Fastly (FSLY) Operating Expenses (2018 - 2026)
Fastly's Operating Expenses was $130.38 million in Q2 2026, up 10.4% from $118.06 million a year earlier but down 1.3% from the prior quarter.
Fastly (FSLY) Operating Expenses (2018 - 2026) Analysis & Trends
On a trailing twelve-month basis, Fastly's Operating Expenses was $504.63 million through Jun 30, 2026, up 10.2% year-over-year; for FY2025, it came in at $475.2 million, up 2.4% from FY2024.
- Operating Expenses shows a five-year compound annual growth rate of 11.3% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $463.85 million in FY2024 (-0.1%), $464.36 million in FY2023 (+1.8%), $455.98 million in FY2022 (+12.2%) and $406.35 million in FY2021 (+46.1%).
- Quarterly Operating Expenses has moved between $100.43 million (Q3 2021) and $132.08 million (Q1 2026) over five years.
- Compared with a year earlier, Operating Expenses has increased for four straight quarters, with growth averaging 2.6% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q3 2021 (growth of 55.0%); the worst was Q4 2024 (a decline of 7.6%).
- Per Business Quant data, FSLY's Operating Expenses in the three quarters before Q2 2026 was $132.08 million (Q1 2026), $121.05 million (Q4 2025) and $121.12 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Microsoft | 3,944.62 Bn | 3,880.11 Bn | 62.56 Bn | 10.93 Bn |
| 2 | International Business Machines | 231.10 Bn | 185.71 Bn | 9.71 Bn | 7.00 Bn |
| 3 | Equinix | 100.11 Bn | 88.01 Bn | 1.31 Bn | 1.97 Bn |
| 4 | Cloudflare | 96.02 Bn | 78.46 Bn | 557.23 Mn | 625.16 Mn |
| 5 | Nebius | 31.44 Bn | 4.87 Bn | 448.70 Mn | 758.20 Mn |
| 6 | Verisign | 27.82 Bn | 25.17 Bn | 393.20 Mn | 146.50 Mn |
| 7 | CoreWeave | 25.57 Bn | 12.66 Bn | 1.70 Bn | 2.62 Bn |
| 8 | Nutanix | 15.68 Bn | 7.37 Bn | 651.35 Mn | 581.36 Mn |
| 9 | GoDaddy | 14.30 Bn | 9.69 Bn | 843.00 Mn | 979.30 Mn |
| 10 | Fastly | 2.56 Bn | 1.16 Bn | 120.41 Mn | 131.68 Mn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 131.68 Mn |
| Jun 30, 2026 | 130.38 Mn |
| Mar 31, 2026 | 132.08 Mn |
| Dec 31, 2025 | 121.05 Mn |
| Sep 30, 2025 | 121.12 Mn |
| Jun 30, 2025 | 118.06 Mn |
| Mar 31, 2025 | 114.98 Mn |
| Dec 31, 2024 | 109.39 Mn |
| Sep 30, 2024 | 115.33 Mn |
| Jun 30, 2024 | 119.64 Mn |
| Mar 31, 2024 | 119.49 Mn |
| Dec 31, 2023 | 118.36 Mn |
| Sep 30, 2023 | 124.43 Mn |
| Jun 30, 2023 | 114.04 Mn |
| Mar 31, 2023 | 107.53 Mn |
| Dec 31, 2022 | 111.05 Mn |
| Sep 30, 2022 | 118.44 Mn |
| Jun 30, 2022 | 115.02 Mn |
| Mar 31, 2022 | 111.47 Mn |
| Dec 31, 2021 | 106.43 Mn |
Fastly 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=FSLY&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "FSLY", "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=FSLY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();