Hyperfine (HYPR) Total Current Liabilities (2020 - 2026)
Hyperfine (HYPR) recorded Total Current Liabilities of $9.63 million in Q2 2026, up 20.5% from $7.99 million a year earlier but down 5.2% from the prior quarter.
Hyperfine (HYPR) Total Current Liabilities (2020 - 2026) Analysis & Trends
At the end of FY2025, Hyperfine reported Total Current Liabilities of $11.73 million, up 34.4% from FY2024.
- Annual Total Current Liabilities has a five-year compound annual growth rate of 23.3% (FY2020 to FY2025).
- Across earlier years, Total Current Liabilities came in at $8.73 million in FY2024 (-0.4%), $8.77 million in FY2023 (-0.4%), $8.8 million in FY2022 (-44.1%) and $15.74 million in FY2021 (+282.3%).
- Quarterly Total Current Liabilities has ranged from $1.95 million in Q3 2021 to $15.74 million in Q4 2021 over the past five years.
- On a year-over-year basis, Total Current Liabilities has increased for four consecutive quarters, with growth averaging 10.9% over the last eight quarters.
- Peak year-over-year performance for Total Current Liabilities in the last five years was growth of 670.1% in Q2 2022, against a decline of 44.1% in Q4 2022 at the low end.
- Per Business Quant, the preceding three quarters came in at $10.15 million (Q1 2026), $11.73 million (Q4 2025) and $10.17 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 257.69 Bn | 236.72 Bn | 4.88 Bn | 15.07 Bn |
| 2 | Abbott Laboratories | 172.10 Bn | 142.53 Bn | 7.27 Bn | 17.81 Bn |
| 3 | Danaher | 163.45 Bn | 147.25 Bn | 3.61 Bn | 8.11 Bn |
| 4 | Intuitive Surgical | 151.11 Bn | 130.54 Bn | 1.96 Bn | 1.92 Bn |
| 5 | Medtronic | 118.91 Bn | 84.16 Bn | 6.34 Bn | 11.80 Bn |
| 6 | Stryker | 113.41 Bn | 99.53 Bn | 4.50 Bn | 6.68 Bn |
| 7 | Boston Scientific | 64.96 Bn | 59.73 Bn | 3.85 Bn | 6.43 Bn |
| 8 | Becton Dickinson | 53.32 Bn | 50.47 Bn | 2.32 Bn | 9.40 Bn |
| 9 | Edwards Lifesciences | 50.67 Bn | 34.67 Bn | 1.35 Bn | 1.51 Bn |
| 10 | Hyperfine | 73.34 Mn | -67.54 Mn | 1.98 Mn | 9.63 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 9.63 Mn |
| Mar 31, 2026 | 10.15 Mn |
| Dec 31, 2025 | 11.73 Mn |
| Sep 30, 2025 | 10.17 Mn |
| Jun 30, 2025 | 7.99 Mn |
| Mar 31, 2025 | 7.98 Mn |
| Dec 31, 2024 | 8.73 Mn |
| Sep 30, 2024 | 9.96 Mn |
| Jun 30, 2024 | 8.79 Mn |
| Mar 31, 2024 | 8.77 Mn |
| Dec 31, 2023 | 8.77 Mn |
| Sep 30, 2023 | 8.21 Mn |
| Jun 30, 2023 | 8.04 Mn |
| Mar 31, 2023 | 8.00 Mn |
| Dec 31, 2022 | 8.80 Mn |
| Sep 30, 2022 | 12.46 Mn |
| Jun 30, 2022 | 10.46 Mn |
| Mar 31, 2022 | 11.41 Mn |
| Dec 31, 2021 | 15.74 Mn |
| Sep 30, 2021 | 1.95 Mn |
Hyperfine 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=HYPR&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-current-liabilities", "ticker": "HYPR", "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=HYPR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();