Arbe Robotics (ARBE) Operating Expenses (2020 - 2026)
Arbe Robotics (ARBE) posted Operating Expenses of $9.83 million for Q2 2026, down 13.0% from $11.3 million a year earlier and down 12.4% from the prior quarter.
Arbe Robotics (ARBE) Operating Expenses (2020 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Arbe Robotics was $43.82 million, down 10.9% year-over-year; for FY2025, it came in at $47.4 million, down 3.0% from FY2024.
- Annual Operating Expenses shows a five-year compound annual growth rate of 26.0% (FY2020 to FY2025).
- In prior years, Arbe Robotics' Operating Expenses was $48.87 million in FY2024 (+4.3%), $46.85 million in FY2023 (-6.2%), $49.97 million in FY2022 (+46.6%) and $34.09 million in FY2021 (+128.0%).
- The Q2 2026 figure stands as the lowest quarterly Operating Expenses since Q3 2021.
- On a year-over-year basis, Operating Expenses has declined in each of the last five quarters, with an average decline of 3.9% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q4 2021, with growth of 264.3%; the weakest was Q4 2023, with a decline of 15.2%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $11.22 million (Q1 2026), $11.51 million (Q4 2025) and $11.27 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Nvidia | 5,515.53 Bn | 5,289.69 Bn | 72.14 Bn | 8.41 Bn |
| 2 | Taiwan Semiconductor Manufacturing | 2,348.76 Bn | 1,974.46 Bn | 27.22 Bn | 3.13 Bn |
| 3 | Broadcom | 1,668.85 Bn | 1,594.89 Bn | 20.46 Bn | 4.50 Bn |
| 4 | Micron Technology | 1,189.94 Bn | 1,128.71 Bn | 35.06 Bn | 1.72 Bn |
| 5 | Advanced Micro Devices | 992.04 Bn | 948.79 Bn | 6.20 Bn | 4.21 Bn |
| 6 | Asml Holding | 682.73 Bn | 638.57 Bn | 5.90 Bn | - |
| 7 | Intel | 585.14 Bn | 469.87 Bn | 6.51 Bn | 4.71 Bn |
| 8 | Lam Research | 393.49 Bn | 370.29 Bn | 3.48 Bn | 965.25 Mn |
| 9 | Applied Materials | 386.29 Bn | 351.73 Bn | 4.59 Bn | 1.51 Bn |
| 10 | Arbe Robotics | 73.59 Mn | -118.67 Mn | -6,000.00 | 9.83 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 9.83 Mn |
| Mar 31, 2026 | 11.22 Mn |
| Dec 31, 2025 | 11.51 Mn |
| Sep 30, 2025 | 11.27 Mn |
| Jun 30, 2025 | 11.30 Mn |
| Mar 31, 2025 | 13.06 Mn |
| Dec 31, 2024 | 12.63 Mn |
| Sep 30, 2024 | 12.18 Mn |
| Jun 30, 2024 | 11.58 Mn |
| Mar 31, 2024 | 12.49 Mn |
| Dec 31, 2023 | 11.91 Mn |
| Sep 30, 2023 | 11.68 Mn |
| Jun 30, 2023 | 12.58 Mn |
| Mar 31, 2023 | 10.68 Mn |
| Dec 31, 2022 | 14.05 Mn |
| Sep 30, 2022 | 11.80 Mn |
| Jun 30, 2022 | 12.98 Mn |
| Mar 31, 2022 | 11.13 Mn |
| Dec 31, 2021 | 14.17 Mn |
| Sep 30, 2021 | 8.50 Mn |
Arbe Robotics 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=ARBE&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "ARBE", "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=ARBE&period=max&api_key=YOUR_API_KEY");
const data = await res.json();