Group 1 Automotive (GPI) Operating Expenses (2010 - 2026)
Group 1 Automotive (GPI) recorded Operating Expenses of $625.6 million in Q2 2026, down 4.3% from $653.7 million a year earlier but up 4.0% from the prior quarter.
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Analysis
Group 1 Automotive (GPI) Operating Expenses (2010 - 2026) Analysis & Trends
On a TTM basis, Group 1 Automotive's Operating Expenses came in at $2.52 billion as of Jun 30, 2026, up 0.6% year-over-year; for FY2025, it came in at $2.57 billion, up 17.2% from FY2024.
- Annual Operating Expenses has increased for five straight years, with a five-year compound annual growth rate of 17.7% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $2.2 billion in FY2024 (+14.0%), $1.93 billion in FY2023 (+8.0%), $1.78 billion in FY2022 (+20.7%) and $1.48 billion in FY2021 (+29.8%).
- Quarterly Operating Expenses has ranged from $376.3 million in Q3 2021 to $656.5 million in Q3 2025 over the past five years.
- On a year-over-year basis, Operating Expenses rose in six of the last eight quarters, with growth averaging 14.4%.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 57.5% in Q4 2021, against a decline of 4.3% in Q2 2026 at the low end.
- Per Business Quant, the preceding three quarters came in at $601.6 million (Q1 2026), $635.4 million (Q4 2025) and $656.5 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,833.63 Bn | 2,350.32 Bn | 104.83 Bn | 173.15 Bn |
| 2 | Home Depot | 313.41 Bn | 306.65 Bn | 16.12 Bn | 9.28 Bn |
| 3 | Tjx Companies | 161.70 Bn | 139.25 Bn | 5.07 Bn | 3.09 Bn |
| 4 | Lowes Companies | 111.03 Bn | 103.99 Bn | 8.58 Bn | 4.46 Bn |
| 5 | Ross Stores | 75.23 Bn | 58.15 Bn | 2.12 Bn | 1.02 Bn |
| 6 | O Reilly Automotive | 74.16 Bn | 73.25 Bn | 2.52 Bn | 1.53 Bn |
| 7 | Target | 70.22 Bn | 64.81 Bn | 8.94 Bn | 5.73 Bn |
| 8 | Autozone | 51.95 Bn | 50.86 Bn | 2.52 Bn | 1.60 Bn |
| 9 | Carvana | 43.24 Bn | 33.73 Bn | 1.38 Bn | 704.00 Mn |
| 10 | Group 1 Automotive | 2.85 Bn | 2.58 Bn | 860.60 Mn | 625.60 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 625.60 Mn |
| Mar 31, 2026 | 601.60 Mn |
| Dec 31, 2025 | 635.40 Mn |
| Sep 30, 2025 | 656.50 Mn |
| Jun 30, 2025 | 653.70 Mn |
| Mar 31, 2025 | 628.40 Mn |
| Dec 31, 2024 | 631.00 Mn |
| Sep 30, 2024 | 591.60 Mn |
| Jun 30, 2024 | 497.20 Mn |
| Mar 31, 2024 | 476.10 Mn |
| Dec 31, 2023 | 487.40 Mn |
| Sep 30, 2023 | 496.70 Mn |
| Jun 30, 2023 | 479.90 Mn |
| Mar 31, 2023 | 462.80 Mn |
| Dec 31, 2022 | 453.70 Mn |
| Sep 30, 2022 | 450.90 Mn |
| Jun 30, 2022 | 460.20 Mn |
| Mar 31, 2022 | 418.50 Mn |
| Dec 31, 2021 | 421.00 Mn |
| Sep 30, 2021 | 376.30 Mn |
API Access
Group 1 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=GPI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "GPI", "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=GPI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();