Fastly (FSLY) Accumulated Expenses (2018 - 2026)
Fastly's (FSLY) quarterly Accumulated Expenses came in at $52.9 million in Q2 2026, up 16.91% year-over-year from $45.3 million in Q2 2025, and up 16.29% quarter-over-quarter from $45.5 million in Q1 2026.
Fastly (FSLY) Accumulated Expenses (2018 - 2026) Analysis & Trends
Fastly (FSLY) has reported Accumulated Expenses for 9 consecutive years, with $52.9 million the latest figure, recorded in Q2 2026.
- On a quarterly basis, Accumulated Expenses rose 16.91% year-over-year to $52.9 million in Q2 2026; TTM through Jun 2026 was $52.9 million, a 16.91% increase from a year earlier, with the FY2025 full-year figure at $70.7 million, up 69.79% from the prior year.
- Accumulated Expenses was $52.9 million for Q2 2026 at Fastly, up from $45.5 million in the prior quarter.
- Over five years, Accumulated Expenses peaked at $70.7 million in Q4 2025 and troughed at $34.4 million in Q2 2024.
- A 5-year average of $49.3 million and a median of $48.5 million in 2022 frame the typical range for Accumulated Expenses.
- Across the five-year window, Accumulated Expenses surged 74.57% in 2022 and tumbled 32.67% in 2024, its largest moves.
- Over 5 years, Accumulated Expenses stood at $61.2 million in 2022, then increased by 1.07% to $61.8 million in 2023, then plunged by 32.67% to $41.6 million in 2024, then surged by 69.79% to $70.7 million in 2025, then fell by 25.09% to $52.9 million in 2026.
- The last three Accumulated Expenses figures came in at $52.9 million (Q2 2026), $45.5 million (Q1 2026), and $70.7 million (Q4 2025), per Business Quant data.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Microsoft | 3,833.59 Bn | 3,756.75 Bn | 60.48 Bn |
| 2 | International Business Machines | 212.47 Bn | 163.37 Bn | 9.91 Bn |
| 3 | Cloudflare | 112.40 Bn | 95.93 Bn | 499.52 Mn |
| 4 | Equinix | 99.47 Bn | 88.02 Bn | 1.40 Bn |
| 5 | Nebius | 60.05 Bn | 33.48 Bn | 448.70 Mn |
| 6 | CoreWeave | 48.26 Bn | 35.35 Bn | 1.70 Bn |
| 7 | Verisign | 25.97 Bn | 23.18 Bn | 384.60 Mn |
| 8 | Nutanix | 18.41 Bn | 10.09 Bn | 651.35 Mn |
| 9 | Akamai Technologies | 16.36 Bn | 9.77 Bn | 613.75 Mn |
| 10 | Fastly | 3.97 Bn | 2.60 Bn | 115.95 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 52.94 Mn |
| Mar 31, 2026 | 45.52 Mn |
| Dec 31, 2025 | 70.67 Mn |
| Sep 30, 2025 | 60.42 Mn |
| Jun 30, 2025 | 45.28 Mn |
| Mar 31, 2025 | 37.17 Mn |
| Dec 31, 2024 | 41.62 Mn |
| Sep 30, 2024 | 40.85 Mn |
| Jun 30, 2024 | 34.45 Mn |
| Mar 31, 2024 | 35.56 Mn |
| Dec 31, 2023 | 61.82 Mn |
| Sep 30, 2023 | 56.60 Mn |
| Jun 30, 2023 | 47.00 Mn |
| Mar 31, 2023 | 42.31 Mn |
| Dec 31, 2022 | 61.16 Mn |
| Sep 30, 2022 | 54.19 Mn |
| Jun 30, 2022 | 49.94 Mn |
| Mar 31, 2022 | 49.90 Mn |
| Dec 31, 2021 | 36.11 Mn |
| Sep 30, 2021 | 36.06 Mn |
Fastly Accumulated 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=accumulated-expenses&ticker=FSLY&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-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=accumulated-expenses&ticker=FSLY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();