Nerdy (NRDY) Total Non-Current Liabilities (2020 - 2026)
Nerdy (NRDY) reported Total Non-Current Liabilities of $36.76 million for Q2 2026, up 64.0% from $22.41 million a year earlier but down 12.6% from the prior quarter.
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Analysis
Nerdy (NRDY) Total Non-Current Liabilities (2020 - 2026) Analysis & Trends
At the end of FY2025, Nerdy posted Total Non-Current Liabilities of $44.95 million, up 58.7% from FY2024.
- Total Non-Current Liabilities has a five-year compound annual growth rate of -37.0% (FY2020 to FY2025).
- By year, Total Non-Current Liabilities came in at $28.33 million in FY2024 (-20.4%), $35.61 million in FY2023 (-4.6%), $37.33 million in FY2022 (-10.9%) and $41.91 million in FY2021 (-90.8%).
- Five-year quarterly Total Non-Current Liabilities spans a low of $22.41 million in Q2 2025 and a high of $91.81 million in Q3 2021.
- Year over year, Total Non-Current Liabilities has now increased in each of the last three quarters, with growth averaging 12.8% over the last eight quarters.
- The high point for year-over-year Total Non-Current Liabilities in five years was Q2 2026 (growth of 64.0%); the low point was Q4 2021 (a decline of 90.8%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $42.06 million (Q1 2026), $44.95 million (Q4 2025) and $31.02 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Non-Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Bryn | 945.00 Bn | 945.00 Bn | - | - |
| 2 | Veeva Systems | 46.20 Bn | 18.45 Bn | 695.95 Mn | 1.60 Bn |
| 3 | Samsara | 22.32 Bn | 19.09 Bn | 392.58 Mn | 1.15 Bn |
| 4 | Toast | 16.73 Bn | 9.40 Bn | 516.00 Mn | 1.10 Bn |
| 5 | Ptc | 15.53 Bn | 14.35 Bn | 490.47 Mn | 2.94 Bn |
| 6 | Duolingo | 13.32 Bn | 8.49 Bn | 216.74 Mn | - |
| 7 | Trimble | 13.32 Bn | 12.38 Bn | 674.90 Mn | 3.15 Bn |
| 8 | Manhattan Associates | 11.58 Bn | 10.58 Bn | 168.33 Mn | 528.94 Mn |
| 9 | Costar | 11.10 Bn | 5.07 Bn | 728.00 Mn | 2.16 Bn |
| 10 | Nerdy | 103.21 Mn | -51.85 Mn | 27.98 Mn | 36.76 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 36.76 Mn |
| Mar 31, 2026 | 42.06 Mn |
| Dec 31, 2025 | 44.95 Mn |
| Sep 30, 2025 | 31.02 Mn |
| Jun 30, 2025 | 22.41 Mn |
| Mar 31, 2025 | 27.38 Mn |
| Dec 31, 2024 | 28.33 Mn |
| Sep 30, 2024 | 35.84 Mn |
| Jun 30, 2024 | 25.70 Mn |
| Mar 31, 2024 | 33.04 Mn |
| Dec 31, 2023 | 35.61 Mn |
| Sep 30, 2023 | 39.82 Mn |
| Jun 30, 2023 | 27.75 Mn |
| Mar 31, 2023 | 35.56 Mn |
| Dec 31, 2022 | 37.33 Mn |
| Sep 30, 2022 | 36.46 Mn |
| Jun 30, 2022 | 35.01 Mn |
| Mar 31, 2022 | 46.83 Mn |
| Dec 31, 2021 | 41.91 Mn |
| Sep 30, 2021 | 91.81 Mn |
API Access
Nerdy Total Non-Current Liabilities 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=total-non-current-liabilities&ticker=NRDY&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-non-current-liabilities", "ticker": "NRDY", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=total-non-current-liabilities&ticker=NRDY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();