Joby Aviation (JOBY) Total Non-Current Liabilities (2020 - 2026)
Joby Aviation (JOBY) recorded Total Non-Current Liabilities of $889.89 million in Q2 2026, up 339.7% from $202.39 million a year earlier and up 0.8% from the prior quarter.
Joby Aviation (JOBY) Total Non-Current Liabilities (2020 - 2026) Analysis & Trends
At the end of FY2025, Joby Aviation reported Total Non-Current Liabilities of $228.66 million, up 31.7% from FY2024.
- Annual Total Non-Current Liabilities has increased for four straight years, though with a five-year compound annual growth rate of -21.7% (FY2020 to FY2025).
- Across earlier years, Total Non-Current Liabilities came in at $173.69 million in FY2024 (+24.9%), $139.1 million in FY2023 (+65.2%), $84.19 million in FY2022 (+36.3%) and $61.75 million in FY2021 (-92.1%).
- The Q2 2026 figure is the highest quarterly Total Non-Current Liabilities since Q2 2021.
- On a year-over-year basis, Total Non-Current Liabilities has increased for seven consecutive quarters, with growth averaging 139.8% over the last eight quarters.
- Peak year-over-year performance for Total Non-Current Liabilities in the last five years was growth of 513.4% in Q1 2026, against a decline of 93.7% in Q2 2022 at the low end.
- Per Business Quant, the preceding three quarters came in at $883 million (Q1 2026), $228.66 million (Q4 2025) and $268.93 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | General Electric | 324.09 Bn | 278.09 Bn | 4.68 Bn | 102.53 Bn |
| 2 | Rtx | 250.22 Bn | 223.44 Bn | 5.13 Bn | 86.00 Mn |
| 3 | Boeing | 147.08 Bn | 53.78 Bn | 2.41 Bn | 157.29 Bn |
| 4 | Lockheed Martin | 117.51 Bn | 104.24 Bn | 2.45 Bn | 48.28 Bn |
| 5 | Howmet Aerospace | 90.46 Bn | 86.07 Bn | 951.00 Mn | 6.90 Bn |
| 6 | General Dynamics | 89.77 Bn | 76.88 Bn | 2.18 Bn | 14.57 Bn |
| 7 | Motorola Solutions | 73.88 Bn | 70.24 Bn | 1.68 Bn | 14.44 Bn |
| 8 | Northrop Grumman | 68.68 Bn | 57.92 Bn | 2.12 Bn | 30.72 Bn |
| 9 | Honeywell International | 66.86 Bn | 19.30 Bn | 3.65 Bn | 52.22 Bn |
| 10 | Joby Aviation | 5.97 Bn | 5.97 Bn | - | 889.89 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 889.89 Mn |
| Mar 31, 2026 | 883.00 Mn |
| Dec 31, 2025 | 228.66 Mn |
| Sep 30, 2025 | 268.93 Mn |
| Jun 30, 2025 | 202.39 Mn |
| Mar 31, 2025 | 143.95 Mn |
| Dec 31, 2024 | 173.69 Mn |
| Sep 30, 2024 | 119.30 Mn |
| Jun 30, 2024 | 113.95 Mn |
| Mar 31, 2024 | 116.24 Mn |
| Dec 31, 2023 | 139.10 Mn |
| Sep 30, 2023 | 145.67 Mn |
| Jun 30, 2023 | 180.90 Mn |
| Mar 31, 2023 | 92.14 Mn |
| Dec 31, 2022 | 84.19 Mn |
| Sep 30, 2022 | 55.16 Mn |
| Jun 30, 2022 | 63.68 Mn |
| Mar 31, 2022 | 111.37 Mn |
| Dec 31, 2021 | 61.75 Mn |
| Sep 30, 2021 | 162.53 Mn |
Joby Aviation Total Non-Current 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-non-current-liabilities&ticker=JOBY&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "ticker": "JOBY", "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-non-current-liabilities&ticker=JOBY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();