Stem (STEM) Total Non-Current Liabilities (2019 - 2026)
Stem (STEM) reported Total Non-Current Liabilities of $545.39 million for Q2 2026, down 2.2% from $557.39 million a year earlier but up 0.4% from the prior quarter.
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Analysis
Stem (STEM) Total Non-Current Liabilities (2019 - 2026) Analysis & Trends
At the end of FY2025, Stem posted Total Non-Current Liabilities of $553.21 million, down 30.8% from FY2024.
- Total Non-Current Liabilities has a five-year compound annual growth rate of 7.9% (FY2020 to FY2025).
- By year, Total Non-Current Liabilities came in at $799.79 million in FY2024 (-13.7%), $926.24 million in FY2023 (+7.0%), $865.46 million in FY2022 (+66.5%) and $519.87 million in FY2021 (+37.1%).
- Five-year quarterly Total Non-Current Liabilities spans a low of $189.9 million in Q3 2021 and a high of $980.07 million in Q2 2023.
- Year over year, Total Non-Current Liabilities has now declined in each of the last nine quarters, with an average decline of 21.4% over the last eight quarters.
- The high point for year-over-year Total Non-Current Liabilities in five years was Q2 2022 (growth of 340.9%); the low point was Q2 2025 (a decline of 37.4%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $543.4 million (Q1 2026), $553.21 million (Q4 2025) and $563.1 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 319.55 Bn | 304.63 Bn | 2.30 Bn | 19.68 Bn |
| 2 | CrowdStrike Holdings | 265.46 Bn | 245.90 Bn | 1.10 Bn | 6.57 Bn |
| 3 | Fortinet | 129.36 Bn | 115.29 Bn | 1.64 Bn | 9.17 Bn |
| 4 | Snowflake | 115.65 Bn | 102.97 Bn | 1.04 Bn | 6.45 Bn |
| 5 | Datadog | 96.45 Bn | 78.09 Bn | 881.34 Mn | 3.16 Bn |
| 6 | Axon Enterprise | 34.50 Bn | 29.03 Bn | 546.45 Mn | 3.68 Bn |
| 7 | Okta | 33.79 Bn | 23.89 Bn | 641.00 Mn | 2.11 Bn |
| 8 | Zscaler | 32.51 Bn | 18.63 Bn | - | 5.20 Bn |
| 9 | Baidu | 29.59 Bn | -44.04 Bn | 1.47 Mn | 12.63 Bn |
| 10 | Stem | 43.72 Mn | -123.76 Mn | 13.89 Mn | 545.39 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 545.39 Mn |
| Mar 31, 2026 | 543.40 Mn |
| Dec 31, 2025 | 553.21 Mn |
| Sep 30, 2025 | 563.10 Mn |
| Jun 30, 2025 | 557.39 Mn |
| Mar 31, 2025 | 786.60 Mn |
| Dec 31, 2024 | 799.79 Mn |
| Sep 30, 2024 | 877.24 Mn |
| Jun 30, 2024 | 890.16 Mn |
| Mar 31, 2024 | 908.77 Mn |
| Dec 31, 2023 | 926.24 Mn |
| Sep 30, 2023 | 941.36 Mn |
| Jun 30, 2023 | 980.07 Mn |
| Mar 31, 2023 | 872.70 Mn |
| Dec 31, 2022 | 865.46 Mn |
| Sep 30, 2022 | 835.74 Mn |
| Jun 30, 2022 | 819.06 Mn |
| Mar 31, 2022 | 783.51 Mn |
| Dec 31, 2021 | 519.87 Mn |
| Sep 30, 2021 | 189.90 Mn |
API Access
Stem 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=STEM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "ticker": "STEM", "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=STEM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();