Genuine Parts (GPC) Operating Expenses (2009 - 2026)
Genuine Parts (GPC) posted Operating Expenses of $2.13 billion for Q2 2026, up 9.6% from $1.95 billion a year earlier and up 4.0% from the prior quarter.
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Analysis
Genuine Parts (GPC) Operating Expenses (2009 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Genuine Parts was $8.33 billion, up 9.8% year-over-year; for FY2025, it came in at $7.98 billion, up 9.4% from FY2024.
- Annual Operating Expenses has increased for ten consecutive years, with a five-year compound annual growth rate of 8.8% (FY2020 to FY2025).
- In prior years, Genuine Parts' Operating Expenses was $7.29 billion in FY2024 (+11.5%), $6.54 billion in FY2023 (+6.8%), $6.13 billion in FY2022 (+12.0%) and $5.47 billion in FY2021 (+4.4%).
- Quarterly Operating Expenses has run from a low of $1.36 billion in Q4 2021 to a high of $2.14 billion in Q4 2025 over five years.
- On a year-over-year basis, Operating Expenses has increased in each of the last ten quarters, with growth averaging 10.8% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q4 2022, with growth of 20.0%; the weakest was Q4 2023, with a decline of 0.7%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $2.05 billion (Q1 2026), $2.14 billion (Q4 2025) and $2.01 billion (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,659.84 Bn | 2,176.54 Bn | 104.83 Bn | 173.15 Bn |
| 2 | Home Depot | 287.59 Bn | 280.83 Bn | 16.12 Bn | 9.28 Bn |
| 3 | Tjx Companies | 147.38 Bn | 124.93 Bn | 5.07 Bn | 3.09 Bn |
| 4 | Lowes Companies | 105.03 Bn | 97.99 Bn | 8.58 Bn | 4.46 Bn |
| 5 | Ross Stores | 74.93 Bn | 57.86 Bn | 2.12 Bn | 1.02 Bn |
| 6 | Target | 71.05 Bn | 65.64 Bn | 8.94 Bn | 5.73 Bn |
| 7 | O Reilly Automotive | 70.25 Bn | 69.33 Bn | 2.52 Bn | 1.53 Bn |
| 8 | Carvana | 69.96 Bn | 61.56 Bn | 1.38 Bn | 704.00 Mn |
| 9 | Autozone | 46.92 Bn | 45.82 Bn | 2.52 Bn | 1.60 Bn |
| 10 | Genuine Parts | 17.51 Bn | 15.56 Bn | 2.47 Bn | 2.13 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 2.13 Bn |
| Mar 31, 2026 | 2.05 Bn |
| Dec 31, 2025 | 2.14 Bn |
| Sep 30, 2025 | 2.01 Bn |
| Jun 30, 2025 | 1.95 Bn |
| Mar 31, 2025 | 1.89 Bn |
| Dec 31, 2024 | 1.88 Bn |
| Sep 30, 2024 | 1.88 Bn |
| Jun 30, 2024 | 1.78 Bn |
| Mar 31, 2024 | 1.75 Bn |
| Dec 31, 2023 | 1.61 Bn |
| Sep 30, 2023 | 1.64 Bn |
| Jun 30, 2023 | 1.68 Bn |
| Mar 31, 2023 | 1.60 Bn |
| Dec 31, 2022 | 1.63 Bn |
| Sep 30, 2022 | 1.55 Bn |
| Jun 30, 2022 | 1.45 Bn |
| Mar 31, 2022 | 1.50 Bn |
| Dec 31, 2021 | 1.36 Bn |
| Sep 30, 2021 | 1.42 Bn |
API Access
Genuine Parts 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=GPC&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "GPC", "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=GPC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();