Ceribell (CBLL) Accumulated Expenses (2023 - 2026)
Ceribell's Accumulated Expenses was $14.06 million in Q3 2026, up 28.9% from $10.91 million a year earlier and up 12.6% from the prior quarter.
Ceribell (CBLL) Accumulated Expenses (2023 - 2026) Analysis & Trends
At the end of FY2025, Accumulated Expenses at Ceribell came in at $14.33 million, up 42.5% from FY2024.
- In earlier years, Accumulated Expenses was $10.05 million in FY2024 (+33.3%) and $7.54 million in FY2023.
- Quarterly Accumulated Expenses has moved between $7.54 million (Q4 2023) and $14.33 million (Q4 2025) over five years.
- Compared with a year earlier, Accumulated Expenses has increased for five straight quarters, with growth averaging 33.8% over the last six quarters.
- Per Business Quant data, CBLL's Accumulated Expenses in the three quarters before Q3 2026 was $12.48 million (Q2 2026), $12.56 million (Q1 2026) and $14.33 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Thermo Fisher Scientific | 266.22 Bn | 242.86 Bn | 5.13 Bn |
| 2 | Abbott Laboratories | 191.31 Bn | 165.77 Bn | 7.39 Bn |
| 3 | Danaher | 166.16 Bn | 145.82 Bn | 3.84 Bn |
| 4 | Intuitive Surgical | 155.98 Bn | 136.40 Bn | 2.08 Bn |
| 5 | Medtronic | 130.05 Bn | 96.18 Bn | 6.34 Bn |
| 6 | Stryker | 123.40 Bn | 109.59 Bn | 4.25 Bn |
| 7 | Boston Scientific | 64.81 Bn | 60.48 Bn | 3.43 Bn |
| 8 | Edwards Lifesciences | 59.87 Bn | 43.18 Bn | 1.35 Bn |
| 9 | Medline | 53.84 Bn | 50.96 Bn | 1.93 Bn |
| 10 | Ceribell | 1.07 Bn | 519.62 Mn | 26.34 Mn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 14.06 Mn |
| Jun 30, 2026 | 12.48 Mn |
| Mar 31, 2026 | 12.56 Mn |
| Dec 31, 2025 | 14.33 Mn |
| Sep 30, 2025 | 10.91 Mn |
| Jun 30, 2025 | 10.43 Mn |
| Mar 31, 2025 | 8.30 Mn |
| Dec 31, 2024 | 10.05 Mn |
| Sep 30, 2024 | 8.57 Mn |
| Dec 31, 2023 | 7.54 Mn |
Ceribell 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=CBLL&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "CBLL", "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=CBLL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();