Noodles (NDLS) Cost of Revenue (2018 - 2026)
Noodles (NDLS) recorded Cost of Revenue of $36.74 million in Q2 2026, down 6.5% from $39.28 million a year earlier but up 0.9% from the prior quarter.
Powered by 
Analysis
Noodles (NDLS) Cost of Revenue (2018 - 2026) Analysis & Trends
On a TTM basis, Noodles' Cost of Revenue came in at $319.6 million as of Jun 30, 2026, down 1.8% year-over-year; for FY2025, it was $325.13 million, up 0.3% from FY2024.
- Annual Cost of Revenue has a five-year compound annual growth rate of 3.7% (FY2020 to FY2025).
- Across earlier years, Cost of Revenue came in at $324.32 million in FY2024 (-1.0%), $327.64 million in FY2023 and $309.47 million in FY2021 (+14.2%).
- Quarterly Cost of Revenue has ranged from $36.41 million in Q1 2026 to $208.96 million in Q4 2025 over the past five years.
- On a year-over-year basis, Cost of Revenue rose in four of the last seven quarters, with growth averaging 21.6%.
- Peak year-over-year performance for Cost of Revenue in the last five years was growth of 164.1% in Q4 2024, against a decline of 7.6% in Q1 2026 at the low end.
- Per Business Quant, the preceding three quarters came in at $36.41 million (Q1 2026), $208.96 million (Q4 2025) and $37.5 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Cost of Rev (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 164.13 Bn | 158.95 Bn | 6.42 Bn | 680.00 Mn |
| 2 | Starbucks | 107.97 Bn | 95.60 Bn | - | - |
| 3 | Chipotle Mexican Grill | 41.04 Bn | 37.02 Bn | - | - |
| 4 | Yum Brands | 37.16 Bn | 34.04 Bn | 1.47 Bn | 700.00 Mn |
| 5 | Restaurant Brands International | 24.42 Bn | 21.52 Bn | 1.38 Bn | 1.14 Bn |
| 6 | Darden Restaurants | 22.67 Bn | 21.77 Bn | 1.68 Bn | 1.52 Bn |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 12.57 Bn | 1.38 Bn | 1.14 Bn |
| 8 | Yum China Holdings | 13.79 Bn | 8.16 Bn | 537.00 Mn | 2.60 Bn |
| 9 | Texas Roadhouse | 10.24 Bn | 9.60 Bn | - | - |
| 10 | Noodles | 79.95 Mn | 71.25 Mn | 90.30 Mn | 36.74 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 36.74 Mn |
| Mar 31, 2026 | 36.41 Mn |
| Dec 30, 2025 | 208.96 Mn |
| Sep 30, 2025 | 37.50 Mn |
| Jul 1, 2025 | 39.28 Mn |
| Apr 1, 2025 | 39.40 Mn |
| Dec 31, 2024 | 208.53 Mn |
| Oct 1, 2024 | 38.42 Mn |
| Jul 2, 2024 | 38.95 Mn |
| Apr 2, 2024 | 38.42 Mn |
| Jan 2, 2024 | 78.94 Mn |
| Oct 3, 2023 | 82.10 Mn |
| Jul 4, 2023 | 81.72 Mn |
| Apr 4, 2023 | 82.34 Mn |
| Sep 27, 2022 | 85.71 Mn |
| Jun 28, 2022 | 85.57 Mn |
| Mar 29, 2022 | 77.41 Mn |
| Dec 28, 2021 | 78.02 Mn |
| Sep 28, 2021 | 79.27 Mn |
| Jun 29, 2021 | 79.25 Mn |
API Access
Noodles Cost of 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=cost-of-revenue&ticker=NDLS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "cost-of-revenue", "ticker": "NDLS", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=cost-of-revenue&ticker=NDLS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();