Nerdy (NRDY) Total Current Liabilities (2019 - 2026)
Nerdy's Total Current Liabilities was $17.18 million in Q2 2026, down 23.4% from $22.41 million a year earlier and down 24.0% from the prior quarter.
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Analysis
Nerdy (NRDY) Total Current Liabilities (2019 - 2026) Analysis & Trends
At the end of FY2025, Total Current Liabilities at Nerdy came in at $25.63 million, down 9.5% from FY2024.
- Total Current Liabilities has now declined for four consecutive years, with a five-year compound annual growth rate of -5.7% (FY2020 to FY2025).
- In earlier years, Total Current Liabilities was $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 (+22.0%).
- The Q2 2026 figure marks the lowest quarterly Total Current Liabilities since Q4 2019.
- Compared with a year earlier, Total Current Liabilities has declined for 11 straight quarters, with an average decline of 15.5% over the last eight quarters.
- The best year-over-year quarter for Total Current Liabilities over five years was Q1 2022 (growth of 42.4%); the worst was Q3 2022 (a decline of 60.3%).
- Per Business Quant data, NRDY's Total Current Liabilities in the three quarters before Q2 2026 was $22.61 million (Q1 2026), $25.63 million (Q4 2025) and $31.02 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Bryn | 945.00 Bn | 945.00 Bn | - | 206,170.00 |
| 2 | Veeva Systems | 45.35 Bn | 17.59 Bn | 695.95 Mn | 1.46 Bn |
| 3 | Samsara | 22.20 Bn | 18.97 Bn | 392.58 Mn | 968.09 Mn |
| 4 | Toast | 17.53 Bn | 10.20 Bn | 516.00 Mn | 1.10 Bn |
| 5 | Ptc | 15.47 Bn | 14.28 Bn | 490.47 Mn | 1.34 Bn |
| 6 | Trimble | 13.41 Bn | 12.48 Bn | 674.90 Mn | 1.41 Bn |
| 7 | Duolingo | 12.56 Bn | 7.73 Bn | 216.74 Mn | 577.83 Mn |
| 8 | Manhattan Associates | 11.77 Bn | 10.77 Bn | 168.33 Mn | 475.05 Mn |
| 9 | Costar | 10.95 Bn | 4.91 Bn | 728.00 Mn | 747.00 Mn |
| 10 | Nerdy | 107.68 Mn | -47.38 Mn | 27.98 Mn | 17.18 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 17.18 Mn |
| Mar 31, 2026 | 22.61 Mn |
| Dec 31, 2025 | 25.63 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 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-current-liabilities&ticker=NRDY&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-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-current-liabilities&ticker=NRDY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();