Sonic Automotive (SAH) Operating Expenses (2010 - 2026)
Sonic Automotive (SAH) recorded Operating Expenses of $449.2 million in Q2 2026, up 8.9% from $412.6 million a year earlier and up 4.1% from the prior quarter.
Sonic Automotive (SAH) Operating Expenses (2010 - 2026) Analysis & Trends
On a TTM basis, Sonic Automotive's Operating Expenses came in at $1.77 billion as of Jun 30, 2026, up 11.5% year-over-year; for FY2025, it came in at $1.68 billion, up 6.4% from FY2024.
- Annual Operating Expenses has a five-year compound annual growth rate of 10.3% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $1.58 billion in FY2024 (-1.5%), $1.6 billion in FY2023 (+2.9%), $1.56 billion in FY2022 (+22.0%) and $1.27 billion in FY2021 (+23.9%).
- Quarterly Operating Expenses has ranged from $321.4 million in Q3 2021 to $451.6 million in Q3 2025 over the past five years.
- On a year-over-year basis, Operating Expenses has increased for five consecutive quarters, with growth averaging 5.9% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 33.7% in Q1 2022, against a decline of 5.0% in Q1 2024 at the low end.
- Per Business Quant, the preceding three quarters came in at $431.6 million (Q1 2026), $433.7 million (Q4 2025) and $451.6 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,786.69 Bn | 2,303.39 Bn | 104.83 Bn | 173.15 Bn |
| 2 | Home Depot | 292.25 Bn | 285.49 Bn | 16.12 Bn | 9.28 Bn |
| 3 | Tjx Companies | 156.35 Bn | 133.89 Bn | 5.07 Bn | 3.09 Bn |
| 4 | Lowes Companies | 105.35 Bn | 98.31 Bn | 8.58 Bn | 4.46 Bn |
| 5 | Ross Stores | 71.70 Bn | 54.63 Bn | 2.12 Bn | 1.02 Bn |
| 6 | O Reilly Automotive | 70.98 Bn | 70.07 Bn | 2.52 Bn | 1.53 Bn |
| 7 | Target | 68.97 Bn | 63.56 Bn | 8.94 Bn | 5.73 Bn |
| 8 | Autozone | 47.65 Bn | 46.55 Bn | 2.52 Bn | 1.60 Bn |
| 9 | Carvana | 43.47 Bn | 33.96 Bn | 1.38 Bn | 704.00 Mn |
| 10 | Sonic Automotive | 1.93 Bn | 1.80 Bn | 616.20 Mn | 449.20 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 449.20 Mn |
| Mar 31, 2026 | 431.60 Mn |
| Dec 31, 2025 | 433.70 Mn |
| Sep 30, 2025 | 451.60 Mn |
| Jun 30, 2025 | 412.60 Mn |
| Mar 31, 2025 | 380.30 Mn |
| Dec 31, 2024 | 399.60 Mn |
| Sep 30, 2024 | 392.10 Mn |
| Jun 30, 2024 | 393.00 Mn |
| Mar 31, 2024 | 392.20 Mn |
| Dec 31, 2023 | 386.30 Mn |
| Sep 30, 2023 | 409.60 Mn |
| Jun 30, 2023 | 391.90 Mn |
| Mar 31, 2023 | 412.80 Mn |
| Dec 31, 2022 | 366.30 Mn |
| Sep 30, 2022 | 399.00 Mn |
| Jun 30, 2022 | 402.80 Mn |
| Mar 31, 2022 | 387.00 Mn |
| Dec 31, 2021 | 343.40 Mn |
| Sep 30, 2021 | 321.40 Mn |
Sonic Automotive 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=SAH&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "SAH", "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=SAH&period=max&api_key=YOUR_API_KEY");
const data = await res.json();