Firy (FIRY) Operating Expenses (2020 - 2026)
Firy (FIRY) posted Operating Expenses of $52.56 million for Q2 2026, up 27.6% from $41.2 million a year earlier and up 38.8% from the prior quarter.
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Analysis
Firy (FIRY) Operating Expenses (2020 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Firy was $180.26 million, up 8.5% year-over-year; for FY2025, it came in at $168.41 million, up 20.8% from FY2024.
- Annual Operating Expenses shows a five-year compound annual growth rate of -12.7% (FY2020 to FY2025).
- In prior years, Firy's Operating Expenses was $139.37 million in FY2024 (-47.7%), $266.37 million in FY2023 (-61.5%), $691.07 million in FY2022 (+2.5%) and $673.97 million in FY2021 (+102.9%).
- The Q2 2026 figure stands as the highest quarterly Operating Expenses since Q3 2023.
- On a year-over-year basis, Operating Expenses has increased in each of the last three quarters, with an average decline of 6.4% over the last seven quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q3 2021, with growth of 107.5%; the weakest was Q4 2023, with a decline of 72.2%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $37.86 million (Q1 2026), $46.2 million (Q4 2025) and $43.65 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Alphabet | 4,164.76 Bn | 3,922.28 Bn | 73.85 Bn | 79.03 Bn |
| 2 | Meta Platforms | 1,823.40 Bn | 1,525.92 Bn | 49.47 Bn | 42.03 Bn |
| 3 | Netflix | 288.27 Bn | 248.47 Bn | 6.52 Bn | 1.51 Bn |
| 4 | Alibaba Group Holding | 252.72 Bn | 70.58 Bn | 15.11 Bn | -5.17 Bn |
| 5 | Shopify | 186.52 Bn | 163.71 Bn | 1.71 Bn | 1.22 Bn |
| 6 | Uber Technologies | 139.11 Bn | 111.09 Bn | 6.38 Bn | 12.30 Bn |
| 7 | Booking Holdings | 123.13 Bn | 56.18 Bn | - | 4.85 Bn |
| 8 | PDD Holdings | 111.72 Bn | -140.21 Bn | 9.45 Bn | -5.39 Bn |
| 9 | AppLovin | 103.35 Bn | 93.38 Bn | 1.70 Bn | 429.41 Mn |
| 10 | Firy | 206.03 Mn | -549.68 Mn | 27.08 Mn | 52.56 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 52.56 Mn |
| Mar 31, 2026 | 37.86 Mn |
| Dec 31, 2025 | 46.20 Mn |
| Sep 30, 2025 | 43.65 Mn |
| Jun 30, 2025 | 41.20 Mn |
| Mar 31, 2025 | 37.37 Mn |
| Dec 31, 2024 | 42.00 Mn |
| Sep 30, 2024 | 45.56 Mn |
| Jun 30, 2024 | -297,000.00 |
| Mar 31, 2024 | 52.11 Mn |
| Dec 31, 2023 | 51.65 Mn |
| Sep 30, 2023 | 67.86 Mn |
| Jun 30, 2023 | 70.42 Mn |
| Mar 31, 2023 | 76.45 Mn |
| Dec 31, 2022 | 186.10 Mn |
| Sep 30, 2022 | 139.18 Mn |
| Jun 30, 2022 | 127.87 Mn |
| Mar 31, 2022 | 237.92 Mn |
| Dec 31, 2021 | 213.82 Mn |
| Sep 30, 2021 | 184.59 Mn |
API Access
Firy 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=FIRY&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "FIRY", "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=FIRY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();