Fastly (FSLY) Accumulated Expenses (2018 - 2026)
Fastly (FSLY) posted Accumulated Expenses of $52.94 million for Q2 2026, up 16.9% from $45.28 million a year earlier and up 16.3% from the prior quarter.
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Analysis
Fastly (FSLY) Accumulated Expenses (2018 - 2026) Analysis & Trends
At the end of FY2025, Fastly's Accumulated Expenses came in at $70.67 million, up 69.8% from FY2024.
- Annual Accumulated Expenses shows a five-year compound annual growth rate of 15.5% (FY2020 to FY2025).
- In prior years, Fastly's Accumulated Expenses was $41.62 million in FY2024 (-32.7%), $61.82 million in FY2023 (+1.1%), $61.16 million in FY2022 (+69.4%) and $36.11 million in FY2021 (+5.2%).
- Quarterly Accumulated Expenses has run from a low of $34.45 million in Q2 2024 to a high of $70.67 million in Q4 2025 over five years.
- On a year-over-year basis, Accumulated Expenses has increased in each of the last six quarters, with growth averaging 16.6% over the last eight quarters.
- The strongest year-over-year quarter for Accumulated Expenses in the past five years was Q2 2022, with growth of 74.6%; the weakest was Q4 2024, with a decline of 32.7%.
- According to Business Quant data, Accumulated Expenses for the three prior quarters was $45.52 million (Q1 2026), $70.67 million (Q4 2025) and $60.42 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Microsoft | 3,964.86 Bn | 3,888.01 Bn | 60.48 Bn |
| 2 | International Business Machines | 222.38 Bn | 173.19 Bn | 9.91 Bn |
| 3 | Cloudflare | 105.62 Bn | 89.15 Bn | 499.52 Mn |
| 4 | Equinix | 96.25 Bn | 84.81 Bn | 1.40 Bn |
| 5 | Nebius | 41.41 Bn | 14.84 Bn | 448.70 Mn |
| 6 | CoreWeave | 33.73 Bn | 20.82 Bn | 1.70 Bn |
| 7 | Verisign | 27.82 Bn | 25.04 Bn | 384.60 Mn |
| 8 | Nutanix | 18.15 Bn | 9.84 Bn | 651.35 Mn |
| 9 | GoDaddy | 13.94 Bn | 9.52 Bn | 828.20 Mn |
| 10 | Fastly | 3.64 Bn | 2.27 Bn | 115.95 Mn |
Historic Data
Download Data
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 |
API Access
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_KEYimport 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();