Thermo Fisher Scientific (TMO) Operating Expenses (2009 - 2026)
Thermo Fisher Scientific (TMO) recorded Operating Expenses of $9.87 billion in Q3 2026, up 7.5% from $9.18 billion a year earlier but down 0.3% from the prior quarter.
Powered by 
Analysis
Thermo Fisher Scientific (TMO) Operating Expenses (2009 - 2026) Analysis & Trends
On a TTM basis, Thermo Fisher Scientific's Operating Expenses came in at $38.88 billion as of Sep 26, 2026, up 7.3% year-over-year; for FY2025, it was $36.81 billion, up 3.6% from FY2024.
- Annual Operating Expenses has a five-year compound annual growth rate of 8.5% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $35.54 billion in FY2024 (-1.3%), $36 billion in FY2023 (-1.4%), $36.52 billion in FY2022 (+25.1%) and $29.18 billion in FY2021 (+19.5%).
- Quarterly Operating Expenses has ranged from $8.16 billion in Q4 2021 to $9.96 billion in Q4 2025 over the past five years.
- On a year-over-year basis, Operating Expenses has increased for six consecutive quarters, with growth averaging 5.1% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 31.2% in Q1 2022, against a decline of 5.8% in Q4 2023 at the low end.
- Per Business Quant, the preceding three quarters came in at $9.91 billion (Q2 2026), $9.14 billion (Q1 2026) and $9.96 billion (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 258.21 Bn | 258.21 Bn | - | 9.87 Bn |
| 2 | Abbott Laboratories | 184.72 Bn | 184.72 Bn | - | 11.66 Bn |
| 3 | Danaher | 163.63 Bn | 147.44 Bn | 3.61 Bn | 2.48 Bn |
| 4 | Intuitive Surgical | 150.86 Bn | 131.14 Bn | 2.08 Bn | 1.49 Bn |
| 5 | Medtronic | 123.68 Bn | 88.93 Bn | 6.34 Bn | 4.06 Bn |
| 6 | Stryker | 111.91 Bn | 111.91 Bn | - | - |
| 7 | Boston Scientific | 61.64 Bn | 61.64 Bn | 3.43 Bn | - |
| 8 | Becton Dickinson | 54.28 Bn | 51.43 Bn | 2.32 Bn | 4.32 Bn |
| 9 | Edwards Lifesciences | 53.21 Bn | 37.22 Bn | 1.35 Bn | 840.10 Mn |
| 10 | Agilent Technologies | 49.54 Bn | 42.43 Bn | 1.04 Bn | 1.43 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 26, 2026 | 9.87 Bn |
| Jun 27, 2026 | 9.91 Bn |
| Mar 28, 2026 | 9.14 Bn |
| Dec 31, 2025 | 9.96 Bn |
| Sep 27, 2025 | 9.18 Bn |
| Jun 28, 2025 | 9.02 Bn |
| Mar 29, 2025 | 8.65 Bn |
| Dec 31, 2024 | 9.38 Bn |
| Sep 28, 2024 | 8.76 Bn |
| Jun 29, 2024 | 8.72 Bn |
| Mar 30, 2024 | 8.68 Bn |
| Dec 31, 2023 | 9.03 Bn |
| Sep 30, 2023 | 8.71 Bn |
| Jul 1, 2023 | 9.11 Bn |
| Apr 1, 2023 | 9.15 Bn |
| Dec 31, 2022 | 9.59 Bn |
| Oct 1, 2022 | 8.97 Bn |
| Jul 2, 2022 | 8.97 Bn |
| Apr 2, 2022 | 9.00 Bn |
| Dec 31, 2021 | 8.16 Bn |
API Access
Thermo Fisher Scientific 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=TMO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "TMO", "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=TMO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();