Group 1 Automotive (GPI) EBITDA (2010 - 2026)
Group 1 Automotive (GPI) posted EBITDA of $235.4 million for Q2 2026, down 16.9% from $283.2 million a year earlier and down 14.4% from the prior quarter.
Powered by 
Analysis
Group 1 Automotive (GPI) EBITDA (2010 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, EBITDA at Group 1 Automotive was $823.3 million, down 20.5% year-over-year; for FY2025, it was $860.5 million, down 16.1% from FY2024.
- Annual EBITDA has declined for three consecutive years, though with a five-year compound annual growth rate of 8.4% (FY2020 to FY2025).
- In prior years, Group 1 Automotive's EBITDA was $1.03 billion in FY2024 (-3.5%), $1.06 billion in FY2023 (-10.1%), $1.18 billion in FY2022 (+22.6%) and $965.8 million in FY2021 (+68.1%).
- Quarterly EBITDA has run from a low of $140.7 million in Q3 2025 to a high of $308.2 million in Q2 2022 over five years.
- On a year-over-year basis, EBITDA increased in three of the last eight quarters, with an average decline of 10.5%.
- The strongest year-over-year quarter for EBITDA in the past five years was Q1 2022, with growth of 80.0%; the weakest was Q3 2025, with a decline of 46.3%.
- According to Business Quant data, EBITDA for the three prior quarters was $275 million (Q1 2026), $172.2 million (Q4 2025) and $140.7 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,887.17 Bn | 2,383.84 Bn | 107.37 Bn | 49.03 Bn |
| 2 | Home Depot | 352.83 Bn | 346.07 Bn | 16.12 Bn | 7.95 Bn |
| 3 | Tjx Companies | 152.69 Bn | 130.24 Bn | 5.07 Bn | 2.33 Bn |
| 4 | Lowes Companies | 129.94 Bn | 122.90 Bn | 8.58 Bn | 4.20 Bn |
| 5 | Target | 75.44 Bn | 70.03 Bn | 8.94 Bn | 3.34 Bn |
| 6 | Ross Stores | 75.40 Bn | 58.32 Bn | 2.12 Bn | 1.24 Bn |
| 7 | O Reilly Automotive | 74.28 Bn | 73.37 Bn | 2.52 Bn | 1.13 Bn |
| 8 | Carvana | 54.79 Bn | 44.38 Bn | 1.52 Bn | 784.00 Mn |
| 9 | Autozone | 53.72 Bn | 52.57 Bn | 3.52 Bn | 1.54 Bn |
| 10 | Group 1 Automotive | 3.17 Bn | 2.05 Bn | 854.80 Mn | 233.30 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 233.30 Mn |
| Jun 30, 2026 | 235.40 Mn |
| Mar 31, 2026 | 275.00 Mn |
| Dec 31, 2025 | 172.20 Mn |
| Sep 30, 2025 | 140.70 Mn |
| Jun 30, 2025 | 283.20 Mn |
| Mar 31, 2025 | 264.40 Mn |
| Dec 31, 2024 | 226.40 Mn |
| Sep 30, 2024 | 262.20 Mn |
| Jun 30, 2024 | 270.20 Mn |
| Mar 31, 2024 | 267.20 Mn |
| Dec 31, 2023 | 218.90 Mn |
| Sep 30, 2023 | 285.40 Mn |
| Jun 30, 2023 | 294.70 Mn |
| Mar 31, 2023 | 264.60 Mn |
| Dec 31, 2022 | 265.10 Mn |
| Sep 30, 2022 | 302.50 Mn |
| Jun 30, 2022 | 308.20 Mn |
| Mar 31, 2022 | 307.50 Mn |
| Dec 31, 2021 | 251.40 Mn |
API Access
Group 1 Automotive EBITDA 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=ebitda&ticker=GPI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "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=ebitda&ticker=GPI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();