Agilent Technologies (A) Total Liabilities (2009 - 2026)
Agilent Technologies' Total Liabilities was $6.6 billion in fiscal Q3 2026 (quarter ended Jul 31, 2026), up 12.8% from $5.86 billion a year earlier and up 11.1% from the prior quarter.
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Analysis
Agilent Technologies (A) Total Liabilities (2009 - 2026) Analysis & Trends
At the end of FY2025 (ended Oct 31, 2025), Total Liabilities at Agilent Technologies came in at $5.99 billion, up 0.6% from FY2024.
- Total Liabilities shows a five-year compound annual growth rate of 4.7% (FY2020 to FY2025).
- In earlier fiscal years, Total Liabilities was $5.95 billion in FY2024 (-46.4%), $11.09 billion in FY2023 (+112.2%), $5.23 billion in FY2022 (-1.7%) and $5.32 billion in FY2021 (+11.8%).
- The fiscal Q3 2026 figure marks the highest quarterly Total Liabilities since fiscal Q4 2023.
- Compared with a year earlier, Total Liabilities was higher in six of the last eight quarters, with growth averaging 4.3%.
- The best year-over-year quarter for Total Liabilities over five years was fiscal Q4 2023 (growth of 112.2%); the worst was fiscal Q4 2024 (a decline of 46.4%).
- Per Business Quant data, A's Total Liabilities in the three fiscal quarters before Q3 2026 was $5.94 billion (Q2 2026), $5.91 billion (Q1 2026) and $5.99 billion (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 243.20 Bn | 222.35 Bn | 4.88 Bn | 60.49 Bn |
| 2 | Abbott Laboratories | 172.35 Bn | 143.43 Bn | 7.27 Bn | 57.45 Bn |
| 3 | Danaher | 154.53 Bn | 138.35 Bn | 3.61 Bn | 39.78 Bn |
| 4 | Intuitive Surgical | 150.04 Bn | 129.59 Bn | 1.96 Bn | 2.58 Bn |
| 5 | Medtronic | 113.25 Bn | 79.11 Bn | 6.34 Bn | 42.46 Bn |
| 6 | Stryker | 106.37 Bn | 92.49 Bn | 4.50 Bn | 23.94 Bn |
| 7 | Boston Scientific | 61.94 Bn | 56.95 Bn | 3.85 Bn | 20.04 Bn |
| 8 | Becton Dickinson | 50.05 Bn | 47.20 Bn | 2.32 Bn | 26.32 Bn |
| 9 | Edwards Lifesciences | 49.13 Bn | 33.24 Bn | 1.35 Bn | 3.14 Bn |
| 10 | Agilent Technologies | 48.07 Bn | 40.96 Bn | 1.04 Bn | 6.60 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | 6.60 Bn |
| Apr 30, 2026 | 5.94 Bn |
| Jan 31, 2026 | 5.91 Bn |
| Oct 31, 2025 | 5.99 Bn |
| Jul 31, 2025 | 5.86 Bn |
| Apr 30, 2025 | 6.02 Bn |
| Jan 31, 2025 | 5.89 Bn |
| Oct 31, 2024 | 5.95 Bn |
| Jul 31, 2024 | 5.09 Bn |
| Apr 30, 2024 | 4.64 Bn |
| Jan 31, 2024 | 4.76 Bn |
| Oct 31, 2023 | 11.09 Bn |
| Jul 31, 2023 | 5.12 Bn |
| Apr 30, 2023 | 5.01 Bn |
| Jan 31, 2023 | 5.31 Bn |
| Oct 31, 2022 | 5.23 Bn |
| Jul 31, 2022 | 5.39 Bn |
| Apr 30, 2022 | 5.33 Bn |
| Jan 31, 2022 | 5.17 Bn |
| Oct 31, 2021 | 5.32 Bn |
API Access
Agilent Technologies 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=A&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "A", "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=A&period=max&api_key=YOUR_API_KEY");
const data = await res.json();