Serve Robotics (SERV) Operating Expenses (2021 - 2026)
Serve Robotics' Operating Expenses was $57.29 million in Q2 2026, up 189.5% from $19.79 million a year earlier and up 33.9% from the prior quarter.
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Analysis
Serve Robotics (SERV) Operating Expenses (2021 - 2026) Analysis & Trends
On a trailing twelve-month basis, Serve Robotics' Operating Expenses was $164.13 million through Jun 30, 2026, up 201.0% year-over-year; for FY2025, it came in at $97.39 million, up 154.8% from FY2024.
- Operating Expenses shows a five-year compound annual growth rate of 457.6% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $38.21 million in FY2024 (+99.0%), $19.2 million in FY2023 (-3.6%), $19.91 million in FY2022 and $54,627 in FY2021 (+202.4%).
- The Q2 2026 figure marks the highest quarterly Operating Expenses in data going back to Q1 2021.
- Compared with a year earlier, Operating Expenses has increased for 12 straight quarters, with growth averaging 148.4% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q3 2025 (growth of 267.2%); the worst was Q1 2022 (a decline of 51.4%).
- Per Business Quant data, SERV's Operating Expenses in the three quarters before Q2 2026 was $42.78 million (Q1 2026), $33.63 million (Q4 2025) and $30.44 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Aurora Innovation | 11.07 Bn | 6.10 Bn | -5.00 Mn | 261.00 Mn |
| 2 | Mobileye Global | 6.05 Bn | -61.98 Mn | 235.00 Mn | 265.00 Mn |
| 3 | Pony AI | 2.84 Bn | 2.91 Bn | 6.35 Mn | -72.09 Mn |
| 4 | WeRide | 1.82 Bn | -1.20 Bn | 12.76 Mn | -73.92 Mn |
| 5 | Securetech Innovations | 781.01 Mn | 780.42 Mn | - | - |
| 6 | Serve Robotics | 402.21 Mn | 402.21 Mn | -8.78 Mn | 57.29 Mn |
| 7 | Kodiak AI | 372.81 Mn | -135.31 Mn | - | 47.18 Mn |
| 8 | Richtech Robotics | 354.53 Mn | 354.53 Mn | 802,000.00 | 14.07 Mn |
| 9 | ECARX Holdings | 326.03 Mn | -35.79 Mn | 44.50 Mn | -50.70 Mn |
| 10 | Palladyne AI | 253.58 Mn | 61.95 Mn | 1.68 Mn | 19.20 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 57.29 Mn |
| Mar 31, 2026 | 42.78 Mn |
| Dec 31, 2025 | 33.63 Mn |
| Sep 30, 2025 | 30.44 Mn |
| Jun 30, 2025 | 19.79 Mn |
| Mar 31, 2025 | 13.54 Mn |
| Dec 31, 2024 | 12.92 Mn |
| Sep 30, 2024 | 8.29 Mn |
| Jun 30, 2024 | 8.70 Mn |
| Mar 31, 2024 | 8.31 Mn |
| Dec 31, 2023 | 6.46 Mn |
| Sep 30, 2023 | 5.07 Mn |
| Jun 30, 2023 | 3.77 Mn |
| Mar 31, 2023 | 3.90 Mn |
| Dec 31, 2022 | 6.02 Mn |
| Sep 30, 2022 | 5.02 Mn |
| Jun 30, 2022 | 19,190.00 |
| Mar 31, 2022 | 7,888.00 |
| Dec 31, 2021 | 9,406.00 |
| Sep 30, 2021 | 14,720.00 |
API Access
Serve 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=SERV&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "SERV", "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=SERV&period=max&api_key=YOUR_API_KEY");
const data = await res.json();