Noodles (NDLS) Revenue (2012 - 2026)
Noodles (NDLS) recorded Revenue of $127.04 million in Q2 2026, up 0.5% from $126.43 million a year earlier and up 2.6% from the prior quarter.
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Analysis
Noodles (NDLS) Revenue (2012 - 2026) Analysis & Trends
On a TTM basis, Noodles' Revenue came in at $495.69 million as of Jun 30, 2026, up 0.2% year-over-year; for FY2025, it came in at $495.09 million, up 0.4% from FY2024.
- Annual Revenue has a five-year compound annual growth rate of 4.7% (FY2020 to FY2025).
- Across earlier years, Revenue came in at $493.27 million in FY2024 (-2.0%), $503.41 million in FY2023 and $475.15 million in FY2021 (+20.7%).
- The Q2 2026 figure is the highest quarterly Revenue since Q2 2024.
- On a year-over-year basis, Revenue rose in three of the last seven quarters, with an average decline of 0.7%.
- Peak year-over-year performance for Revenue in the last five years was growth of 18.1% in Q3 2021, against a decline of 6.6% in Q4 2024 at the low end.
- Per Business Quant, the preceding three quarters came in at $123.79 million (Q1 2026), $122.78 million (Q4 2025) and $122.09 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Revenue (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 163.51 Bn | 158.34 Bn | 6.42 Bn | 7.10 Bn |
| 2 | Starbucks | 107.11 Bn | 94.75 Bn | - | 9.32 Bn |
| 3 | Chipotle Mexican Grill | 40.42 Bn | 36.40 Bn | - | 3.35 Bn |
| 4 | Yum Brands | 37.23 Bn | 34.12 Bn | 1.47 Bn | 2.17 Bn |
| 5 | Restaurant Brands International | 24.82 Bn | 21.92 Bn | 1.38 Bn | 2.52 Bn |
| 6 | Darden Restaurants | 22.06 Bn | 21.17 Bn | -113.70 Mn | 3.72 Bn |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 12.57 Bn | 1.38 Bn | 2.52 Bn |
| 8 | Yum China Holdings | 14.18 Bn | 8.54 Bn | 537.00 Mn | 3.14 Bn |
| 9 | Texas Roadhouse | 10.25 Bn | 9.62 Bn | - | 1.68 Bn |
| 10 | Noodles | 79.06 Mn | 70.36 Mn | 90.30 Mn | 127.04 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 127.04 Mn |
| Mar 31, 2026 | 123.79 Mn |
| Dec 30, 2025 | 122.78 Mn |
| Sep 30, 2025 | 122.09 Mn |
| Jul 1, 2025 | 126.43 Mn |
| Apr 1, 2025 | 123.79 Mn |
| Dec 31, 2024 | 121.77 Mn |
| Oct 1, 2024 | 122.75 Mn |
| Jul 2, 2024 | 127.35 Mn |
| Apr 2, 2024 | 121.40 Mn |
| Jan 2, 2024 | 130.40 Mn |
| Oct 3, 2023 | 127.85 Mn |
| Jul 4, 2023 | 125.15 Mn |
| Apr 4, 2023 | 126.08 Mn |
| Sep 27, 2022 | 129.38 Mn |
| Jun 28, 2022 | 131.07 Mn |
| Mar 29, 2022 | 112.56 Mn |
| Dec 28, 2021 | 114.80 Mn |
| Sep 28, 2021 | 125.13 Mn |
| Jun 29, 2021 | 125.65 Mn |
API Access
Noodles 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=NDLS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "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=revenue&ticker=NDLS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();