iHuman (IH) Accumulated Expenses (2019 - 2026)
iHuman's Accumulated Expenses was $12.08 million in the quarter ended Mar 31, 2026, up 9.3% from $11.05 million a year earlier but down 26.0% from the prior quarter.
iHuman (IH) Accumulated Expenses (2019 - 2026) Analysis & Trends
As of Dec 31, 2025, Accumulated Expenses at iHuman came in at $16.55 million, down 4.5% from the prior year.
- Accumulated Expenses has now declined for three consecutive years, though with a five-year compound annual growth rate of 0.2% (years ended Dec 2020 to Dec 2025).
- In earlier years, Accumulated Expenses was $17.33 million in the year ended Dec 31, 2024 (-14.4%), $20.24 million in the year ended Dec 31, 2023 (-3.6%), $20.98 million in the year ended Dec 31, 2022 (+15.4%) and $18.19 million in the year ended Dec 31, 2021 (+10.9%).
- Quarterly Accumulated Expenses has moved between $11.05 million (the quarter ended Mar 31, 2025) and $15.31 billion (the quarter ended Sep 30, 2025) over five years.
- Compared with a year earlier, Accumulated Expenses was higher in two of the last seven quarters, with an average decline of 7.2%.
- The best year-over-year quarter for Accumulated Expenses over five years was the quarter ended Sep 30, 2021 (growth of 27.2%); the worst was the quarter ended Sep 30, 2022 (a decline of 18.5%).
- Per Business Quant data, IH's Accumulated Expenses in the three quarters before the quarter ended Mar 31, 2026 was $16.32 million (quarter ended Dec 31, 2025), $15.31 billion (quarter ended Sep 30, 2025) and $12.6 million (quarter ended Jun 30, 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Bryn | 945.00 Bn | 945.00 Bn | - |
| 2 | Veeva Systems | 46.20 Bn | 18.45 Bn | 695.95 Mn |
| 3 | Samsara | 22.32 Bn | 19.09 Bn | 392.58 Mn |
| 4 | Toast | 16.73 Bn | 9.40 Bn | 516.00 Mn |
| 5 | Ptc | 15.53 Bn | 14.35 Bn | 490.47 Mn |
| 6 | Duolingo | 13.32 Bn | 8.49 Bn | 216.74 Mn |
| 7 | Trimble | 13.32 Bn | 12.38 Bn | 674.90 Mn |
| 8 | Manhattan Associates | 11.58 Bn | 10.58 Bn | 168.33 Mn |
| 9 | Costar | 11.10 Bn | 5.07 Bn | 728.00 Mn |
| 10 | iHuman | 113.46 Mn | -157.98 Bn | 16.39 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 11.12 Mn |
| Mar 31, 2026 | 12.08 Mn |
| Dec 31, 2025 | 16.32 Mn |
| Sep 30, 2025 | 15.31 Bn |
| Jun 30, 2025 | 12.60 Mn |
| Mar 31, 2025 | 11.05 Mn |
| Dec 31, 2024 | 17.61 Mn |
| Sep 30, 2024 | 16.58 Mn |
| Jun 30, 2024 | 12.56 Mn |
| Mar 31, 2024 | 13.03 Mn |
| Dec 31, 2023 | 19.95 Mn |
| Sep 30, 2023 | 18.05 Mn |
| Jun 30, 2023 | 15.23 Mn |
| Mar 31, 2023 | 13.83 Mn |
| Dec 31, 2022 | 20.35 Mn |
| Sep 30, 2022 | 15.19 Mn |
| Jun 30, 2022 | 12.99 Mn |
| Mar 31, 2022 | 13.76 Mn |
| Dec 31, 2021 | 18.13 Mn |
| Sep 30, 2021 | 18.64 Mn |
iHuman Accumulated 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=accumulated-expenses&ticker=IH&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "IH", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=accumulated-expenses&ticker=IH&period=max&api_key=YOUR_API_KEY");
const data = await res.json();