Intuitive Machines (LUNR) Total Debt (2022 - 2026)
Intuitive Machines (LUNR) posted Total Debt of $336.35 million for Q2 2026, up 0.2% from the prior quarter.
Analysis
Intuitive Machines (LUNR) Total Debt (2022 - 2026) Analysis & Trends
At the end of FY2025, Intuitive Machines' Total Debt came in at $335.34 million.
- Annual Total Debt shows a three-year compound annual growth rate of 156.1% (FY2022 to FY2025).
- In prior years, Intuitive Machines' Total Debt was $8 million in FY2023 (-59.9%) and $19.96 million in FY2022.
- The Q2 2026 figure stands as the highest quarterly Total Debt in data going back to Q4 2022.
- According to Business Quant data, Total Debt for the three prior quarters was $335.84 million (Q1 2026), $335.34 million (Q4 2025) and $334.83 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Debt (Qtr) |
|---|---|---|---|---|---|
| 1 | General Electric | 324.09 Bn | 278.09 Bn | 4.68 Bn | 19.16 Bn |
| 2 | Rtx | 250.22 Bn | 223.44 Bn | 5.13 Bn | 37.38 Bn |
| 3 | Boeing | 147.08 Bn | 53.78 Bn | 2.41 Bn | 45.90 Bn |
| 4 | Lockheed Martin | 117.51 Bn | 104.24 Bn | 2.45 Bn | 20.54 Bn |
| 5 | Howmet Aerospace | 90.46 Bn | 86.07 Bn | 951.00 Mn | 4.95 Bn |
| 6 | General Dynamics | 89.77 Bn | 76.88 Bn | 2.18 Bn | 7.52 Bn |
| 7 | Motorola Solutions | 73.88 Bn | 70.24 Bn | 1.68 Bn | 9.03 Bn |
| 8 | Northrop Grumman | 68.68 Bn | 57.92 Bn | 2.12 Bn | 14.43 Bn |
| 9 | Honeywell International | 66.86 Bn | 19.30 Bn | 3.65 Bn | 34.01 Bn |
| 10 | Intuitive Machines | 3.21 Bn | 2.60 Bn | 35.87 Mn | 336.35 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 336.35 Mn |
| Mar 31, 2026 | 335.84 Mn |
| Dec 31, 2025 | 335.34 Mn |
| Sep 30, 2025 | 334.83 Mn |
| Jun 30, 2024 | 3.00 Mn |
| Mar 31, 2024 | 8.00 Mn |
| Dec 31, 2023 | 8.00 Mn |
| Sep 30, 2023 | 19.98 Mn |
| Jun 30, 2023 | 19.98 Mn |
| Mar 31, 2023 | 19.97 Mn |
| Dec 31, 2022 | 19.96 Mn |
API Access
Intuitive Machines Total Debt 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-debt&ticker=LUNR&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-debt", "ticker": "LUNR", "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-debt&ticker=LUNR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();