Abbott Laboratories (ABT) Operating Expenses (2009 - 2026)
Abbott Laboratories' Operating Expenses was $11.66 billion in Q3 2026, up 25.2% from $9.31 billion a year earlier and up 6.9% from the prior quarter.
Abbott Laboratories (ABT) Operating Expenses (2009 - 2026) Analysis & Trends
On a trailing twelve-month basis, Abbott Laboratories' Operating Expenses was $41.58 billion through Sep 30, 2026, up 15.1% year-over-year; for FY2025, it was $36.28 billion, up 3.3% from FY2024.
- Operating Expenses shows a five-year compound annual growth rate of 4.4% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $35.13 billion in FY2024 (+4.4%), $33.63 billion in FY2023 (-4.7%), $35.29 billion in FY2022 (+1.8%) and $34.65 billion in FY2021 (+18.5%).
- The Q3 2026 figure marks the highest quarterly Operating Expenses in data going back to Q2 2009.
- Compared with a year earlier, Operating Expenses has increased for 11 straight quarters, with growth averaging 9.8% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q3 2026 (growth of 25.2%); the worst was Q1 2023 (a decline of 8.3%).
- Per Business Quant data, ABT's Operating Expenses in the three quarters before Q3 2026 was $10.9 billion (Q2 2026), $9.82 billion (Q1 2026) and $9.21 billion (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 265.71 Bn | 242.23 Bn | 5.13 Bn | 9.87 Bn |
| 2 | Abbott Laboratories | 189.37 Bn | 163.23 Bn | 7.39 Bn | 11.66 Bn |
| 3 | Danaher | 164.78 Bn | 144.43 Bn | 3.84 Bn | 2.59 Bn |
| 4 | Intuitive Surgical | 157.85 Bn | 138.13 Bn | 2.08 Bn | 1.49 Bn |
| 5 | Medtronic | 129.66 Bn | 94.91 Bn | 6.34 Bn | 4.06 Bn |
| 6 | Stryker | 121.82 Bn | 108.01 Bn | 4.25 Bn | 3.21 Bn |
| 7 | Boston Scientific | 63.42 Bn | 58.86 Bn | 3.43 Bn | 2.60 Bn |
| 8 | Edwards Lifesciences | 59.49 Bn | 42.69 Bn | 1.35 Bn | 844.30 Mn |
| 9 | Becton Dickinson | 58.38 Bn | 55.53 Bn | 2.32 Bn | 4.32 Bn |
| 10 | Agilent Technologies | 50.16 Bn | 43.05 Bn | 1.04 Bn | 1.43 Bn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 11.66 Bn |
| Jun 30, 2026 | 10.90 Bn |
| Mar 31, 2026 | 9.82 Bn |
| Dec 31, 2025 | 9.21 Bn |
| Sep 30, 2025 | 9.31 Bn |
| Jun 30, 2025 | 9.09 Bn |
| Mar 31, 2025 | 8.67 Bn |
| Dec 31, 2024 | 9.06 Bn |
| Sep 30, 2024 | 8.78 Bn |
| Jun 30, 2024 | 8.71 Bn |
| Mar 31, 2024 | 8.58 Bn |
| Dec 31, 2023 | 8.46 Bn |
| Sep 30, 2023 | 8.50 Bn |
| Jun 30, 2023 | 8.44 Bn |
| Mar 31, 2023 | 8.24 Bn |
| Dec 31, 2022 | 8.79 Bn |
| Sep 30, 2022 | 8.64 Bn |
| Jun 30, 2022 | 8.88 Bn |
| Mar 31, 2022 | 8.98 Bn |
| Dec 31, 2021 | 9.09 Bn |
Abbott Laboratories 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=ABT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "ABT", "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=ABT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();