Roku (ROKU) Operating Expenses (2016 - 2026)
Roku's Operating Expenses came in at $527.52 million for Q2 2026, up 1.3% from $520.99 million a year earlier and up 2.8% from the prior quarter.
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Analysis
Roku (ROKU) Operating Expenses (2016 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Roku reported Operating Expenses of $2.1 billion, up 0.3% year-over-year; for FY2025, it came in at $2.08 billion, up 2.8% from FY2024.
- Operating Expenses carries a five-year compound annual growth rate of 20.2% (FY2020 to FY2025).
- Going back by year, Operating Expenses was $2.02 billion in FY2024 (-12.6%), $2.31 billion in FY2023 (+17.4%), $1.97 billion in FY2022 (+68.0%) and $1.17 billion in FY2021 (+41.6%).
- The five-year range for quarterly Operating Expenses is $295.07 million (Q3 2021) to $718.61 million (Q3 2023).
- Year-over-year, Operating Expenses increased in five of the last eight quarters, with an average decline of 1.4%.
- The fastest year-over-year change in Operating Expenses over five years came in Q2 2022 (growth of 73.0%), and the weakest in Q3 2024 (a decline of 28.2%).
- Business Quant data shows ROKU's Operating Expenses at $513.16 million (Q1 2026), $540.85 million (Q4 2025) and $515.43 million (Q3 2025) in the three quarters before Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 319.55 Bn | 304.63 Bn | 2.30 Bn | 2.13 Bn |
| 2 | CrowdStrike Holdings | 265.46 Bn | 245.90 Bn | 1.10 Bn | 1.13 Bn |
| 3 | Fortinet | 129.36 Bn | 115.29 Bn | 1.64 Bn | 953.90 Mn |
| 4 | Snowflake | 115.65 Bn | 102.97 Bn | 1.04 Bn | 1.30 Bn |
| 5 | Datadog | 96.45 Bn | 78.09 Bn | 881.34 Mn | 875.89 Mn |
| 6 | Axon Enterprise | 34.50 Bn | 29.03 Bn | 546.45 Mn | 499.67 Mn |
| 7 | Okta | 33.79 Bn | 23.89 Bn | 641.00 Mn | 534.00 Mn |
| 8 | Zscaler | 32.51 Bn | 18.63 Bn | - | - |
| 9 | Baidu | 29.59 Bn | -44.04 Bn | 1.47 Mn | 4.17 Bn |
| 10 | Roku | 22.66 Bn | 13.10 Bn | 673.70 Mn | 527.52 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 527.52 Mn |
| Mar 31, 2026 | 513.16 Mn |
| Dec 31, 2025 | 540.85 Mn |
| Sep 30, 2025 | 515.43 Mn |
| Jun 30, 2025 | 520.99 Mn |
| Mar 31, 2025 | 502.78 Mn |
| Dec 31, 2024 | 551.70 Mn |
| Sep 30, 2024 | 515.84 Mn |
| Jun 30, 2024 | 495.94 Mn |
| Mar 31, 2024 | 460.33 Mn |
| Dec 31, 2023 | 542.09 Mn |
| Sep 30, 2023 | 718.61 Mn |
| Jun 30, 2023 | 504.23 Mn |
| Mar 31, 2023 | 550.06 Mn |
| Dec 31, 2022 | 614.28 Mn |
| Sep 30, 2022 | 503.78 Mn |
| Jun 30, 2022 | 465.66 Mn |
| Mar 31, 2022 | 388.30 Mn |
| Dec 31, 2021 | 358.28 Mn |
| Sep 30, 2021 | 295.07 Mn |
API Access
Roku Operating Expenses 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=operating-expenses&ticker=ROKU&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "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=operating-expenses&ticker=ROKU&period=max&api_key=YOUR_API_KEY");
const data = await res.json();