Roku (ROKU) Total Non-Current Liabilities (2016 - 2026)
Roku's Total Non-Current Liabilities was $1.67 billion in Q2 2026, up 3.4% from $1.62 billion a year earlier and up 4.5% from the prior quarter.
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Analysis
Roku (ROKU) Total Non-Current Liabilities (2016 - 2026) Analysis & Trends
At the end of FY2025, Total Non-Current Liabilities at Roku came in at $1.7 billion, down 3.8% from FY2024.
- Total Non-Current Liabilities shows a five-year compound annual growth rate of 12.6% (FY2020 to FY2025).
- In earlier years, Total Non-Current Liabilities was $1.77 billion in FY2024 (-6.2%), $1.89 billion in FY2023 (+11.2%), $1.7 billion in FY2022 (+37.6%) and $1.23 billion in FY2021 (+31.3%).
- Quarterly Total Non-Current Liabilities has moved between $1.17 billion (Q3 2021) and $1.89 billion (Q4 2023) over five years.
- Compared with a year earlier, Total Non-Current Liabilities was higher in 1 of the last eight quarters, with an average decline of 3.3%.
- The best year-over-year quarter for Total Non-Current Liabilities over five years was Q4 2022 (growth of 37.6%); the worst was Q1 2025 (a decline of 7.5%).
- Per Business Quant data, ROKU's Total Non-Current Liabilities in the three quarters before Q2 2026 was $1.6 billion (Q1 2026), $1.7 billion (Q4 2025) and $1.7 billion (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 | Roku | 22.66 Bn | 13.10 Bn | 673.70 Mn | 1.67 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.67 Bn |
| Mar 31, 2026 | 1.60 Bn |
| Dec 31, 2025 | 1.70 Bn |
| Sep 30, 2025 | 1.70 Bn |
| Jun 30, 2025 | 1.62 Bn |
| Mar 31, 2025 | 1.62 Bn |
| Dec 31, 2024 | 1.77 Bn |
| Sep 30, 2024 | 1.80 Bn |
| Jun 30, 2024 | 1.67 Bn |
| Mar 31, 2024 | 1.75 Bn |
| Dec 31, 2023 | 1.89 Bn |
| Sep 30, 2023 | 1.83 Bn |
| Jun 30, 2023 | 1.57 Bn |
| Mar 31, 2023 | 1.44 Bn |
| Dec 31, 2022 | 1.70 Bn |
| Sep 30, 2022 | 1.54 Bn |
| Jun 30, 2022 | 1.44 Bn |
| Mar 31, 2022 | 1.33 Bn |
| Dec 31, 2021 | 1.23 Bn |
| Sep 30, 2021 | 1.17 Bn |
API Access
Roku 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=ROKU&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "ticker": "ROKU", "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=ROKU&period=max&api_key=YOUR_API_KEY");
const data = await res.json();