Thermo Fisher Scientific (TMO) Total Liabilities (2009 - 2026)
Thermo Fisher Scientific's Total Liabilities came in at $60.49 billion for Q2 2026, up 19.2% from $50.75 billion a year earlier but down 1.4% from the prior quarter.
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Analysis
Thermo Fisher Scientific (TMO) Total Liabilities (2009 - 2026) Analysis & Trends
At the end of FY2025, Thermo Fisher Scientific's Total Liabilities was $56.93 billion, up 19.2% from FY2024.
- Total Liabilities carries a five-year compound annual growth rate of 10.5% (FY2020 to FY2025).
- Going back by year, Total Liabilities was $47.77 billion in FY2024 (-8.1%), $52 billion in FY2023 (-2.1%), $53.12 billion in FY2022 (-2.1%) and $54.27 billion in FY2021 (+57.1%).
- The five-year range for quarterly Total Liabilities is $34.84 billion (Q3 2021) to $61.34 billion (Q1 2026).
- Year-over-year, Total Liabilities has increased for four consecutive quarters, with growth averaging 6.2% over the last eight quarters.
- The fastest year-over-year change in Total Liabilities over five years came in Q1 2022 (growth of 67.6%), and the weakest in Q4 2024 (a decline of 8.1%).
- Business Quant data shows TMO's Total Liabilities at $61.34 billion (Q1 2026), $56.93 billion (Q4 2025) and $52 billion (Q3 2025) in the three quarters before Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 259.67 Bn | 236.18 Bn | 5.13 Bn | 59.47 Bn |
| 2 | Abbott Laboratories | 201.04 Bn | 171.47 Bn | 7.27 Bn | 57.45 Bn |
| 3 | Intuitive Surgical | 168.15 Bn | 148.44 Bn | 2.08 Bn | 3.23 Bn |
| 4 | Danaher | 165.12 Bn | 144.78 Bn | 3.84 Bn | 39.65 Bn |
| 5 | Medtronic | 134.78 Bn | 100.03 Bn | 6.34 Bn | 42.46 Bn |
| 6 | Stryker | 130.30 Bn | 116.49 Bn | 4.25 Bn | 23.79 Bn |
| 7 | Boston Scientific | 66.68 Bn | 62.11 Bn | 3.43 Bn | 19.59 Bn |
| 8 | Edwards Lifesciences | 59.17 Bn | 42.38 Bn | 1.35 Bn | 3.18 Bn |
| 9 | Becton Dickinson | 58.15 Bn | 55.30 Bn | 2.32 Bn | 26.32 Bn |
| 10 | Agilent Technologies | 48.88 Bn | 41.77 Bn | 1.04 Bn | 6.60 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 26, 2026 | 59.47 Bn |
| Jun 27, 2026 | 60.49 Bn |
| Mar 28, 2026 | 61.34 Bn |
| Dec 31, 2025 | 56.93 Bn |
| Sep 27, 2025 | 52.00 Bn |
| Jun 28, 2025 | 50.75 Bn |
| Mar 29, 2025 | 49.68 Bn |
| Dec 31, 2024 | 47.77 Bn |
| Sep 28, 2024 | 51.39 Bn |
| Jun 29, 2024 | 51.08 Bn |
| Mar 30, 2024 | 51.59 Bn |
| Dec 31, 2023 | 52.00 Bn |
| Sep 30, 2023 | 51.71 Bn |
| Jul 1, 2023 | 50.30 Bn |
| Apr 1, 2023 | 52.35 Bn |
| Dec 31, 2022 | 53.12 Bn |
| Oct 1, 2022 | 46.93 Bn |
| Jul 2, 2022 | 48.23 Bn |
| Apr 2, 2022 | 51.73 Bn |
| Dec 31, 2021 | 54.27 Bn |
API Access
Thermo Fisher Scientific Total Liabilities 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=total-liabilities&ticker=TMO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "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=total-liabilities&ticker=TMO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();