Aeva Technologies (AEVA) Operating Expenses (2020 - 2026)
Aeva Technologies (AEVA) reported Operating Expenses of $36.75 million for Q2 2026, up 14.1% from $32.2 million a year earlier but down 0.9% from the prior quarter.
Aeva Technologies (AEVA) Operating Expenses (2020 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Aeva Technologies' Operating Expenses came in at $137.83 million, up 3.2% year-over-year; for FY2025, it was $126.94 million, down 17.9% from FY2024.
- Operating Expenses has a five-year compound annual growth rate of 35.4% (FY2020 to FY2025).
- By year, Operating Expenses came in at $154.58 million in FY2024 (+8.9%), $141.9 million in FY2023 (-3.9%), $147.7 million in FY2022 (+37.2%) and $107.62 million in FY2021 (+286.5%).
- Five-year quarterly Operating Expenses spans a low of $28.57 million in Q3 2021 and a high of $48.07 million in Q2 2024.
- Year over year, Operating Expenses gained in three of the last eight quarters, with an average decline of 3.6%.
- The high point for year-over-year Operating Expenses in five years was Q1 2022 (growth of 67.0%); the low point was Q2 2025 (a decline of 33.0%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $37.08 million (Q1 2026), $30.42 million (Q4 2025) and $33.59 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Apple | 4,943.67 Bn | 4,691.16 Bn | 54.77 Bn | 19.08 Bn |
| 2 | Cisco Systems | 421.20 Bn | 357.13 Bn | 11.06 Bn | 6.80 Bn |
| 3 | Dell Technologies | 347.85 Bn | 303.60 Bn | 9.83 Bn | 4.45 Bn |
| 4 | Arista Networks | 258.42 Bn | 211.87 Bn | 1.91 Bn | 532.30 Mn |
| 5 | Sandisk | 250.08 Bn | 238.60 Bn | 7.58 Bn | 545.00 Mn |
| 6 | Seagate Technology Holdings | 208.99 Bn | 203.98 Bn | 1.90 Bn | 2.07 Bn |
| 7 | Western Digital | 163.62 Bn | 151.74 Bn | 2.03 Bn | 465.00 Mn |
| 8 | Sony | 143.48 Bn | 93.86 Bn | 6.53 Bn | 14.83 Bn |
| 9 | Hewlett Packard Enterprise | 83.23 Bn | 61.11 Bn | 4.93 Bn | 10.82 Bn |
| 10 | Aeva Technologies | 980.11 Mn | 531.93 Mn | 2.19 Mn | 36.75 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 36.75 Mn |
| Mar 31, 2026 | 37.08 Mn |
| Dec 31, 2025 | 30.42 Mn |
| Sep 30, 2025 | 33.59 Mn |
| Jun 30, 2025 | 32.20 Mn |
| Mar 31, 2025 | 30.73 Mn |
| Dec 31, 2024 | 33.41 Mn |
| Sep 30, 2024 | 37.16 Mn |
| Jun 30, 2024 | 48.07 Mn |
| Mar 31, 2024 | 35.95 Mn |
| Dec 31, 2023 | 35.97 Mn |
| Sep 30, 2023 | 33.78 Mn |
| Jun 30, 2023 | 36.26 Mn |
| Mar 31, 2023 | 35.89 Mn |
| Dec 31, 2022 | 41.27 Mn |
| Sep 30, 2022 | 36.41 Mn |
| Jun 30, 2022 | 36.19 Mn |
| Mar 31, 2022 | 33.84 Mn |
| Dec 31, 2021 | 32.88 Mn |
| Sep 30, 2021 | 28.57 Mn |
Aeva Technologies 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=AEVA&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "AEVA", "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=AEVA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();