Duolingo (DUOL) Change in Accured Expenses (2020 - 2026)
Duolingo's Change in Accured Expenses was $1.2 million in Q2 2026, compared with -$4.15 million a year earlier and down 80.0% from the prior quarter.
Duolingo (DUOL) Change in Accured Expenses (2020 - 2026) Analysis & Trends
On a trailing twelve-month basis, Duolingo's Change in Accured Expenses was $17.76 million through Jun 30, 2026, up 66.0% year-over-year; for FY2025, it came in at $255,000, down 98.5% from FY2024.
- Change in Accured Expenses shows a five-year compound annual growth rate of -47.2% (FY2020 to FY2025).
- In earlier years, Change in Accured Expenses was $16.85 million in FY2024 (+389.3%), $3.44 million in FY2023 (-60.5%), $8.72 million in FY2022 (+135.2%) and $3.71 million in FY2021 (-40.3%).
- Quarterly Change in Accured Expenses has moved between -$6.2 million (Q1 2025) and $15.5 million (Q4 2024) over five years.
- Compared with a year earlier, Change in Accured Expenses was higher in two of the last four quarters, with growth averaging 164.6%.
- The best year-over-year quarter for Change in Accured Expenses over five years was Q4 2024 (growth of 375.6%); the worst was Q2 2024 (a decline of 85.5%).
- Per Business Quant data, DUOL's Change in Accured Expenses in the three quarters before Q2 2026 was $5.96 million (Q1 2026), $5.45 million (Q4 2025) and $5.16 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Bryn | 945.00 Bn | 945.00 Bn | - | 50,912.00 |
| 2 | Veeva Systems | 44.24 Bn | 16.49 Bn | 695.95 Mn | -10.50 Mn |
| 3 | Samsara | 24.06 Bn | 20.83 Bn | 392.58 Mn | 34.27 Mn |
| 4 | Toast | 17.18 Bn | 9.85 Bn | 516.00 Mn | 57.00 Mn |
| 5 | Ptc | 15.95 Bn | 14.76 Bn | 490.47 Mn | 133.18 Mn |
| 6 | Duolingo | 13.49 Bn | 8.67 Bn | 216.74 Mn | 1.20 Mn |
| 7 | Trimble | 13.41 Bn | 12.48 Bn | 674.90 Mn | 42.10 Mn |
| 8 | Manhattan Associates | 11.90 Bn | 10.90 Bn | 168.33 Mn | 20.69 Mn |
| 9 | Costar | 11.09 Bn | 5.06 Bn | 728.00 Mn | 33.00 Mn |
| 10 | Bentley Systems | 9.73 Bn | 9.19 Bn | 336.74 Mn | 21.64 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.20 Mn |
| Mar 31, 2026 | 5.96 Mn |
| Dec 31, 2025 | 5.45 Mn |
| Sep 30, 2025 | 5.16 Mn |
| Jun 30, 2025 | -4.15 Mn |
| Mar 31, 2025 | -6.20 Mn |
| Dec 31, 2024 | 15.50 Mn |
| Sep 30, 2024 | 5.55 Mn |
| Jun 30, 2024 | 315,000.00 |
| Mar 31, 2024 | -4.51 Mn |
| Dec 31, 2023 | 3.26 Mn |
| Sep 30, 2023 | 1.22 Mn |
| Jun 30, 2023 | 2.17 Mn |
| Mar 31, 2023 | -3.20 Mn |
| Dec 31, 2022 | 4.45 Mn |
| Sep 30, 2022 | 764,000.00 |
| Jun 30, 2022 | 2.24 Mn |
| Mar 31, 2022 | 1.27 Mn |
| Dec 31, 2021 | 3.30 Mn |
| Sep 30, 2021 | 700,000.00 |
Duolingo Change in Accured Expenses 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=change-in-accured-expenses&ticker=DUOL&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "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=change-in-accured-expenses&ticker=DUOL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();