Duolingo (DUOL) Total Current Liabilities (2020 - 2026)
Duolingo's Total Current Liabilities came in at $577.83 million for Q2 2026, up 22.6% from $471.38 million a year earlier and up 0.6% from the prior quarter.
Duolingo (DUOL) Total Current Liabilities (2020 - 2026) Analysis & Trends
At the end of FY2025, Duolingo's Total Current Liabilities was $551.15 million, up 30.5% from FY2024.
- Total Current Liabilities has increased in each of the last five years, with a five-year compound annual growth rate of 53.0% (FY2020 to FY2025).
- Going back by year, Total Current Liabilities was $422.23 million in FY2024 (+52.2%), $277.36 million in FY2023 (+52.6%), $181.77 million in FY2022 (+52.6%) and $119.13 million in FY2021 (+81.4%).
- The Q2 2026 figure represents the highest quarterly Total Current Liabilities in data going back to Q4 2020.
- Year-over-year, Total Current Liabilities has increased for 17 consecutive quarters, with growth averaging 39.6% over the last eight quarters.
- Across the past five years, year-over-year growth in Total Current Liabilities ran from 22.6% in Q2 2026 to 81.4% in Q4 2021.
- Business Quant data shows DUOL's Total Current Liabilities at $574.11 million (Q1 2026), $551.15 million (Q4 2025) and $484.54 million (Q3 2025) in the three quarters before Q2 2026.
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 | Bentley Systems | 9.44 Bn | 8.90 Bn | 336.74 Mn | 988.14 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 577.83 Mn |
| Mar 31, 2026 | 574.11 Mn |
| Dec 31, 2025 | 551.15 Mn |
| Sep 30, 2025 | 484.54 Mn |
| Jun 30, 2025 | 471.38 Mn |
| Mar 31, 2025 | 454.49 Mn |
| Dec 31, 2024 | 422.23 Mn |
| Sep 30, 2024 | 342.13 Mn |
| Jun 30, 2024 | 317.72 Mn |
| Mar 31, 2024 | 303.72 Mn |
| Dec 31, 2023 | 277.36 Mn |
| Sep 30, 2023 | 234.93 Mn |
| Jun 30, 2023 | 217.11 Mn |
| Mar 31, 2023 | 202.81 Mn |
| Dec 31, 2022 | 181.77 Mn |
| Sep 30, 2022 | 155.63 Mn |
| Jun 30, 2022 | 147.33 Mn |
| Mar 31, 2022 | 135.78 Mn |
| Dec 31, 2021 | 119.13 Mn |
| Sep 30, 2021 | 98.65 Mn |
Duolingo 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=DUOL&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-current-liabilities", "ticker": "DUOL", "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=DUOL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();