Eli Lilly (LLY) Operating Expenses (2009 - 2026)
Eli Lilly's Operating Expenses was $7.95 billion in Q2 2026, up 30.6% from $6.09 billion a year earlier and up 18.3% from the prior quarter.
Eli Lilly (LLY) Operating Expenses (2009 - 2026) Analysis & Trends
On a trailing twelve-month basis, Eli Lilly's Operating Expenses was $28.26 billion through Jun 30, 2026, up 28.3% year-over-year; for FY2025, it was $24.92 billion, up 21.9% from FY2024.
- Operating Expenses has now increased for seven consecutive years, with a five-year compound annual growth rate of 15.3% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $20.45 billion in FY2024 (+21.8%), $16.79 billion in FY2023 (+21.0%), $13.88 billion in FY2022 (+1.4%) and $13.68 billion in FY2021 (+11.9%).
- The Q2 2026 figure marks the highest quarterly Operating Expenses in data going back to Q1 2009.
- Compared with a year earlier, Operating Expenses has increased for 17 straight quarters, with growth averaging 23.8% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q3 2025 (growth of 33.7%); the worst was Q1 2022 (a decline of 8.4%).
- Per Business Quant data, LLY's Operating Expenses in the three quarters before Q2 2026 was $6.72 billion (Q1 2026), $7.02 billion (Q4 2025) and $6.57 billion (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Eli Lilly | 1,130.22 Bn | 1,098.81 Bn | 19.71 Bn | 7.95 Bn |
| 2 | Johnson & Johnson | 613.62 Bn | 532.15 Bn | 17.26 Bn | 10.12 Bn |
| 3 | AbbVie | 501.46 Bn | 474.57 Bn | 12.70 Bn | 10.56 Bn |
| 4 | Merck | 366.84 Bn | 321.22 Bn | 12.21 Bn | 12.80 Bn |
| 5 | Novartis Ag | 297.85 Bn | 261.84 Bn | 11.24 Bn | 6.09 Bn |
| 6 | Astrazeneca | 261.66 Bn | 235.34 Bn | 12.86 Bn | 9.70 Bn |
| 7 | Amgen | 235.39 Bn | 190.79 Bn | 7.24 Bn | 6.54 Bn |
| 8 | Gilead Sciences | 190.66 Bn | 164.86 Bn | 6.22 Bn | 18.20 Bn |
| 9 | Pfizer | 169.57 Bn | 116.22 Bn | 10.94 Bn | 6.68 Bn |
| 10 | Vertex Pharmaceuticals | 131.60 Bn | 103.61 Bn | 2.84 Bn | 2.09 Bn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 7.95 Bn |
| Mar 31, 2026 | 6.72 Bn |
| Dec 31, 2025 | 7.02 Bn |
| Sep 30, 2025 | 6.57 Bn |
| Jun 30, 2025 | 6.09 Bn |
| Mar 31, 2025 | 5.24 Bn |
| Dec 31, 2024 | 5.79 Bn |
| Sep 30, 2024 | 4.92 Bn |
| Jun 30, 2024 | 5.26 Bn |
| Mar 31, 2024 | 4.48 Bn |
| Dec 31, 2023 | 4.56 Bn |
| Sep 30, 2023 | 4.21 Bn |
| Jun 30, 2023 | 4.28 Bn |
| Mar 31, 2023 | 3.73 Bn |
| Dec 31, 2022 | 3.68 Bn |
| Sep 30, 2022 | 3.62 Bn |
| Jun 30, 2022 | 3.41 Bn |
| Mar 31, 2022 | 3.17 Bn |
| Dec 31, 2021 | 3.59 Bn |
| Sep 30, 2021 | 3.28 Bn |
Eli Lilly 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=LLY&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "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=operating-expenses&ticker=LLY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();