Dine Brands Global (DIN) Revenue (2010 - 2026)
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Analysis
Dine Brands Global (DIN) Revenue (2010 - 2026) Analysis & Trends
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Revenue (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 195.98 Bn | 190.80 Bn | 6.42 Bn | 7.10 Bn |
| 2 | Starbucks | 120.13 Bn | 107.76 Bn | - | 9.32 Bn |
| 3 | Yum Brands | 44.36 Bn | 41.25 Bn | 1.47 Bn | 2.17 Bn |
| 4 | Chipotle Mexican Grill | 43.92 Bn | 40.41 Bn | - | 3.29 Bn |
| 5 | Restaurant Brands International | 27.10 Bn | 22.88 Bn | 1.40 Bn | 2.53 Bn |
| 6 | Darden Restaurants | 25.62 Bn | 24.72 Bn | 1.68 Bn | 3.20 Bn |
| 7 | Restaurant Brands International Limited Partnership | 24.67 Bn | 20.46 Bn | 1.40 Bn | 2.53 Bn |
| 8 | Yum China Holdings | 17.38 Bn | 11.04 Bn | 537.00 Mn | 3.14 Bn |
| 9 | Texas Roadhouse | 12.08 Bn | 11.42 Bn | - | 1.68 Bn |
| 10 | Dine Brands Global | 428.34 Mn | 7.34 Mn | 84.70 Mn | 248.90 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 27, 2026 | 248.90 Mn |
| 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 |
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();