Dine Brands Global (DIN) Revenue (2010 - 2026)
Dine Brands Global's Revenue came in at $240.9 million for Q2 2026, up 4.4% from $230.8 million a year earlier and up 7.0% from the prior quarter.
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Analysis
Dine Brands Global (DIN) Revenue (2010 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 28, 2026, Dine Brands Global reported Revenue of $899.84 million, up 6.4% year-over-year; for FY2025, it was $879.3 million, up 8.2% from FY2024.
- Revenue carries a five-year compound annual growth rate of 5.0% (FY2020 to FY2025).
- Going back by year, Revenue was $812.3 million in FY2024 (-2.3%), $831.1 million in FY2023 (-8.6%), $909.4 million in FY2022 (+1.5%) and $896.2 million in FY2021 (+30.0%).
- The Q2 2026 figure represents the highest quarterly Revenue since Q1 2012.
- Year-over-year, Revenue has increased for six consecutive quarters, with growth averaging 4.7% over the last eight quarters.
- The fastest year-over-year change in Revenue over five years came in Q3 2021 (growth of 29.5%), and the weakest in Q3 2023 (a decline of 13.1%).
- Business Quant data shows DIN's Revenue at $225.2 million (Q1 2026), $217.57 million (Q4 2025) and $216.17 million (Q3 2025) in the three quarters before Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Revenue (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 163.51 Bn | 158.34 Bn | 6.42 Bn | 7.10 Bn |
| 2 | Starbucks | 107.11 Bn | 94.75 Bn | - | 9.32 Bn |
| 3 | Chipotle Mexican Grill | 40.42 Bn | 36.40 Bn | - | 3.35 Bn |
| 4 | Yum Brands | 37.23 Bn | 34.12 Bn | 1.47 Bn | 2.17 Bn |
| 5 | Restaurant Brands International | 24.82 Bn | 21.92 Bn | 1.38 Bn | 2.52 Bn |
| 6 | Darden Restaurants | 22.06 Bn | 21.17 Bn | -113.70 Mn | 3.72 Bn |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 12.57 Bn | 1.38 Bn | 2.52 Bn |
| 8 | Yum China Holdings | 14.18 Bn | 8.54 Bn | 537.00 Mn | 3.14 Bn |
| 9 | Texas Roadhouse | 10.25 Bn | 9.62 Bn | - | 1.68 Bn |
| 10 | Dine Brands Global | 352.51 Mn | -145.39 Mn | 91.20 Mn | 240.90 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 28, 2026 | 240.90 Mn |
| Mar 29, 2026 | 225.20 Mn |
| Dec 28, 2025 | 217.57 Mn |
| Sep 30, 2025 | 216.17 Mn |
| Jun 29, 2025 | 230.80 Mn |
| Mar 30, 2025 | 214.80 Mn |
| Dec 29, 2024 | 204.76 Mn |
| Sep 30, 2024 | 195.03 Mn |
| Jun 30, 2024 | 206.27 Mn |
| Mar 31, 2024 | 206.24 Mn |
| Dec 31, 2023 | 206.30 Mn |
| Sep 30, 2023 | 202.60 Mn |
| Jun 30, 2023 | 208.42 Mn |
| Mar 31, 2023 | 213.80 Mn |
| Dec 31, 2022 | 207.97 Mn |
| Sep 30, 2022 | 233.22 Mn |
| Jun 30, 2022 | 237.80 Mn |
| Mar 31, 2022 | 230.42 Mn |
| Dec 31, 2021 | 229.66 Mn |
| Sep 30, 2021 | 228.72 Mn |
API Access
Dine Brands Global 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=revenue&ticker=DIN&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "revenue", "ticker": "DIN", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=revenue&ticker=DIN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();