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.
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Analysis
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 Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Cost of Rev (Qtr) |
|---|---|---|---|---|---|
| 1 | Tesla | 1,160.73 Bn | 982.96 Bn | 5.49 Bn | 22.55 Bn |
| 2 | General Motors | 75.19 Bn | -29.42 Bn | 9.28 Bn | 40.74 Bn |
| 3 | Ferrari | 74.17 Bn | 66.47 Bn | 1.14 Bn | 1.04 Bn |
| 4 | Ford Motor | 49.64 Bn | -84.78 Bn | 7.38 Bn | 42.15 Bn |
| 5 | Honda Motor | 47.63 Bn | -102.18 Bn | 8.46 Bn | 29.57 Bn |
| 6 | Toyota Motor | 28.28 Bn | -349.28 Bn | 19.83 Bn | 64.56 Bn |
| 7 | Rivian Automotive | 19.71 Bn | -2.02 Bn | 176.00 Mn | 1.98 Bn |
| 8 | Magna International | 17.43 Bn | 11.40 Bn | 1.63 Bn | 8.43 Bn |
| 9 | Stellantis | 12.80 Bn | -148.64 Bn | 3.94 Bn | 39.33 Bn |
| 10 | Xpeng | 9.74 Bn | 9.74 Bn | 599.70 Mn | 2.30 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 2.30 Bn |
| Mar 31, 2026 | 1.49 Bn |
| Dec 31, 2025 | 2.47 Bn |
| Sep 30, 2025 | 2.27 Bn |
| Jun 30, 2025 | 2.09 Bn |
| Mar 31, 2025 | 1.84 Bn |
| Dec 31, 2024 | 1.92 Bn |
| Sep 30, 2024 | 1.19 Bn |
| Jun 30, 2024 | 963.59 Mn |
| Mar 31, 2024 | 797.73 Mn |
| Dec 31, 2023 | 1.70 Bn |
| Sep 30, 2023 | 1.21 Bn |
| Jun 30, 2023 | 751.01 Mn |
| Mar 31, 2023 | 579.78 Mn |
| Dec 31, 2022 | 660.18 Mn |
| Sep 30, 2022 | 862.62 Mn |
| Jun 30, 2022 | 1.00 Bn |
| Mar 31, 2022 | 1.03 Bn |
| Dec 31, 2021 | 1.18 Bn |
| Sep 30, 2021 | 760.33 Mn |
API Access
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_KEYimport 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();