Lear (LEA) Operating Expenses (2010 - 2026)
Lear (LEA) recorded Operating Expenses of $197.5 million in Q2 2026, up 6.0% from $186.3 million a year earlier and up 3.8% from the prior quarter.
Powered by 
Analysis
Lear (LEA) Operating Expenses (2010 - 2026) Analysis & Trends
On a TTM basis, Lear's Operating Expenses came in at $736.7 million as of Jul 4, 2026, up 5.3% year-over-year; for FY2025, it came in at $707.6 million, up 0.7% from FY2024.
- Annual Operating Expenses has a five-year compound annual growth rate of 3.7% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $702.5 million in FY2024 (-1.7%), $714.7 million in FY2023 (+4.4%), $684.8 million in FY2022 (+6.5%) and $643.2 million in FY2021 (+9.2%).
- The Q2 2026 figure is the highest quarterly Operating Expenses in data going back to Q1 2010.
- On a year-over-year basis, Operating Expenses has increased for three consecutive quarters, with growth averaging 1.5% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 23.0% in Q4 2022, against a decline of 7.6% in Q1 2025 at the low end.
- Per Business Quant, the preceding three quarters came in at $190.3 million (Q1 2026), $182.5 million (Q4 2025) and $166.4 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Tesla | 1,148.52 Bn | 983.08 Bn | 4.75 Bn | 4.35 Bn |
| 2 | Toyota Motor | 242.17 Bn | -164.57 Bn | 20.95 Bn | 78.18 Bn |
| 3 | Ferrari | 145.86 Bn | 138.30 Bn | 1.18 Bn | 471.42 Mn |
| 4 | Honda Motor | 143.38 Bn | 10.76 Bn | 8.46 Bn | -34.70 Bn |
| 5 | General Motors | 67.56 Bn | -37.30 Bn | 7.33 Bn | 46.57 Bn |
| 6 | Ford Motor | 47.24 Bn | -95.23 Bn | 6.08 Bn | 47.66 Bn |
| 7 | Rivian Automotive | 20.35 Bn | -2.94 Bn | 179.00 Mn | 1.02 Bn |
| 8 | Magna International | 17.85 Bn | 15.41 Bn | 1.61 Bn | 273.20 Mn |
| 9 | Stellantis | 12.63 Bn | -153.36 Bn | 5.55 Bn | 4.85 Bn |
| 10 | Lear | 5.82 Bn | 2.04 Bn | 470.30 Mn | 197.50 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 4, 2026 | 197.50 Mn |
| Apr 4, 2026 | 190.30 Mn |
| Dec 31, 2025 | 182.50 Mn |
| Sep 27, 2025 | 166.40 Mn |
| Jun 28, 2025 | 186.30 Mn |
| Mar 29, 2025 | 172.40 Mn |
| Dec 31, 2024 | 166.60 Mn |
| Sep 28, 2024 | 174.10 Mn |
| Jun 29, 2024 | 175.30 Mn |
| Mar 30, 2024 | 186.50 Mn |
| Dec 31, 2023 | 172.60 Mn |
| Sep 30, 2023 | 182.50 Mn |
| Jul 1, 2023 | 182.80 Mn |
| Apr 1, 2023 | 176.80 Mn |
| Dec 31, 2022 | 172.40 Mn |
| Oct 1, 2022 | 163.90 Mn |
| Jul 2, 2022 | 171.20 Mn |
| Apr 2, 2022 | 177.30 Mn |
| Dec 31, 2021 | 140.20 Mn |
| Oct 2, 2021 | 163.30 Mn |
API Access
Lear 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=LEA&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "LEA", "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=LEA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();