Sight Sciences (SGHT) Total Liabilities (2020 - 2026)
Sight Sciences' Total Liabilities was $51.98 million in Q2 2026, unchanged from $51.96 million a year earlier and down 6.8% from the prior quarter.
Sight Sciences (SGHT) Total Liabilities (2020 - 2026) Analysis & Trends
At the end of FY2025, Total Liabilities at Sight Sciences came in at $51.36 million, down 7.2% from FY2024.
- Total Liabilities shows a five-year compound annual growth rate of -20.5% (FY2020 to FY2025).
- In earlier years, Total Liabilities was $55.32 million in FY2024 (+19.1%), $46.44 million in FY2023 (-12.4%), $53 million in FY2022 (+10.2%) and $48.08 million in FY2021 (-70.3%).
- Quarterly Total Liabilities has moved between $46.35 million (Q1 2024) and $537.03 million (Q3 2021) over five years.
- Compared with a year earlier, Total Liabilities was higher in five of the last eight quarters, with growth averaging 5.6%.
- The best year-over-year quarter for Total Liabilities over five years was Q4 2024 (growth of 19.1%); the worst was Q3 2022 (a decline of 90.3%).
- Per Business Quant data, SGHT's Total Liabilities in the three quarters before Q2 2026 was $55.8 million (Q1 2026), $51.36 million (Q4 2025) and $51.97 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 251.30 Bn | 230.45 Bn | 4.88 Bn | 60.49 Bn |
| 2 | Abbott Laboratories | 174.70 Bn | 145.78 Bn | 7.27 Bn | 57.45 Bn |
| 3 | Danaher | 158.94 Bn | 142.76 Bn | 3.61 Bn | 39.78 Bn |
| 4 | Intuitive Surgical | 145.87 Bn | 125.42 Bn | 1.96 Bn | 2.58 Bn |
| 5 | Medtronic | 111.49 Bn | 77.36 Bn | 6.34 Bn | 42.46 Bn |
| 6 | Stryker | 106.96 Bn | 93.08 Bn | 4.50 Bn | 23.94 Bn |
| 7 | Boston Scientific | 63.62 Bn | 58.63 Bn | 3.85 Bn | 20.04 Bn |
| 8 | Edwards Lifesciences | 50.80 Bn | 34.92 Bn | 1.35 Bn | 3.14 Bn |
| 9 | Becton Dickinson | 49.59 Bn | 46.74 Bn | 2.32 Bn | 26.32 Bn |
| 10 | Sight Sciences | 511.60 Mn | 162.54 Mn | 21.37 Mn | 51.98 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 51.98 Mn |
| Mar 31, 2026 | 55.80 Mn |
| Dec 31, 2025 | 51.36 Mn |
| Sep 30, 2025 | 51.97 Mn |
| Jun 30, 2025 | 51.96 Mn |
| Mar 31, 2025 | 52.05 Mn |
| Dec 31, 2024 | 55.32 Mn |
| Sep 30, 2024 | 48.64 Mn |
| Jun 30, 2024 | 48.08 Mn |
| Mar 31, 2024 | 46.35 Mn |
| Dec 31, 2023 | 46.44 Mn |
| Sep 30, 2023 | 49.57 Mn |
| Jun 30, 2023 | 49.16 Mn |
| Mar 31, 2023 | 50.27 Mn |
| Dec 31, 2022 | 53.00 Mn |
| Sep 30, 2022 | 52.30 Mn |
| Jun 30, 2022 | 48.99 Mn |
| Mar 31, 2022 | 46.68 Mn |
| Dec 31, 2021 | 48.08 Mn |
| Sep 30, 2021 | 537.03 Mn |
Sight Sciences 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=SGHT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "SGHT", "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=SGHT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();