Noodles (NDLS) Cash & Equivalents (2012 - 2026)
Noodles' Cash & Equivalents was $1.3 million in Q2 2026, down 42.6% from $2.26 million a year earlier and down 10.0% from the prior quarter.
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Analysis
Noodles (NDLS) Cash & Equivalents (2012 - 2026) Analysis & Trends
At the end of FY2025, Cash & Equivalents at Noodles came in at $1.27 million, up 10.1% from FY2024.
- Cash & Equivalents shows a five-year compound annual growth rate of -30.6% (FY2020 to FY2025).
- In earlier years, Cash & Equivalents was $1.15 million in FY2024 (-61.9%), $3.01 million in FY2023 and $2.26 million in FY2021 (-71.2%).
- Quarterly Cash & Equivalents has moved between $1.15 million (Q4 2024) and $4.69 million (Q3 2025) over five years.
- Compared with a year earlier, Cash & Equivalents was higher in five of the last seven quarters, with an average decline of 2.7%.
- The best year-over-year quarter for Cash & Equivalents over five years was Q3 2025 (growth of 41.9%); the worst was Q4 2021 (a decline of 71.2%).
- Per Business Quant data, NDLS's Cash & Equivalents in the three quarters before Q2 2026 was $1.44 million (Q1 2026), $1.27 million (Q4 2025) and $4.69 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Cash & Equiv. (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 163.51 Bn | 158.34 Bn | 6.42 Bn | 822.00 Mn |
| 2 | Starbucks | 107.11 Bn | 94.75 Bn | - | 3.45 Bn |
| 3 | Chipotle Mexican Grill | 40.42 Bn | 36.40 Bn | - | 228.20 Mn |
| 4 | Yum Brands | 37.23 Bn | 34.12 Bn | 1.47 Bn | 674.00 Mn |
| 5 | Restaurant Brands International | 24.82 Bn | 21.92 Bn | 1.38 Bn | 1.06 Bn |
| 6 | Darden Restaurants | 22.06 Bn | 21.17 Bn | -113.70 Mn | 219.50 Mn |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 12.57 Bn | 1.38 Bn | 1.06 Bn |
| 8 | Yum China Holdings | 14.18 Bn | 8.54 Bn | 537.00 Mn | 485.00 Mn |
| 9 | Texas Roadhouse | 10.25 Bn | 9.62 Bn | - | 202.43 Mn |
| 10 | Noodles | 79.06 Mn | 70.36 Mn | 90.30 Mn | 1.30 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.30 Mn |
| Mar 31, 2026 | 1.44 Mn |
| Dec 30, 2025 | 1.27 Mn |
| Sep 30, 2025 | 4.69 Mn |
| Jul 1, 2025 | 2.26 Mn |
| Apr 1, 2025 | 1.40 Mn |
| Dec 31, 2024 | 1.15 Mn |
| Oct 1, 2024 | 3.31 Mn |
| Jul 2, 2024 | 1.81 Mn |
| Apr 2, 2024 | 1.33 Mn |
| Jan 2, 2024 | 3.01 Mn |
| Oct 3, 2023 | 2.53 Mn |
| Jul 4, 2023 | 3.14 Mn |
| Apr 4, 2023 | 2.06 Mn |
| Jan 3, 2023 | 1.52 Mn |
| Sep 27, 2022 | 1.84 Mn |
| Jun 28, 2022 | 1.80 Mn |
| Mar 29, 2022 | 1.60 Mn |
| Dec 28, 2021 | 2.26 Mn |
| Sep 28, 2021 | 3.15 Mn |
API Access
Noodles Cash & Equivalents 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=cash-and-equivalents&ticker=NDLS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "cash-and-equivalents", "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=cash-and-equivalents&ticker=NDLS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();