Stem (STEM) Total Liabilities (2019 - 2026)
Stem's Total Liabilities was $549.77 million in Q2 2026, down 7.2% from $592.7 million a year earlier but up 0.4% from the prior quarter.
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Analysis
Stem (STEM) Total Liabilities (2019 - 2026) Analysis & Trends
At the end of FY2025, Total Liabilities at Stem came in at $558.33 million, down 33.1% from FY2024.
- Total Liabilities shows a five-year compound annual growth rate of 7.8% (FY2020 to FY2025).
- In earlier years, Total Liabilities was $835.19 million in FY2024 (-10.2%), $930.3 million in FY2023 (+7.0%), $869.73 million in FY2022 (+66.0%) and $524 million in FY2021 (+36.7%).
- Quarterly Total Liabilities has moved between $194.05 million (Q3 2021) and $984.15 million (Q2 2023) over five years.
- Compared with a year earlier, Total Liabilities has declined for nine straight quarters, with an average decline of 20.8% over the last eight quarters.
- The best year-over-year quarter for Total Liabilities over five years was Q3 2022 (growth of 332.9%); the worst was Q3 2021 (a decline of 58.5%).
- Per Business Quant data, STEM's Total Liabilities in the three quarters before Q2 2026 was $547.76 million (Q1 2026), $558.33 million (Q4 2025) and $598.29 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 319.55 Bn | 304.63 Bn | 2.30 Bn | 20.97 Bn |
| 2 | CrowdStrike Holdings | 265.46 Bn | 245.90 Bn | 1.10 Bn | 6.89 Bn |
| 3 | Fortinet | 129.36 Bn | 115.29 Bn | 1.64 Bn | 9.31 Bn |
| 4 | Snowflake | 115.65 Bn | 102.97 Bn | 1.04 Bn | 6.54 Bn |
| 5 | Datadog | 96.45 Bn | 78.09 Bn | 881.34 Mn | 3.18 Bn |
| 6 | Axon Enterprise | 34.50 Bn | 29.03 Bn | 546.45 Mn | 3.81 Bn |
| 7 | Okta | 33.79 Bn | 23.89 Bn | 641.00 Mn | 2.17 Bn |
| 8 | Zscaler | 32.51 Bn | 18.63 Bn | - | 5.27 Bn |
| 9 | Baidu | 29.59 Bn | -44.04 Bn | 1.47 Mn | 27.69 Bn |
| 10 | Stem | 43.72 Mn | -123.76 Mn | 13.89 Mn | 549.77 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 549.77 Mn |
| Mar 31, 2026 | 547.76 Mn |
| Dec 31, 2025 | 558.33 Mn |
| Sep 30, 2025 | 598.29 Mn |
| Jun 30, 2025 | 592.70 Mn |
| Mar 31, 2025 | 822.01 Mn |
| Dec 31, 2024 | 835.19 Mn |
| Sep 30, 2024 | 881.39 Mn |
| Jun 30, 2024 | 894.28 Mn |
| Mar 31, 2024 | 912.84 Mn |
| Dec 31, 2023 | 930.30 Mn |
| Sep 30, 2023 | 945.45 Mn |
| Jun 30, 2023 | 984.15 Mn |
| Mar 31, 2023 | 876.93 Mn |
| Dec 31, 2022 | 869.73 Mn |
| Sep 30, 2022 | 840.00 Mn |
| Jun 30, 2022 | 823.28 Mn |
| Mar 31, 2022 | 787.68 Mn |
| Dec 31, 2021 | 524.00 Mn |
| Sep 30, 2021 | 194.05 Mn |
API Access
Stem Total 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-liabilities&ticker=STEM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-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-liabilities&ticker=STEM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();