O Reilly Automotive (ORLY) Cost of Revenue (2009 - 2026)
O Reilly Automotive's Cost of Revenue came in at $2.38 billion for Q2 2026, up 8.0% from $2.2 billion a year earlier and up 7.3% from the prior quarter.
O Reilly Automotive (ORLY) Cost of Revenue (2009 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, O Reilly Automotive reported Cost of Revenue of $8.98 billion, up 7.9% year-over-year; for FY2025, it came in at $8.61 billion, up 5.6% from FY2024.
- Cost of Revenue has increased in each of the last 16 years, with a five-year compound annual growth rate of 9.3% (FY2020 to FY2025).
- Going back by year, Cost of Revenue was $8.15 billion in FY2024 (+5.8%), $7.71 billion in FY2023 (+9.7%), $7.03 billion in FY2022 (+11.4%) and $6.31 billion in FY2021 (+14.3%).
- The Q2 2026 figure represents the highest quarterly Cost of Revenue in data going back to Q1 2009.
- Year-over-year, Cost of Revenue has increased for 66 consecutive quarters, with growth averaging 6.3% over the last eight quarters.
- The year-over-year growth in Cost of Revenue has ranged between 3.4% (Q3 2024) and 15.0% (Q4 2022) over the last five years.
- Business Quant data shows ORLY's Cost of Revenue at $2.21 billion (Q1 2026), $2.13 billion (Q4 2025) and $2.27 billion (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Cost of Rev (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,654.24 Bn | 2,170.93 Bn | 104.83 Bn | 95.78 Bn |
| 2 | Home Depot | 289.19 Bn | 282.43 Bn | 16.12 Bn | 31.75 Bn |
| 3 | Tjx Companies | 143.39 Bn | 120.94 Bn | 5.07 Bn | 10.11 Bn |
| 4 | Lowes Companies | 105.29 Bn | 98.25 Bn | 8.58 Bn | 17.38 Bn |
| 5 | Ross Stores | 75.79 Bn | 58.72 Bn | 2.12 Bn | 4.15 Bn |
| 6 | Target | 72.00 Bn | 66.59 Bn | 8.94 Bn | 17.60 Bn |
| 7 | O Reilly Automotive | 70.61 Bn | 69.69 Bn | 2.52 Bn | 2.38 Bn |
| 8 | Carvana | 66.52 Bn | 58.12 Bn | 1.38 Bn | 5.99 Bn |
| 9 | Autozone | 47.57 Bn | 46.47 Bn | 2.52 Bn | 2.32 Bn |
| 10 | JD.com | 32.28 Bn | -77.90 Bn | 8.71 Bn | 42.31 Bn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 2.38 Bn |
| Mar 31, 2026 | 2.21 Bn |
| Dec 31, 2025 | 2.13 Bn |
| Sep 30, 2025 | 2.27 Bn |
| Jun 30, 2025 | 2.20 Bn |
| Mar 31, 2025 | 2.02 Bn |
| Dec 31, 2024 | 1.99 Bn |
| Sep 30, 2024 | 2.11 Bn |
| Jun 30, 2024 | 2.10 Bn |
| Mar 31, 2024 | 1.94 Bn |
| Dec 31, 2023 | 1.86 Bn |
| Sep 30, 2023 | 2.04 Bn |
| Jun 30, 2023 | 1.98 Bn |
| Mar 31, 2023 | 1.82 Bn |
| Dec 31, 2022 | 1.79 Bn |
| Sep 30, 2022 | 1.86 Bn |
| Jun 30, 2022 | 1.79 Bn |
| Mar 31, 2022 | 1.59 Bn |
| Dec 31, 2021 | 1.56 Bn |
| Sep 30, 2021 | 1.66 Bn |
O Reilly Automotive 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=ORLY&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "cost-of-revenue", "ticker": "ORLY", "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=ORLY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();