Vyome Holdings (HIND) Operating Expenses (2015 - 2026)
Vyome Holdings' Operating Expenses was $874,224 in Q2 2026, up 150.9% from $348,424 a year earlier but down 23.8% from the prior quarter.
Vyome Holdings (HIND) Operating Expenses (2015 - 2026) Analysis & Trends
On a trailing twelve-month basis, Vyome Holdings' Operating Expenses was $11.99 million through Jun 30, 2026, up 795.7% year-over-year; for FY2025, it was $10.67 million, up 788.3% from FY2024.
- Operating Expenses shows a five-year compound annual growth rate of -10.6% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $1.2 million in FY2024 (-94.3%), $20.93 million in FY2023 (-60.6%), $53.15 million in FY2022 (-19.7%) and $66.23 million in FY2021 (+253.8%).
- Quarterly Operating Expenses has moved between $318,063 (Q3 2024) and $39.29 million (Q4 2021) over five years.
- Compared with a year earlier, Operating Expenses has increased for three straight quarters, with growth averaging 49.1% over the last seven quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q4 2021 (growth of 711.0%); the worst was Q3 2024 (a decline of 93.8%).
- Per Business Quant data, HIND's Operating Expenses in the three quarters before Q2 2026 was $1.15 million (Q1 2026), $1.38 million (Q4 2025) and $8.59 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Johnson & Johnson | 655.56 Bn | 574.09 Bn | 17.26 Bn | 10.12 Bn |
| 2 | AbbVie | 470.94 Bn | 444.10 Bn | 12.70 Bn | 10.56 Bn |
| 3 | Merck | 367.14 Bn | 321.57 Bn | 12.21 Bn | 12.80 Bn |
| 4 | Novartis Ag | 280.33 Bn | 236.20 Bn | 11.24 Bn | -6.09 Bn |
| 5 | Astrazeneca | 257.78 Bn | 231.34 Bn | 12.86 Bn | -9.70 Bn |
| 6 | Amgen | 226.04 Bn | 181.44 Bn | 7.24 Bn | 6.54 Bn |
| 7 | Gilead Sciences | 188.89 Bn | 163.01 Bn | 6.22 Bn | 18.20 Bn |
| 8 | Pfizer | 163.75 Bn | 110.70 Bn | 10.94 Bn | 6.68 Bn |
| 9 | Vertex Pharmaceuticals | 133.68 Bn | 105.69 Bn | 2.84 Bn | 2.09 Bn |
| 10 | Vyome Holdings | 14.25 Mn | -11.86 Mn | 11,658.00 | 874,224.00 |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 874,224.00 |
| Mar 31, 2026 | 1.15 Mn |
| Dec 31, 2025 | 1.38 Mn |
| Sep 30, 2025 | 8.59 Mn |
| Jun 30, 2025 | 348,424.00 |
| Mar 31, 2025 | 353,417.00 |
| Dec 31, 2024 | 318,767.00 |
| Sep 30, 2024 | 318,063.00 |
| Jun 30, 2024 | 3.19 Mn |
| Mar 31, 2024 | 3.38 Mn |
| Dec 31, 2023 | 3.74 Mn |
| Sep 30, 2023 | 5.17 Mn |
| Jun 30, 2023 | 5.17 Mn |
| Mar 31, 2023 | 6.86 Mn |
| Dec 31, 2022 | 18.29 Mn |
| Sep 30, 2022 | 14.40 Mn |
| Jun 30, 2022 | 11.13 Mn |
| Mar 31, 2022 | 9.33 Mn |
| Dec 31, 2021 | 39.29 Mn |
| Sep 30, 2021 | 16.55 Mn |
Vyome Holdings Operating 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=operating-expenses&ticker=HIND&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "HIND", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=HIND&period=max&api_key=YOUR_API_KEY");
const data = await res.json();