Intuitive Machines (LUNR) Debt Ratio (2022 - 2026)
Intuitive Machines' (LUNR) Debt Ratio came in at 0.18 for Q2 2026, down 8.8% from the prior quarter.
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Analysis
Intuitive Machines (LUNR) Debt Ratio (2022 - 2026) Analysis & Trends
For FY2025, Intuitive Machines' Debt Ratio stood at 0.44.
- In prior years, Intuitive Machines' Debt Ratio was 0.09 in FY2023 (-68.7%) and 0.30 in FY2022.
- The Q2 2026 figure stands as the lowest quarterly Debt Ratio since Q2 2024.
- According to Business Quant data, Debt Ratio for the three prior quarters was 0.20 (Q1 2026), 0.44 (Q4 2025) and 0.44 (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Debt Ratio (Qtr) |
|---|---|---|---|---|---|
| 1 | General Electric | 315.55 Bn | 274.07 Bn | 5.02 Bn | 0.15 |
| 2 | Rtx | 270.32 Bn | 238.59 Bn | 5.81 Bn | 0.21 |
| 3 | Lockheed Martin | 148.10 Bn | 132.33 Bn | 2.44 Bn | 0.32 |
| 4 | Boeing | 137.34 Bn | 46.30 Bn | 2.17 Bn | 0.27 |
| 5 | General Dynamics | 101.75 Bn | 88.86 Bn | 2.18 Bn | 0.12 |
| 6 | Motorola Solutions | 81.40 Bn | 77.74 Bn | 1.68 Bn | 0.47 |
| 7 | Howmet Aerospace | 81.35 Bn | 77.10 Bn | 1.00 Bn | 0.36 |
| 8 | Northrop Grumman | 79.82 Bn | 67.28 Bn | 2.35 Bn | 0.27 |
| 9 | Honeywell International | 69.67 Bn | 69.67 Bn | - | - |
| 10 | Intuitive Machines | 1.78 Bn | -22.96 Mn | 35.87 Mn | 0.18 |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 0.18 |
| Mar 31, 2026 | 0.20 |
| Dec 31, 2025 | 0.44 |
| Sep 30, 2025 | 0.44 |
| Jun 30, 2024 | 0.02 |
| Mar 31, 2024 | 0.05 |
| Dec 31, 2023 | 0.09 |
| Sep 30, 2023 | 0.19 |
| Jun 30, 2023 | 0.21 |
| Mar 31, 2023 | 0.20 |
| Dec 31, 2022 | 0.30 |
API Access
Intuitive Machines Debt Ratio 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=debt-ratio&ticker=LUNR&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "debt-ratio", "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=debt-ratio&ticker=LUNR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();