F5 (FFIV) Operating Expenses (2009 - 2026)
F5 (FFIV) posted Operating Expenses of $498.25 million for fiscal Q3 2026 (quarter ended Jun 30, 2026), up 14.4% from $435.43 million a year earlier and up 3.4% from the prior quarter.
F5 (FFIV) Operating Expenses (2009 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at F5 was $1.9 billion, up 11.6% year-over-year; for FY2025 (ended Sep 30, 2025), it was $1.75 billion, up 9.3% from FY2024.
- Annual Operating Expenses shows a five-year compound annual growth rate of 2.4% (FY2020 to FY2025).
- In prior fiscal years, F5's Operating Expenses was $1.6 billion in FY2024 (-8.4%), $1.75 billion in FY2023 (-0.3%), $1.75 billion in FY2022 (+2.1%) and $1.72 billion in FY2021 (+10.7%).
- The fiscal Q3 2026 figure stands as the highest quarterly Operating Expenses in data going back to fiscal Q3 2009.
- On a year-over-year basis, Operating Expenses has increased in each of the last eight quarters, with growth averaging 9.5% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was fiscal Q3 2026, with growth of 14.4%; the weakest was fiscal Q1 2024, with a decline of 13.8%.
- According to Business Quant data, Operating Expenses for the three prior fiscal quarters was $481.78 million (Q2 2026), $456.49 million (Q1 2026) and $460.56 million (Q4 2025).
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 | F5 | 24.75 Bn | 19.16 Bn | 711.51 Mn | 498.25 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 498.25 Mn |
| Mar 31, 2026 | 481.78 Mn |
| Dec 31, 2025 | 456.49 Mn |
| Sep 30, 2025 | 460.56 Mn |
| Jun 30, 2025 | 435.43 Mn |
| Mar 31, 2025 | 431.27 Mn |
| Dec 31, 2024 | 420.90 Mn |
| Sep 30, 2024 | 411.93 Mn |
| Jun 30, 2024 | 395.98 Mn |
| Mar 31, 2024 | 400.28 Mn |
| Dec 31, 2023 | 391.69 Mn |
| Sep 30, 2023 | 394.27 Mn |
| Jun 30, 2023 | 457.39 Mn |
| Mar 31, 2023 | 441.48 Mn |
| Dec 31, 2022 | 454.16 Mn |
| Sep 30, 2022 | 445.04 Mn |
| Jun 30, 2022 | 436.29 Mn |
| Mar 31, 2022 | 433.22 Mn |
| Dec 31, 2021 | 437.88 Mn |
| Sep 30, 2021 | 426.96 Mn |
F5 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=FFIV&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "FFIV", "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=FFIV&period=max&api_key=YOUR_API_KEY");
const data = await res.json();