Xpeng (XPEV) Cost of Revenue (2019 - 2026)
Xpeng's Cost of Revenue came in at $2.31 billion for Q2 2026, up 9.4% from $2.11 billion a year earlier and up 53.8% from the prior quarter.
Xpeng (XPEV) Cost of Revenue (2019 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Xpeng reported Cost of Revenue of $8.6 billion, up 21.9% year-over-year; for FY2025, it was $8.9 billion, up 85.5% from FY2024.
- Cost of Revenue has increased in each of the last six years, with a five-year compound annual growth rate of 60.0% (FY2020 to FY2025).
- Going back by year, Cost of Revenue was $4.8 billion in FY2024 (+12.7%), $4.26 billion in FY2023 (+23.5%), $3.45 billion in FY2022 (+19.6%) and $2.88 billion in FY2021 (+239.0%).
- The five-year range for quarterly Cost of Revenue is $577.55 million (Q1 2023) to $2.5 billion (Q4 2025).
- Year-over-year, Cost of Revenue increased in seven of the last eight quarters, with growth averaging 46.8%.
- The fastest year-over-year change in Cost of Revenue over five years came in Q4 2021 (growth of 192.1%), and the weakest in Q1 2023 (a decline of 44.1%).
- Business Quant data shows XPEV's Cost of Revenue at $1.5 billion (Q1 2026), $2.5 billion (Q4 2025) and $2.29 billion (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Cost of Rev (Qtr) |
|---|---|---|---|---|---|
| 1 | Tesla | 1,223.67 Bn | 1,049.69 Bn | 4.75 Bn | 23.49 Bn |
| 2 | Toyota Motor | 243.73 Bn | -163.01 Bn | 20.95 Bn | 63.91 Bn |
| 3 | Honda Motor | 126.52 Bn | -7.78 Bn | 8.46 Bn | 29.57 Bn |
| 4 | General Motors | 72.50 Bn | -34.01 Bn | 7.33 Bn | 40.70 Bn |
| 5 | Ferrari | 68.83 Bn | 61.27 Bn | 1.18 Bn | 1.07 Bn |
| 6 | Ford Motor | 48.36 Bn | -94.13 Bn | 6.08 Bn | 42.22 Bn |
| 7 | Rivian Automotive | 18.97 Bn | -4.34 Bn | 179.00 Mn | 1.48 Bn |
| 8 | Magna International | 18.29 Bn | 15.51 Bn | 1.61 Bn | 9.37 Bn |
| 9 | Stellantis | 13.35 Bn | -153.18 Bn | 5.55 Bn | 44.99 Bn |
| 10 | Xpeng | 9.11 Bn | -1.64 Bn | 601.83 Mn | 2.31 Bn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 2.31 Bn |
| Mar 31, 2026 | 1.50 Bn |
| Dec 31, 2025 | 2.50 Bn |
| Sep 30, 2025 | 2.29 Bn |
| Jun 30, 2025 | 2.11 Bn |
| Mar 31, 2025 | 1.84 Bn |
| Dec 31, 2024 | 1.89 Bn |
| Sep 30, 2024 | 1.22 Bn |
| Jun 30, 2024 | 959.88 Mn |
| Mar 31, 2024 | 790.04 Mn |
| Dec 31, 2023 | 1.72 Bn |
| Sep 30, 2023 | 1.20 Bn |
| Jun 30, 2023 | 725.40 Mn |
| Mar 31, 2023 | 577.55 Mn |
| Dec 31, 2022 | 680.75 Mn |
| Sep 30, 2022 | 829.44 Mn |
| Jun 30, 2022 | 989.38 Mn |
| Mar 31, 2022 | 1.03 Bn |
| Dec 31, 2021 | 1.18 Bn |
| Sep 30, 2021 | 760.33 Mn |
Xpeng Cost of Revenue 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=cost-of-revenue&ticker=XPEV&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "cost-of-revenue", "ticker": "XPEV", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=cost-of-revenue&ticker=XPEV&period=max&api_key=YOUR_API_KEY");
const data = await res.json();