BJs RESTAURANTS (BJRI) Operating Expenses (2010 - 2026)
BJs RESTAURANTS (BJRI) reported Operating Expenses of $370.45 million for Q2 2026, up 7.6% from $344.38 million a year earlier and up 6.6% from the prior quarter.
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Analysis
BJs RESTAURANTS (BJRI) Operating Expenses (2010 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, BJs RESTAURANTS's Operating Expenses came in at $1.39 billion, up 2.8% year-over-year; for FY2025, it came in at $1.35 billion, up 0.7% from FY2024.
- Operating Expenses has a five-year compound annual growth rate of 9.4% (FY2020 to FY2025).
- By year, Operating Expenses came in at $1.34 billion in FY2024 (+1.8%), $1.32 billion in FY2023 and $1.1 billion in FY2021 (+27.6%).
- The Q2 2026 figure ranks as the highest quarterly Operating Expenses in data going back to Q2 2010.
- Year over year, Operating Expenses gained in five of the last seven quarters, with growth averaging 1.3%.
- The high point for year-over-year Operating Expenses in five years was Q4 2021 (growth of 37.7%); the low point was Q4 2024 (a decline of 5.6%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $347.5 million (Q1 2026), $344.26 million (Q4 2025) and $331.15 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 163.51 Bn | 158.34 Bn | 6.42 Bn | 3.76 Bn |
| 2 | Starbucks | 107.11 Bn | 94.75 Bn | - | 8.42 Bn |
| 3 | Chipotle Mexican Grill | 40.42 Bn | 36.40 Bn | - | 2.82 Bn |
| 4 | Yum Brands | 37.23 Bn | 34.12 Bn | 1.47 Bn | 1.51 Bn |
| 5 | Restaurant Brands International | 24.82 Bn | 21.92 Bn | 1.38 Bn | 1.80 Bn |
| 6 | Darden Restaurants | 22.06 Bn | 21.17 Bn | -113.70 Mn | 3.20 Bn |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 12.57 Bn | 1.38 Bn | 1.80 Bn |
| 8 | Yum China Holdings | 14.18 Bn | 8.54 Bn | 537.00 Mn | 2.79 Bn |
| 9 | Texas Roadhouse | 10.25 Bn | 9.62 Bn | - | 1.54 Bn |
| 10 | BJs RESTAURANTS | 1.21 Bn | 1.13 Bn | 289.79 Mn | 370.45 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 370.45 Mn |
| Mar 31, 2026 | 347.50 Mn |
| Dec 30, 2025 | 344.26 Mn |
| Sep 30, 2025 | 331.15 Mn |
| Jul 1, 2025 | 344.38 Mn |
| Apr 1, 2025 | 333.02 Mn |
| Dec 31, 2024 | 349.13 Mn |
| Oct 1, 2024 | 328.31 Mn |
| Jul 2, 2024 | 336.71 Mn |
| Apr 2, 2024 | 329.08 Mn |
| Jan 2, 2024 | 369.98 Mn |
| Oct 3, 2023 | 321.03 Mn |
| Jul 4, 2023 | 339.46 Mn |
| Apr 4, 2023 | 338.66 Mn |
| Sep 27, 2022 | 316.52 Mn |
| Jun 28, 2022 | 326.55 Mn |
| Mar 29, 2022 | 306.42 Mn |
| Dec 28, 2021 | 299.28 Mn |
| Sep 28, 2021 | 289.14 Mn |
| Jun 29, 2021 | 283.61 Mn |
API Access
BJs RESTAURANTS 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=BJRI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "BJRI", "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=BJRI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();