Restaurant Brands International (QSR) EV to EBITDA (2014 - 2026)
Restaurant Brands International's (QSR) quarterly EV to EBITDA came in at 36.04 in Q2 2026, down 22.55% year-over-year from 46.53 in Q2 2025, and down 16.66% quarter-over-quarter from 43.24 in Q1 2026.
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Restaurant Brands International (QSR) EV to EBITDA (2014 - 2026) Analysis & Trends
Restaurant Brands International (QSR) has reported EV to EBITDA for 13 consecutive years, with 36.04 the latest figure, recorded in Q2 2026.
- On a quarterly basis, EV to EBITDA fell 22.55% year-over-year to 36.04 in Q2 2026; TTM through Jun 2026 was 9.9, a 6.16% decrease from a year earlier, with the FY2025 full-year figure at 10.9, up 22.33% from the prior year.
- EV to EBITDA was 36.04 for Q2 2026 at Restaurant Brands International, down from 43.24 in the prior quarter.
- Over five years, EV to EBITDA peaked at 59.12 in Q4 2022 and troughed at 29.93 in Q2 2022.
- A 5-year average of 41.8 and a median of 41.66 in 2022 frame the typical range for EV to EBITDA.
- Across the five-year window, EV to EBITDA surged 49.66% in 2023 and slumped 36.83% in 2024, its largest moves.
- Over 5 years, EV to EBITDA stood at 59.12 in 2022, then decreased by 9.14% to 53.71 in 2023, then tumbled by 36.83% to 33.93 in 2024, then grew by 13.87% to 38.63 in 2025, then dropped by 6.72% to 36.04 in 2026.
- The last three EV to EBITDA figures came in at 36.04 (Q2 2026), 43.24 (Q1 2026), and 38.63 (Q4 2025), per Business Quant data.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Mcdonalds | 168.67 Bn | 167.85 Bn | 6.42 Bn |
| 2 | Starbucks | 107.32 Bn | 103.72 Bn | 6.49 Bn |
| 3 | Chipotle Mexican Grill | 41.40 Bn | 40.73 Bn | 2.35 Bn |
| 4 | Yum Brands | 38.39 Bn | 37.72 Bn | 1.47 Bn |
| 5 | Restaurant Brands International | 25.02 Bn | 25.51 Bn | 1.89 Bn |
| 6 | Darden Restaurants | 24.39 Bn | 24.17 Bn | 3.68 Bn |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 15.95 Bn | 1.89 Bn |
| 8 | Yum China Holdings | 14.09 Bn | 13.41 Bn | 2.22 Bn |
| 9 | Texas Roadhouse | 10.81 Bn | 10.63 Bn | 1.44 Bn |
| 10 | Dominos Pizza | 9.81 Bn | 9.60 Bn | 478.23 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 36.04 |
| Mar 31, 2026 | 43.24 |
| Dec 31, 2025 | 38.63 |
| Sep 30, 2025 | 32.58 |
| Jun 30, 2025 | 46.53 |
| Mar 31, 2025 | 52.05 |
| Dec 31, 2024 | 33.93 |
| Sep 30, 2024 | 41.55 |
| Jun 30, 2024 | 35.05 |
| Mar 31, 2024 | 47.71 |
| Dec 31, 2023 | 53.71 |
| Sep 30, 2023 | 37.15 |
| Jun 30, 2023 | 44.79 |
| Mar 31, 2023 | 48.31 |
| Dec 31, 2022 | 59.12 |
| Sep 30, 2022 | 30.38 |
| Jun 30, 2022 | 29.93 |
| Mar 31, 2022 | 41.78 |
| Dec 31, 2021 | 46.35 |
| Sep 30, 2021 | 35.83 |
API Access
Restaurant Brands International EV to EBITDA 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=ev-to-ebitda&ticker=QSR&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ev-to-ebitda", "ticker": "QSR", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=ev-to-ebitda&ticker=QSR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();