Joby Aviation (JOBY) Cash & Equivalents (2020 - 2026)
Joby Aviation's Cash & Equivalents was $629.86 million in Q2 2026, up 87.3% from $336.31 million a year earlier but down 28.0% from the prior quarter.
Joby Aviation (JOBY) Cash & Equivalents (2020 - 2026) Analysis & Trends
At the end of FY2025, Cash & Equivalents at Joby Aviation came in at $240.81 million, up 20.6% from FY2024.
- Cash & Equivalents shows a five-year compound annual growth rate of 25.5% (FY2020 to FY2025).
- In earlier years, Cash & Equivalents was $199.63 million in FY2024 (-2.2%), $204.02 million in FY2023 (+39.6%), $146.1 million in FY2022 (-84.7%) and $955.56 million in FY2021.
- Quarterly Cash & Equivalents has moved between $49.8 million (Q1 2023) and $1.02 billion (Q3 2021) over five years.
- Compared with a year earlier, Cash & Equivalents has increased for six straight quarters, with growth averaging 99.0% over the last eight quarters.
- The best year-over-year quarter for Cash & Equivalents over five years was Q1 2026 (growth of 615.1%); the worst was Q1 2023 (a decline of 88.1%).
- Per Business Quant data, JOBY's Cash & Equivalents in the three quarters before Q2 2026 was $874.52 million (Q1 2026), $240.81 million (Q4 2025) and $208.37 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Cash & Equiv. (Qtr) |
|---|---|---|---|---|---|
| 1 | General Electric | 321.31 Bn | 275.31 Bn | 4.68 Bn | 9.35 Bn |
| 2 | Rtx | 248.97 Bn | 222.19 Bn | 5.13 Bn | 8.31 Bn |
| 3 | Boeing | 152.99 Bn | 59.70 Bn | 2.41 Bn | 7.24 Bn |
| 4 | Lockheed Martin | 116.67 Bn | 103.39 Bn | 2.45 Bn | 3.79 Bn |
| 5 | Howmet Aerospace | 92.54 Bn | 88.15 Bn | 951.00 Mn | 563.00 Mn |
| 6 | General Dynamics | 89.31 Bn | 76.42 Bn | 2.18 Bn | 4.33 Bn |
| 7 | Motorola Solutions | 74.04 Bn | 70.40 Bn | 1.68 Bn | 710.00 Mn |
| 8 | Northrop Grumman | 67.90 Bn | 57.15 Bn | 2.12 Bn | 2.31 Bn |
| 9 | Honeywell International | 67.82 Bn | 20.27 Bn | 3.65 Bn | 8.75 Bn |
| 10 | Joby Aviation | 5.87 Bn | 5.87 Bn | - | 629.86 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 629.86 Mn |
| Mar 31, 2026 | 874.52 Mn |
| Dec 31, 2025 | 240.81 Mn |
| Sep 30, 2025 | 208.37 Mn |
| Jun 30, 2025 | 336.31 Mn |
| Mar 31, 2025 | 122.29 Mn |
| Dec 31, 2024 | 199.63 Mn |
| Sep 30, 2024 | 152.29 Mn |
| Jun 30, 2024 | 175.10 Mn |
| Mar 31, 2024 | 110.55 Mn |
| Dec 31, 2023 | 204.02 Mn |
| Sep 30, 2023 | 480.37 Mn |
| Jun 30, 2023 | 382.67 Mn |
| Mar 31, 2023 | 49.80 Mn |
| Dec 31, 2022 | 146.10 Mn |
| Sep 30, 2022 | 193.84 Mn |
| Jun 30, 2022 | 311.09 Mn |
| Mar 31, 2022 | 417.12 Mn |
| Dec 31, 2021 | 955.56 Mn |
| Sep 30, 2021 | 1.02 Bn |
Joby Aviation Cash & Equivalents 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=cash-and-equivalents&ticker=JOBY&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "cash-and-equivalents", "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=cash-and-equivalents&ticker=JOBY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();