Restaurant Brands International Limited Partnership (RSTRF) Inventory (2013 - 2026)
Restaurant Brands International Limited Partnership (RSTRF) reported Inventory of $224 million for Q2 2026, up 34.1% from $167 million a year earlier and up 10.3% from the prior quarter.
Restaurant Brands International Limited Partnership (RSTRF) Inventory (2013 - 2026) Analysis & Trends
At the end of FY2025, Restaurant Brands International Limited Partnership posted Inventory of $205 million, up 44.4% from FY2024.
- Inventory has a five-year compound annual growth rate of 16.4% (FY2020 to FY2025).
- By year, Inventory came in at $142 million in FY2024 (-14.5%), $166 million in FY2023 (+24.8%), $133 million in FY2022 (+38.5%) and $96 million in FY2021 (unchanged).
- The Q2 2026 figure ranks as the highest quarterly Inventory in data going back to Q4 2013.
- Year over year, Inventory has now increased in each of the last six quarters, with growth averaging 16.8% over the last eight quarters.
- The high point for year-over-year Inventory in five years was Q2 2023 (growth of 50.0%); the low point was Q4 2024 (a decline of 14.5%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $203 million (Q1 2026), $205 million (Q4 2025) and $216 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Inventory (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 171.96 Bn | 166.78 Bn | 6.42 Bn | 58.00 Mn |
| 2 | Starbucks | 110.34 Bn | 97.96 Bn | - | 2.21 Bn |
| 3 | Yum Brands | 41.48 Bn | 38.36 Bn | 1.47 Bn | - |
| 4 | Chipotle Mexican Grill | 39.00 Bn | 34.98 Bn | - | 46.62 Mn |
| 5 | Restaurant Brands International | 25.80 Bn | 21.35 Bn | 1.38 Bn | 224.00 Mn |
| 6 | Darden Restaurants | 24.38 Bn | 23.48 Bn | 1.68 Bn | 321.00 Mn |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 12.57 Bn | 1.38 Bn | 224.00 Mn |
| 8 | Yum China Holdings | 15.57 Bn | 9.23 Bn | 537.00 Mn | 459.00 Mn |
| 9 | Texas Roadhouse | 11.21 Bn | 10.55 Bn | - | 49.69 Mn |
| 10 | Luckin Coffee | 10.73 Bn | 9.81 Bn | - | 424.02 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 224.00 Mn |
| Mar 31, 2026 | 203.00 Mn |
| Dec 31, 2025 | 205.00 Mn |
| Sep 30, 2025 | 216.00 Mn |
| Jun 30, 2025 | 167.00 Mn |
| Mar 31, 2025 | 159.00 Mn |
| Dec 31, 2024 | 142.00 Mn |
| Sep 30, 2024 | 169.00 Mn |
| Jun 30, 2024 | 160.00 Mn |
| Mar 31, 2024 | 152.00 Mn |
| Dec 31, 2023 | 166.00 Mn |
| Sep 30, 2023 | 160.00 Mn |
| Jun 30, 2023 | 171.00 Mn |
| Mar 31, 2023 | 145.00 Mn |
| Dec 31, 2022 | 133.00 Mn |
| Sep 30, 2022 | 129.00 Mn |
| Jun 30, 2022 | 114.00 Mn |
| Mar 31, 2022 | 108.00 Mn |
| Dec 31, 2021 | 96.00 Mn |
| Sep 30, 2021 | 96.00 Mn |
Restaurant Brands International Limited Partnership Inventory 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=inventory&ticker=RSTRF&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "inventory", "ticker": "RSTRF", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=inventory&ticker=RSTRF&period=max&api_key=YOUR_API_KEY");
const data = await res.json();