Eli Lilly (LLY) Total Liabilities (2009 - 2026)
Eli Lilly (LLY) posted Total Liabilities of $108.4 billion for Q2 2026, up 31.3% from $82.57 billion a year earlier and up 27.0% from the prior quarter.
Eli Lilly (LLY) Total Liabilities (2009 - 2026) Analysis & Trends
At the end of FY2025, Eli Lilly's Total Liabilities came in at $85.94 billion, up 33.4% from FY2024.
- Annual Total Liabilities has increased for three consecutive years, with a five-year compound annual growth rate of 16.1% (FY2020 to FY2025).
- In prior years, Eli Lilly's Total Liabilities was $64.44 billion in FY2024 (+21.3%), $53.14 billion in FY2023 (+37.3%), $38.71 billion in FY2022 (-2.4%) and $39.65 billion in FY2021 (-2.8%).
- The Q2 2026 figure stands as the highest quarterly Total Liabilities in data going back to Q2 2009.
- On a year-over-year basis, Total Liabilities has increased in each of the last 14 quarters, with growth averaging 33.5% over the last eight quarters.
- The strongest year-over-year quarter for Total Liabilities in the past five years was Q3 2025, with growth of 48.6%; the weakest was Q3 2022, with a decline of 7.3%.
- According to Business Quant data, Total Liabilities for the three prior quarters was $85.38 billion (Q1 2026), $85.94 billion (Q4 2025) and $91.08 billion (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,146.94 Bn | 1,115.53 Bn | 19.71 Bn | 108.40 Bn |
| 2 | Johnson & Johnson | 624.96 Bn | 543.49 Bn | 17.26 Bn | 116.09 Bn |
| 3 | AbbVie | 510.15 Bn | 483.27 Bn | 12.70 Bn | 141.05 Bn |
| 4 | Merck | 366.13 Bn | 320.51 Bn | 12.21 Bn | 87.82 Bn |
| 5 | Novartis Ag | 297.75 Bn | 261.74 Bn | 11.24 Bn | 80.09 Bn |
| 6 | Astrazeneca | 261.93 Bn | 235.62 Bn | 12.86 Bn | 65.46 Bn |
| 7 | Amgen | 236.51 Bn | 191.91 Bn | 7.24 Bn | 83.95 Bn |
| 8 | Gilead Sciences | 194.27 Bn | 168.47 Bn | 6.22 Bn | 37.53 Bn |
| 9 | Pfizer | 171.74 Bn | 118.39 Bn | 10.94 Bn | 115.64 Bn |
| 10 | Vertex Pharmaceuticals | 130.00 Bn | 102.01 Bn | 2.84 Bn | 7.18 Bn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 108.40 Bn |
| Mar 31, 2026 | 85.38 Bn |
| Dec 31, 2025 | 85.94 Bn |
| Sep 30, 2025 | 91.08 Bn |
| Jun 30, 2025 | 82.57 Bn |
| Mar 31, 2025 | 73.54 Bn |
| Dec 31, 2024 | 64.44 Bn |
| Sep 30, 2024 | 61.29 Bn |
| Jun 30, 2024 | 58.24 Bn |
| Mar 31, 2024 | 51.05 Bn |
| Dec 31, 2023 | 53.14 Bn |
| Sep 30, 2023 | 46.61 Bn |
| Jun 30, 2023 | 43.66 Bn |
| Mar 31, 2023 | 41.87 Bn |
| Dec 31, 2022 | 38.71 Bn |
| Sep 30, 2022 | 37.30 Bn |
| Jun 30, 2022 | 38.40 Bn |
| Mar 31, 2022 | 37.46 Bn |
| Dec 31, 2021 | 39.65 Bn |
| Sep 30, 2021 | 40.23 Bn |
Eli Lilly 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=LLY&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "LLY", "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=LLY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();