Intuitive Machines (LUNR) Non-Current Assets (2021 - 2026)
Intuitive Machines (LUNR) posted Non-Current Assets of $1.22 billion for Q2 2026, compared with $78.89 million a year earlier and up 1.0% from the prior quarter.
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Analysis
Intuitive Machines (LUNR) Non-Current Assets (2021 - 2026) Analysis & Trends
At the end of FY2025, Intuitive Machines' Non-Current Assets came in at $138.34 million, up 122.3% from FY2024.
- Annual Non-Current Assets has increased for three consecutive years, though with a four-year compound annual growth rate of -19.5% (FY2021 to FY2025).
- In prior years, Intuitive Machines' Non-Current Assets was $62.24 million in FY2024 (+14.6%), $54.3 million in FY2023 (+108.7%), $26.01 million in FY2022 (-92.1%) and $330.08 million in FY2021.
- The Q2 2026 figure stands as the highest quarterly Non-Current Assets in data going back to Q3 2021.
- The strongest year-over-year quarter for Non-Current Assets in the past five years was Q4 2025, with growth of 122.3%; the weakest was Q4 2022, with a decline of 92.1%.
- According to Business Quant data, Non-Current Assets for the three prior quarters was $1.21 billion (Q1 2026), $138.34 million (Q4 2025) and $87.55 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Non-Current Assets (Qtr) |
|---|---|---|---|---|---|
| 1 | General Electric | 324.09 Bn | 278.09 Bn | 4.68 Bn | 87.98 Bn |
| 2 | Rtx | 250.22 Bn | 223.44 Bn | 5.13 Bn | 1.25 Bn |
| 3 | Boeing | 147.08 Bn | 53.78 Bn | 2.41 Bn | 41.24 Bn |
| 4 | Lockheed Martin | 117.51 Bn | 104.24 Bn | 2.45 Bn | 34.05 Bn |
| 5 | Howmet Aerospace | 90.46 Bn | 86.07 Bn | 951.00 Mn | 9.06 Bn |
| 6 | General Dynamics | 89.77 Bn | 76.88 Bn | 2.18 Bn | 33.13 Bn |
| 7 | Motorola Solutions | 73.88 Bn | 70.24 Bn | 1.68 Bn | 13.11 Bn |
| 8 | Northrop Grumman | 68.68 Bn | 57.92 Bn | 2.12 Bn | 35.17 Bn |
| 9 | Honeywell International | 66.86 Bn | 19.30 Bn | 3.65 Bn | 49.27 Bn |
| 10 | Intuitive Machines | 3.21 Bn | 2.60 Bn | 35.87 Mn | 1.22 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.22 Bn |
| Mar 31, 2026 | 1.21 Bn |
| Dec 31, 2025 | 138.34 Mn |
| Sep 30, 2025 | 87.55 Mn |
| Jun 30, 2025 | 78.89 Mn |
| Mar 31, 2025 | 68.70 Mn |
| Dec 31, 2024 | 62.24 Mn |
| Sep 30, 2024 | 56.53 Mn |
| Jun 30, 2024 | 57.01 Mn |
| Mar 31, 2024 | 55.04 Mn |
| Dec 31, 2023 | 54.30 Mn |
| Sep 30, 2023 | 54.09 Mn |
| Jun 30, 2023 | 45.24 Mn |
| Mar 31, 2023 | 34.10 Mn |
| Dec 31, 2022 | 26.01 Mn |
| Sep 30, 2022 | 331.74 Mn |
| Jun 30, 2022 | 330.35 Mn |
| Mar 31, 2022 | 330.00 Mn |
| Dec 31, 2021 | 330.08 Mn |
| Sep 30, 2021 | 300.44 Mn |
API Access
Intuitive Machines Non-Current Assets 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-assets&ticker=LUNR&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "non-current-assets", "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-assets&ticker=LUNR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();