Krispy Kreme (DNUT) Intangibles (2021 - 2026)
Krispy Kreme's Intangibles was $727.73 million in the quarter ended Jun 28, 2026, down 10.4% from $812.34 million a year earlier and down 0.7% from the prior quarter.
Krispy Kreme (DNUT) Intangibles (2021 - 2026) Analysis & Trends
As of Dec 28, 2025, Intangibles at Krispy Kreme came in at $797.75 million, down 2.7% from the prior year.
- Intangibles has now declined for three consecutive years, with a four-year compound annual growth rate of -5.4% (years ended Dec 2021 to Dec 2025).
- In earlier years, Intangibles was $819.93 million in the year ended Dec 29, 2024 (-13.4%), $946.35 million in the year ended Dec 31, 2023 (-2.0%), $966.09 million in the year ended Jan 1, 2023 and $998.01 million in the year ended Jan 3, 2021.
- The figure for the quarter ended Jun 28, 2026 marks the lowest quarterly Intangibles in data going back to the quarter ended Jan 1, 2023.
- Compared with a year earlier, Intangibles has declined for 11 straight quarters, with an average decline of 9.7% over the last eight quarters.
- Across the past five years, year-over-year decline in Intangibles ran from 2.0% in the quarter ended Dec 31, 2023 to 13.4% in the quarter ended Dec 29, 2024.
- Per Business Quant data, DNUT's Intangibles in the three quarters before the quarter ended Jun 28, 2026 was $733.1 million (quarter ended Mar 29, 2026), $797.75 million (quarter ended Dec 28, 2025) and $803.59 million (quarter ended Sep 28, 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Intangibles (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 174.16 Bn | 168.98 Bn | 6.42 Bn | - |
| 2 | Starbucks | 112.39 Bn | 100.02 Bn | - | 172.30 Mn |
| 3 | Yum Brands | 41.31 Bn | 38.20 Bn | 1.47 Bn | 807.00 Mn |
| 4 | Chipotle Mexican Grill | 36.17 Bn | 32.15 Bn | - | - |
| 5 | Restaurant Brands International | 26.03 Bn | 21.59 Bn | 1.38 Bn | 10.95 Bn |
| 6 | Darden Restaurants | 24.43 Bn | 23.53 Bn | 1.68 Bn | 1.35 Bn |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 12.57 Bn | 1.38 Bn | 10.95 Bn |
| 8 | Yum China Holdings | 15.44 Bn | 9.10 Bn | 537.00 Mn | 151.00 Mn |
| 9 | Texas Roadhouse | 10.99 Bn | 10.33 Bn | - | 26.49 Mn |
| 10 | Krispy Kreme | 499.61 Mn | 330.47 Mn | - | 727.73 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 28, 2026 | 727.73 Mn |
| Mar 29, 2026 | 733.10 Mn |
| Dec 28, 2025 | 797.75 Mn |
| Sep 28, 2025 | 803.59 Mn |
| Jun 29, 2025 | 812.34 Mn |
| Mar 30, 2025 | 813.87 Mn |
| Dec 29, 2024 | 819.93 Mn |
| Sep 29, 2024 | 831.74 Mn |
| Jun 30, 2024 | 927.71 Mn |
| Mar 31, 2024 | 938.85 Mn |
| Dec 31, 2023 | 946.35 Mn |
| Oct 1, 2023 | 949.46 Mn |
| Jul 2, 2023 | 960.09 Mn |
| Apr 2, 2023 | 963.55 Mn |
| Jan 1, 2023 | 966.09 Mn |
| Oct 2, 2022 | 966.36 Mn |
| Jul 3, 2022 | 969.32 Mn |
| Apr 3, 2022 | 985.54 Mn |
| Jan 2, 2022 | 992.52 Mn |
| Oct 3, 2021 | 993.44 Mn |
Krispy Kreme Intangibles 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=intangibles&ticker=DNUT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "intangibles", "ticker": "DNUT", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=intangibles&ticker=DNUT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();