Faraday Future Intelligent Electric (FFAI) Total Liabilities (2020 - 2026)
Faraday Future Intelligent Electric's Total Liabilities came in at $307.09 million for Q2 2026, down 9.6% from $339.87 million a year earlier.
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Analysis
Faraday Future Intelligent Electric (FFAI) Total Liabilities (2020 - 2026) Analysis & Trends
At the end of FY2025, Faraday Future Intelligent Electric's Total Liabilities was $305.2 million, down 1.7% from FY2024.
- Total Liabilities carries a five-year compound annual growth rate of -19.4% (FY2020 to FY2025).
- Going back by year, Total Liabilities was $310.43 million in FY2024 (+2.7%), $302.3 million in FY2023 (-7.9%), $328.3 million in FY2022 (-3.4%) and $339.78 million in FY2021 (-62.1%).
- The five-year range for quarterly Total Liabilities is $252.94 million (Q3 2022) to $393.33 million (Q3 2025).
- Year-over-year, Total Liabilities increased in three of the last seven quarters, with growth averaging 2.7%.
- The fastest year-over-year change in Total Liabilities over five years came in Q3 2025 (growth of 34.5%), and the weakest in Q1 2022 (a decline of 65.3%).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Tesla | 1,148.52 Bn | 983.08 Bn | 4.75 Bn | 61.06 Bn |
| 2 | Toyota Motor | 242.17 Bn | -164.57 Bn | 20.95 Bn | 404.08 Bn |
| 3 | Ferrari | 145.86 Bn | 138.30 Bn | 1.18 Bn | 7.62 Bn |
| 4 | Honda Motor | 143.38 Bn | 10.76 Bn | 8.46 Bn | 136.83 Bn |
| 5 | General Motors | 67.56 Bn | -37.30 Bn | 7.33 Bn | 219.10 Bn |
| 6 | Ford Motor | 47.24 Bn | -95.23 Bn | 6.08 Bn | 249.78 Bn |
| 7 | Rivian Automotive | 20.35 Bn | -2.94 Bn | 179.00 Mn | 10.01 Bn |
| 8 | Magna International | 17.85 Bn | 15.41 Bn | 1.61 Bn | - |
| 9 | Stellantis | 12.63 Bn | -153.36 Bn | 5.55 Bn | 176.31 Bn |
| 10 | Faraday Future Intelligent Electric | 8.88 Mn | -84.68 Mn | -10.70 Mn | 307.09 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 307.09 Mn |
| Dec 31, 2025 | 305.20 Mn |
| Sep 30, 2025 | 393.33 Mn |
| Jun 30, 2025 | 339.87 Mn |
| Mar 31, 2025 | 270.78 Mn |
| Dec 31, 2024 | 310.43 Mn |
| Sep 30, 2024 | 292.33 Mn |
| Jun 30, 2024 | 309.21 Mn |
| Mar 31, 2024 | 298.42 Mn |
| Dec 31, 2023 | 302.30 Mn |
| Sep 30, 2023 | 317.72 Mn |
| Jun 30, 2023 | 289.79 Mn |
| Mar 31, 2023 | 320.16 Mn |
| Dec 31, 2022 | 328.30 Mn |
| Sep 30, 2022 | 252.94 Mn |
| Jun 30, 2022 | 319.74 Mn |
| Mar 31, 2022 | 303.74 Mn |
| Dec 31, 2021 | 339.78 Mn |
| Sep 30, 2021 | 377.94 Mn |
| Jun 30, 2021 | 782.67 Mn |
API Access
Faraday Future Intelligent Electric 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=FFAI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "FFAI", "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=FFAI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();