22 Bn |
| Sep 30, 2022 | 105.70 Bn |
| Jun 30, 2022 | 108.03 Bn |
| Mar 31, 2022 | 114.16 Bn |
| Dec 31, 2021 | 113.01 Bn |
| Sep 30, 2021 | 121.86 Bn |
International Business Machines Total Liabilities 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=total-liabilities&ticker=IBM&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "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=total-liabilities&ticker=IBM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();