Local Bounti Corporation (LOCL) Operating Expenses (2021 - 2026)
Local Bounti Corporation (LOCL) posted Operating Expenses of $14.99 million for Q2 2026, down 11.4% from $16.92 million a year earlier and down 3.1% from the prior quarter.
Local Bounti Corporation (LOCL) Operating Expenses (2021 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Local Bounti Corporation was $64.83 million, down 8.5% year-over-year; for FY2025, it was $68.49 million, up 8.6% from FY2024.
- Annual Operating Expenses shows a five-year compound annual growth rate of 54.0% (FY2020 to FY2025).
- In prior years, Local Bounti Corporation's Operating Expenses was $63.06 million in FY2024 (-47.1%), $119.13 million in FY2023 (+23.1%), $96.74 million in FY2022 (+115.3%) and $44.92 million in FY2021 (+467.7%).
- Quarterly Operating Expenses has run from a low of $5.69 million in Q3 2021 to a high of $59.93 million in Q4 2023 over five years.
- On a year-over-year basis, Operating Expenses has declined in each of the last three quarters, with an average decline of 5.0% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q2 2022, with growth of 611.4%; the weakest was Q4 2024, with a decline of 71.1%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $15.47 million (Q1 2026), $14.74 million (Q4 2025) and $19.63 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Archer-Daniels-Midland | 38.28 Bn | 34.57 Bn | 1.94 Bn | 1.04 Bn |
| 2 | Bunge Global | 20.79 Bn | 18.30 Bn | 1.68 Bn | 606.00 Mn |
| 3 | Tyson Foods | 17.93 Bn | 14.29 Bn | 921.00 Mn | 559.00 Mn |
| 4 | Jbs | 12.60 Bn | -20.51 Bn | 2.59 Bn | 1.99 Bn |
| 5 | Darling Ingredients | 9.52 Bn | 9.12 Bn | 503.37 Mn | 1.52 Bn |
| 6 | Smithfield Foods | 7.49 Bn | 2.44 Bn | 478.00 Mn | 191.00 Mn |
| 7 | Pilgrims Pride | 6.49 Bn | 4.32 Bn | 339.75 Mn | 273.80 Mn |
| 8 | Ingredion | 6.09 Bn | 2.26 Bn | 426.00 Mn | 45.00 Mn |
| 9 | Seaboard | 3.89 Bn | -931.52 Mn | 221.00 Mn | 121.00 Mn |
| 10 | Local Bounti Corporation | 29.94 Mn | 29.94 Mn | 1.05 Mn | 14.99 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 14.99 Mn |
| Mar 31, 2026 | 15.47 Mn |
| Dec 31, 2025 | 14.74 Mn |
| Sep 30, 2025 | 19.63 Mn |
| Jun 30, 2025 | 16.92 Mn |
| Mar 31, 2025 | 17.20 Mn |
| Dec 31, 2024 | 17.31 Mn |
| Sep 30, 2024 | 19.44 Mn |
| Jun 30, 2024 | 15.22 Mn |
| Mar 31, 2024 | 11.09 Mn |
| Dec 31, 2023 | 59.93 Mn |
| Sep 30, 2023 | 19.41 Mn |
| Jun 30, 2023 | 20.23 Mn |
| Mar 31, 2023 | 19.56 Mn |
| Dec 31, 2022 | 23.07 Mn |
| Sep 30, 2022 | 23.26 Mn |
| Jun 30, 2022 | 26.21 Mn |
| Mar 31, 2022 | 24.21 Mn |
| Dec 31, 2021 | 26.83 Mn |
| Sep 30, 2021 | 5.69 Mn |
Local Bounti Corporation 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=LOCL&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "LOCL", "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=LOCL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();