Autozone (AZO) Operating Expenses (2009 - 2026)
Autozone (AZO) posted Operating Expenses of $1.6 billion for fiscal Q3 2026 (quarter ended May 9, 2026), up 7.6% from $1.49 billion a year earlier and up 3.6% from the prior quarter.
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Analysis
Autozone (AZO) Operating Expenses (2009 - 2026) Analysis & Trends
For the trailing twelve months through May 9, 2026, Operating Expenses at Autozone was $6.74 billion, up 7.1% year-over-year; for FY2025 (ended Aug 30, 2025), it came in at $6.36 billion, up 5.4% from FY2024.
- Annual Operating Expenses has increased for six consecutive fiscal years, with a five-year compound annual growth rate of 7.9% (FY2020 to FY2025).
- In prior fiscal years, Autozone's Operating Expenses was $6.03 billion in FY2024 (+7.7%), $5.6 billion in FY2023 (+7.6%), $5.2 billion in FY2022 (+9.0%) and $4.77 billion in FY2021 (+9.7%).
- Quarterly Operating Expenses has run from a low of $1.16 billion in fiscal Q2 2022 to a high of $2.02 billion in fiscal Q4 2025 over five years.
- On a year-over-year basis, Operating Expenses has increased in each of the last 29 quarters, with growth averaging 7.5% over the last eight quarters.
- The year-over-year growth in Operating Expenses has ranged between 3.0% (fiscal Q4 2025) and 10.4% (fiscal Q1 2022) over the last five years.
- According to Business Quant data, Operating Expenses for the three prior fiscal quarters was $1.54 billion (Q2 2026), $1.58 billion (Q1 2026) and $2.02 billion (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,686.58 Bn | 2,203.28 Bn | 104.83 Bn | 173.15 Bn |
| 2 | Home Depot | 283.87 Bn | 277.11 Bn | 16.12 Bn | 9.28 Bn |
| 3 | Tjx Companies | 145.82 Bn | 123.36 Bn | 5.07 Bn | 3.09 Bn |
| 4 | Lowes Companies | 103.43 Bn | 96.39 Bn | 8.58 Bn | 4.46 Bn |
| 5 | Ross Stores | 74.61 Bn | 57.54 Bn | 2.12 Bn | 1.02 Bn |
| 6 | Target | 71.16 Bn | 65.74 Bn | 8.94 Bn | 5.73 Bn |
| 7 | O Reilly Automotive | 69.71 Bn | 68.80 Bn | 2.52 Bn | 1.53 Bn |
| 8 | Carvana | 68.78 Bn | 60.38 Bn | 1.38 Bn | 704.00 Mn |
| 9 | Autozone | 46.23 Bn | 45.13 Bn | 2.52 Bn | 1.60 Bn |
| 10 | JD.com | 32.27 Bn | -77.91 Bn | 8.71 Bn | -1.53 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| May 9, 2026 | 1.60 Bn |
| Feb 14, 2026 | 1.54 Bn |
| Nov 22, 2025 | 1.58 Bn |
| Aug 30, 2025 | 2.02 Bn |
| May 10, 2025 | 1.49 Bn |
| Feb 15, 2025 | 1.42 Bn |
| Nov 23, 2024 | 1.43 Bn |
| Aug 31, 2024 | 1.96 Bn |
| May 4, 2024 | 1.37 Bn |
| Feb 10, 2024 | 1.34 Bn |
| Nov 18, 2023 | 1.37 Bn |
| Aug 26, 2023 | 1.78 Bn |
| May 6, 2023 | 1.29 Bn |
| Feb 11, 2023 | 1.26 Bn |
| Nov 19, 2022 | 1.27 Bn |
| Aug 27, 2022 | 1.65 Bn |
| May 7, 2022 | 1.22 Bn |
| Feb 12, 2022 | 1.16 Bn |
| Nov 20, 2021 | 1.17 Bn |
| Aug 28, 2021 | 1.52 Bn |
API Access
Autozone 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=AZO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "AZO", "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=AZO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();