Genuine Parts (GPC) Cost of Revenue (2009 - 2026)
Genuine Parts' Cost of Revenue was $4.07 billion in Q2 2026, up 5.9% from $3.84 billion a year earlier and up 3.6% from the prior quarter.
Genuine Parts (GPC) Cost of Revenue (2009 - 2026) Analysis & Trends
On a trailing twelve-month basis, Genuine Parts' Cost of Revenue was $15.82 billion through Jun 30, 2026, up 5.4% year-over-year; for FY2025, it was $15.36 billion, up 2.6% from FY2024.
- Cost of Revenue has now increased for five consecutive years, with a five-year compound annual growth rate of 7.1% (FY2020 to FY2025).
- In earlier years, Cost of Revenue was $14.96 billion in FY2024 (+1.1%), $14.8 billion in FY2023 (+3.1%), $14.36 billion in FY2022 (+17.3%) and $12.24 billion in FY2021 (+12.4%).
- The Q2 2026 figure marks the highest quarterly Cost of Revenue in data going back to Q1 2009.
- Compared with a year earlier, Cost of Revenue has increased for five straight quarters, with growth averaging 3.6% over the last eight quarters.
- The best year-over-year quarter for Cost of Revenue over five years was Q3 2022 (growth of 18.9%); the worst was Q1 2024 (a decline of 1.1%).
- Per Business Quant data, GPC's Cost of Revenue in the three quarters before Q2 2026 was $3.93 billion (Q1 2026), $3.91 billion (Q4 2025) and $3.92 billion (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Cost of Rev (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,712.14 Bn | 2,228.84 Bn | 104.83 Bn | 95.78 Bn |
| 2 | Home Depot | 282.27 Bn | 275.52 Bn | 16.12 Bn | 31.75 Bn |
| 3 | Tjx Companies | 146.16 Bn | 123.70 Bn | 5.07 Bn | 10.11 Bn |
| 4 | Lowes Companies | 101.42 Bn | 94.39 Bn | 8.58 Bn | 17.38 Bn |
| 5 | Ross Stores | 73.06 Bn | 55.98 Bn | 2.12 Bn | 4.15 Bn |
| 6 | Target | 70.86 Bn | 65.45 Bn | 8.94 Bn | 17.60 Bn |
| 7 | Carvana | 70.11 Bn | 61.71 Bn | 1.38 Bn | 5.99 Bn |
| 8 | O Reilly Automotive | 69.29 Bn | 68.38 Bn | 2.52 Bn | 2.38 Bn |
| 9 | Autozone | 45.61 Bn | 44.51 Bn | 2.52 Bn | 2.32 Bn |
| 10 | Genuine Parts | 17.54 Bn | 15.59 Bn | 2.47 Bn | 4.07 Bn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 4.07 Bn |
| Mar 31, 2026 | 3.93 Bn |
| Dec 31, 2025 | 3.91 Bn |
| Sep 30, 2025 | 3.92 Bn |
| Jun 30, 2025 | 3.84 Bn |
| Mar 31, 2025 | 3.69 Bn |
| Dec 31, 2024 | 3.70 Bn |
| Sep 30, 2024 | 3.77 Bn |
| Jun 30, 2024 | 3.78 Bn |
| Mar 31, 2024 | 3.71 Bn |
| Dec 31, 2023 | 3.55 Bn |
| Sep 30, 2023 | 3.72 Bn |
| Jun 30, 2023 | 3.78 Bn |
| Mar 31, 2023 | 3.75 Bn |
| Dec 31, 2022 | 3.55 Bn |
| Sep 30, 2022 | 3.70 Bn |
| Jun 30, 2022 | 3.64 Bn |
| Mar 31, 2022 | 3.47 Bn |
| Dec 31, 2021 | 3.11 Bn |
| Sep 30, 2021 | 3.11 Bn |
Genuine Parts Cost of Revenue 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=cost-of-revenue&ticker=GPC&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "cost-of-revenue", "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=cost-of-revenue&ticker=GPC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();