Firefly Neuroscience (AIFF) Operating Expenses (2010 - 2026)
Firefly Neuroscience (AIFF) reported Operating Expenses of $2.23 million for Q2 2026, up 16.7% from $1.91 million a year earlier but down 0.2% from the prior quarter.
Firefly Neuroscience (AIFF) Operating Expenses (2010 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Firefly Neuroscience's Operating Expenses came in at $9.94 million, down 15.8% year-over-year; for FY2025, it came in at $9.5 million, down 6.5% from FY2024.
- Operating Expenses has a five-year compound annual growth rate of 39.5% (FY2020 to FY2025).
- By year, Operating Expenses came in at $10.16 million in FY2024 (+184.2%), $3.58 million in FY2023 (-56.8%), $8.28 million in FY2022 (+18.4%) and $7 million in FY2021 (+289.3%).
- Five-year quarterly Operating Expenses spans a low of $670,000 in Q3 2023 and a high of $4.3 million in Q3 2024.
- Year over year, Operating Expenses gained in six of the last eight quarters, with growth averaging 96.0%.
- The high point for year-over-year Operating Expenses in five years was Q3 2024 (growth of 541.9%); the low point was Q3 2023 (a decline of 64.9%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $2.23 million (Q1 2026), $2.68 million (Q4 2025) and $2.8 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 250.84 Bn | 229.99 Bn | 4.88 Bn | 9.91 Bn |
| 2 | Abbott Laboratories | 174.73 Bn | 145.82 Bn | 7.27 Bn | 10.90 Bn |
| 3 | Danaher | 159.85 Bn | 143.67 Bn | 3.61 Bn | 2.48 Bn |
| 4 | Intuitive Surgical | 146.79 Bn | 126.35 Bn | 1.96 Bn | 988.50 Mn |
| 5 | Medtronic | 114.54 Bn | 80.41 Bn | 6.34 Bn | 4.06 Bn |
| 6 | Stryker | 105.67 Bn | 91.79 Bn | 4.50 Bn | 2.84 Bn |
| 7 | Boston Scientific | 63.93 Bn | 58.94 Bn | 3.85 Bn | 2.67 Bn |
| 8 | Becton Dickinson | 50.12 Bn | 47.27 Bn | 2.32 Bn | 4.32 Bn |
| 9 | Edwards Lifesciences | 50.06 Bn | 34.17 Bn | 1.35 Bn | 840.10 Mn |
| 10 | Firefly Neuroscience | 34.78 Mn | 15.35 Mn | 253,000.00 | 2.23 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 2.23 Mn |
| Mar 31, 2026 | 2.23 Mn |
| Dec 31, 2025 | 2.68 Mn |
| Sep 30, 2025 | 2.80 Mn |
| Jun 30, 2025 | 1.91 Mn |
| Mar 31, 2025 | 2.11 Mn |
| Dec 31, 2024 | 3.49 Mn |
| Sep 30, 2024 | 4.30 Mn |
| Jun 30, 2024 | 1.27 Mn |
| Mar 31, 2024 | 1.10 Mn |
| Dec 31, 2023 | 1.59 Mn |
| Sep 30, 2023 | 670,000.00 |
| Jun 30, 2023 | 1.65 Mn |
| Mar 31, 2023 | 1.61 Mn |
| Dec 31, 2022 | 1.54 Mn |
| Sep 30, 2022 | 1.91 Mn |
| Jun 30, 2022 | 2.86 Mn |
| Mar 31, 2022 | 2.81 Mn |
| Dec 31, 2021 | 4.28 Mn |
| Sep 30, 2021 | 1.06 Mn |
Firefly Neuroscience 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=AIFF&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "AIFF", "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=AIFF&period=max&api_key=YOUR_API_KEY");
const data = await res.json();