SmartRent (SMRT) Total Non-Current Liabilities (2020 - 2026)
SmartRent (SMRT) reported Total Non-Current Liabilities of $63.33 million for Q2 2026, down 41.7% from $108.61 million a year earlier and down 1.2% from the prior quarter.
SmartRent (SMRT) Total Non-Current Liabilities (2020 - 2026) Analysis & Trends
At the end of FY2025, SmartRent posted Total Non-Current Liabilities of $82.99 million, down 32.9% from FY2024.
- Total Non-Current Liabilities has declined for three consecutive years, with a five-year compound annual growth rate of -14.5% (FY2020 to FY2025).
- By year, Total Non-Current Liabilities came in at $123.62 million in FY2024 (-24.3%), $163.21 million in FY2023 (-15.3%), $192.7 million in FY2022 (+55.4%) and $123.98 million in FY2021 (-31.7%).
- The Q2 2026 figure ranks as the lowest quarterly Total Non-Current Liabilities in data going back to Q4 2020.
- Year over year, Total Non-Current Liabilities has now declined in each of the last 11 quarters, with an average decline of 30.1% over the last eight quarters.
- The high point for year-over-year Total Non-Current Liabilities in five years was Q4 2022 (growth of 55.4%); the low point was Q2 2026 (a decline of 41.7%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $64.09 million (Q1 2026), $82.99 million (Q4 2025) and $95.18 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Bryn | 945.00 Bn | 945.00 Bn | - | - |
| 2 | Veeva Systems | 45.35 Bn | 17.59 Bn | 695.95 Mn | 1.60 Bn |
| 3 | Samsara | 22.20 Bn | 18.97 Bn | 392.58 Mn | 1.15 Bn |
| 4 | Toast | 17.53 Bn | 10.20 Bn | 516.00 Mn | 1.10 Bn |
| 5 | Ptc | 15.47 Bn | 14.28 Bn | 490.47 Mn | 2.94 Bn |
| 6 | Trimble | 13.41 Bn | 12.48 Bn | 674.90 Mn | 3.15 Bn |
| 7 | Duolingo | 12.56 Bn | 7.73 Bn | 216.74 Mn | - |
| 8 | Manhattan Associates | 11.77 Bn | 10.77 Bn | 168.33 Mn | 528.94 Mn |
| 9 | Costar | 10.95 Bn | 4.91 Bn | 728.00 Mn | 2.16 Bn |
| 10 | SmartRent | 229.93 Mn | -166.12 Mn | 16.22 Mn | 63.33 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 63.33 Mn |
| Mar 31, 2026 | 64.09 Mn |
| Dec 31, 2025 | 82.99 Mn |
| Sep 30, 2025 | 95.18 Mn |
| Jun 30, 2025 | 108.61 Mn |
| Mar 31, 2025 | 108.58 Mn |
| Dec 31, 2024 | 123.62 Mn |
| Sep 30, 2024 | 136.08 Mn |
| Jun 30, 2024 | 145.00 Mn |
| Mar 31, 2024 | 148.48 Mn |
| Dec 31, 2023 | 163.21 Mn |
| Sep 30, 2023 | 167.75 Mn |
| Jun 30, 2023 | 170.54 Mn |
| Mar 31, 2023 | 177.89 Mn |
| Dec 31, 2022 | 192.70 Mn |
| Sep 30, 2022 | 162.17 Mn |
| Jun 30, 2022 | 163.26 Mn |
| Mar 31, 2022 | 163.03 Mn |
| Dec 31, 2021 | 123.98 Mn |
| Sep 30, 2021 | 110.27 Mn |
SmartRent Total Non-Current Liabilities 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-non-current-liabilities&ticker=SMRT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "ticker": "SMRT", "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-non-current-liabilities&ticker=SMRT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();