Globalfoundries (GFS) Total Liabilities (2019 - 2026)
Globalfoundries (GFS) reported Total Liabilities of $5.01 billion for Q2 2026, down 6.0% from $5.34 billion a year earlier and down 2.6% from the prior quarter.
Globalfoundries (GFS) Total Liabilities (2019 - 2026) Analysis & Trends
At the end of FY2025, Globalfoundries posted Total Liabilities of $5.16 billion, down 13.7% from FY2024.
- Total Liabilities has declined for three consecutive years, though with a five-year compound annual growth rate of 0.3% (FY2020 to FY2025).
- By year, Total Liabilities came in at $5.98 billion in FY2024 (-13.3%), $6.89 billion in FY2023 (-12.5%), $7.88 billion in FY2022 (+12.7%) and $7 billion in FY2021 (+37.7%).
- Five-year quarterly Total Liabilities spans a low of $4.94 billion in Q3 2025 and a high of $8.13 billion in Q3 2022.
- Year over year, Total Liabilities has now declined in each of the last 14 quarters, with an average decline of 14.1% over the last eight quarters.
- The high point for year-over-year Total Liabilities in five years was Q4 2021 (growth of 37.7%); the low point was Q1 2025 (a decline of 24.9%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $5.15 billion (Q1 2026), $5.16 billion (Q4 2025) and $4.94 billion (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Nvidia | 5,757.49 Bn | 5,531.65 Bn | 72.14 Bn | 91.29 Bn |
| 2 | Taiwan Semiconductor Manufacturing | 2,520.17 Bn | 2,145.88 Bn | 27.22 Bn | 93.12 Bn |
| 3 | Broadcom | 1,730.62 Bn | 1,656.67 Bn | 20.46 Bn | 88.46 Bn |
| 4 | Micron Technology | 1,201.21 Bn | 1,139.97 Bn | 35.06 Bn | 33.39 Bn |
| 5 | Advanced Micro Devices | 1,031.02 Bn | 987.76 Bn | 6.20 Bn | 17.24 Bn |
| 6 | Asml Holding | 716.82 Bn | 672.66 Bn | 5.90 Bn | 36.03 Bn |
| 7 | Intel | 585.95 Bn | 470.68 Bn | 6.51 Bn | 99.30 Bn |
| 8 | Lam Research | 432.69 Bn | 409.49 Bn | 3.48 Bn | 11.06 Bn |
| 9 | Applied Materials | 430.35 Bn | 395.79 Bn | 4.59 Bn | 17.90 Bn |
| 10 | Globalfoundries | 26.99 Bn | 15.36 Bn | 505.00 Mn | 5.01 Bn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 5.01 Bn |
| Mar 31, 2026 | 5.15 Bn |
| Dec 31, 2025 | 5.16 Bn |
| Sep 30, 2025 | 4.94 Bn |
| Jun 30, 2025 | 5.34 Bn |
| Mar 31, 2025 | 5.38 Bn |
| Dec 31, 2024 | 5.98 Bn |
| Sep 30, 2024 | 6.52 Bn |
| Jun 30, 2024 | 6.63 Bn |
| Mar 31, 2024 | 7.16 Bn |
| Dec 31, 2023 | 6.89 Bn |
| Sep 30, 2023 | 7.01 Bn |
| Jun 30, 2023 | 7.24 Bn |
| Mar 31, 2023 | 7.51 Bn |
| Dec 31, 2022 | 7.88 Bn |
| Sep 30, 2022 | 8.13 Bn |
| Jun 30, 2022 | 7.54 Bn |
| Mar 31, 2022 | 7.56 Bn |
| Dec 31, 2021 | 7.00 Bn |
| Dec 31, 2020 | 5.08 Bn |
Globalfoundries 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=GFS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "GFS", "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=GFS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();