Duolingo (DUOL) Total Liabilities (2020 - 2026)
Duolingo (DUOL) recorded Total Liabilities of $664.21 million in Q2 2026, up 17.4% from $565.53 million a year earlier but down 0.3% from the prior quarter.
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Analysis
Duolingo (DUOL) Total Liabilities (2020 - 2026) Analysis & Trends
At the end of FY2025, Duolingo reported Total Liabilities of $645.18 million, up 35.2% from FY2024.
- Annual Total Liabilities has increased for four straight years, with a five-year compound annual growth rate of 20.3% (FY2020 to FY2025).
- Across earlier years, Total Liabilities came in at $477.18 million in FY2024 (+59.9%), $298.46 million in FY2023 (+45.4%), $205.27 million in FY2022 (+38.5%) and $148.26 million in FY2021 (-42.2%).
- Quarterly Total Liabilities has ranged from $107.05 million in Q3 2021 to $666.23 million in Q1 2026 over the past five years.
- On a year-over-year basis, Total Liabilities has increased for 16 consecutive quarters, with growth averaging 42.3% over the last eight quarters.
- Peak year-over-year performance for Total Liabilities in the last five years was growth of 68.0% in Q3 2022, against a decline of 42.2% in Q4 2021 at the low end.
- Per Business Quant, the preceding three quarters came in at $666.23 million (Q1 2026), $645.18 million (Q4 2025) and $578.1 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Bryn | 945.00 Bn | 945.00 Bn | - | 206,169.00 |
| 2 | Veeva Systems | 45.35 Bn | 17.59 Bn | 695.95 Mn | 1.63 Bn |
| 3 | Samsara | 22.20 Bn | 18.97 Bn | 392.58 Mn | 1.17 Bn |
| 4 | Toast | 17.53 Bn | 10.20 Bn | 516.00 Mn | 1.14 Bn |
| 5 | Ptc | 15.47 Bn | 14.28 Bn | 490.47 Mn | 3.04 Bn |
| 6 | Trimble | 13.41 Bn | 12.48 Bn | 674.90 Mn | 3.43 Bn |
| 7 | Duolingo | 12.56 Bn | 7.73 Bn | 216.74 Mn | 664.21 Mn |
| 8 | Manhattan Associates | 11.77 Bn | 10.77 Bn | 168.33 Mn | 541.14 Mn |
| 9 | Costar | 10.95 Bn | 4.91 Bn | 728.00 Mn | 2.19 Bn |
| 10 | Bentley Systems | 9.44 Bn | 8.90 Bn | 336.74 Mn | 2.38 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 664.21 Mn |
| Mar 31, 2026 | 666.23 Mn |
| Dec 31, 2025 | 645.18 Mn |
| Sep 30, 2025 | 578.10 Mn |
| Jun 30, 2025 | 565.53 Mn |
| Mar 31, 2025 | 509.32 Mn |
| Dec 31, 2024 | 477.18 Mn |
| Sep 30, 2024 | 397.10 Mn |
| Jun 30, 2024 | 372.50 Mn |
| Mar 31, 2024 | 357.62 Mn |
| Dec 31, 2023 | 298.46 Mn |
| Sep 30, 2023 | 255.90 Mn |
| Jun 30, 2023 | 238.40 Mn |
| Mar 31, 2023 | 225.19 Mn |
| Dec 31, 2022 | 205.27 Mn |
| Sep 30, 2022 | 179.87 Mn |
| Jun 30, 2022 | 172.83 Mn |
| Mar 31, 2022 | 163.80 Mn |
| Dec 31, 2021 | 148.26 Mn |
| Sep 30, 2021 | 107.05 Mn |
API Access
Duolingo Total 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-liabilities&ticker=DUOL&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-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-liabilities&ticker=DUOL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();