International Business Machines (IBM) Total Liabilities (2009 - 2026)
International Business Machines (IBM) reported Total Liabilities of $118.81 billion for Q3 2026, up 0.4% from $118.32 billion a year earlier and up 1.1% from the prior quarter.
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Analysis
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%).
- Five-year quarterly Total Liabilities spans a low of $105.22 billion in Q4 2022 and a high of $123.17 billion in Q1 2026.
- Year over year, Total Liabilities gained in six of the last eight quarters, with growth averaging 3.7%.
- 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 Q3 2026 came in at $117.56 billion (Q2 2026), $123.17 billion (Q1 2026) and $119.14 billion (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Microsoft | 3,890.86 Bn | 3,826.35 Bn | 62.56 Bn | 308.89 Bn |
| 2 | International Business Machines | 233.55 Bn | 188.83 Bn | 9.71 Bn | 118.81 Bn |
| 3 | Cloudflare | 109.18 Bn | 91.62 Bn | 557.23 Mn | 6.23 Bn |
| 4 | Equinix | 104.31 Bn | 92.20 Bn | 1.31 Bn | 29.91 Bn |
| 5 | CoreWeave | 29.43 Bn | 14.28 Bn | 2.48 Bn | 87.46 Bn |
| 6 | Nebius | 29.32 Bn | 122.11 Mn | 761.10 Mn | 26.44 Bn |
| 7 | Verisign | 28.11 Bn | 25.46 Bn | 393.20 Mn | 3.56 Bn |
| 8 | Nutanix | 16.34 Bn | 8.02 Bn | 651.35 Mn | 4.37 Bn |
| 9 | GoDaddy | 13.97 Bn | 9.35 Bn | 843.00 Mn | 8.05 Bn |
| 10 | Akamai Technologies | 12.30 Bn | 3.31 Bn | 617.27 Mn | 10.40 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 118.81 Bn |
| 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 |
API Access
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_KEYimport 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();