Pattern (PTRN) Operating Expenses (2024 - 2026)
Pattern's Operating Expenses came in at $841.24 million for Q2 2026, up 48.1% from $568.02 million a year earlier and up 14.6% from the prior quarter.
Pattern (PTRN) Operating Expenses (2024 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Pattern reported Operating Expenses of $2.97 billion, up 49.1% year-over-year; for FY2025, it came in at $2.48 billion, up 44.9% from FY2024.
- Going back by year, Operating Expenses was $1.71 billion in FY2024 (+30.1%) and $1.31 billion in FY2023.
- The Q2 2026 figure represents the highest quarterly Operating Expenses in data going back to Q3 2024.
- Year-over-year, Operating Expenses has increased for four consecutive quarters, with growth averaging 49.8% over the last four quarters.
- Business Quant data shows PTRN's Operating Expenses at $734.16 million (Q1 2026), $697.06 million (Q4 2025) and $699.83 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,654.24 Bn | 2,170.93 Bn | 104.83 Bn | 173.15 Bn |
| 2 | Home Depot | 289.19 Bn | 282.43 Bn | 16.12 Bn | 9.28 Bn |
| 3 | Tjx Companies | 143.39 Bn | 120.94 Bn | 5.07 Bn | 3.09 Bn |
| 4 | Lowes Companies | 105.29 Bn | 98.25 Bn | 8.58 Bn | 4.46 Bn |
| 5 | Ross Stores | 75.79 Bn | 58.72 Bn | 2.12 Bn | 1.02 Bn |
| 6 | Target | 72.00 Bn | 66.59 Bn | 8.94 Bn | 5.73 Bn |
| 7 | O Reilly Automotive | 70.61 Bn | 69.69 Bn | 2.52 Bn | 1.53 Bn |
| 8 | Carvana | 66.52 Bn | 58.12 Bn | 1.38 Bn | 704.00 Mn |
| 9 | Autozone | 47.57 Bn | 46.47 Bn | 2.52 Bn | 1.60 Bn |
| 10 | Pattern | 2.61 Bn | 1.31 Bn | 384.36 Mn | 841.24 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 841.24 Mn |
| Mar 31, 2026 | 734.16 Mn |
| Dec 31, 2025 | 697.06 Mn |
| Sep 30, 2025 | 699.83 Mn |
| Jun 30, 2025 | 568.02 Mn |
| Mar 31, 2025 | 511.00 Mn |
| Dec 31, 2024 | 492.34 Mn |
| Sep 30, 2024 | 421.74 Mn |
Pattern 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=PTRN&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "PTRN", "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=PTRN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();