Intuitive Machines (LUNR) Non-Current Debt (2022 - 2026)
Intuitive Machines (LUNR) recorded Non-Current Debt of $336.35 million in Q2 2026, up 0.2% from the prior quarter.
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Analysis
Intuitive Machines (LUNR) Non-Current Debt (2022 - 2026) Analysis & Trends
At the end of FY2025, Intuitive Machines reported Non-Current Debt of $335.34 million.
- Annual Non-Current Debt has a three-year compound annual growth rate of 342.8% (FY2022 to FY2025).
- Across earlier years, Non-Current Debt came in at $3.86 million in FY2022.
- Per Business Quant, the preceding three quarters came in at $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) | Non-Current Debt (Qtr) |
|---|---|---|---|---|---|
| 1 | General Electric | 324.09 Bn | 278.09 Bn | 4.68 Bn | 17.16 Bn |
| 2 | Rtx | 250.22 Bn | 223.44 Bn | 5.13 Bn | 31.86 Bn |
| 3 | Boeing | 147.08 Bn | 53.78 Bn | 2.41 Bn | 41.34 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 | 4.05 Bn |
| 6 | General Dynamics | 89.77 Bn | 76.88 Bn | 2.18 Bn | 6.26 Bn |
| 7 | Motorola Solutions | 73.88 Bn | 70.24 Bn | 1.68 Bn | 8.42 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 | 26.23 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 |
| Mar 31, 2023 | 3.87 Mn |
| Dec 31, 2022 | 3.86 Mn |
API Access
Intuitive Machines Non-Current 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=non-current-debt&ticker=LUNR&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "non-current-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=non-current-debt&ticker=LUNR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();