Palantir Technologies (PLTR) Operating Expenses (2019 - 2026)
Palantir Technologies (PLTR) reported Operating Expenses of $726.59 million for Q2 2026, up 34.2% from $541.45 million a year earlier and up 9.6% from the prior quarter.
Palantir Technologies (PLTR) Operating Expenses (2019 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Palantir Technologies' Operating Expenses came in at $2.59 billion, up 18.4% year-over-year; for FY2025, it came in at $2.27 billion, up 14.2% from FY2024.
- Operating Expenses has increased for four consecutive years, with a five-year compound annual growth rate of 3.5% (FY2020 to FY2025).
- By year, Operating Expenses came in at $1.99 billion in FY2024 (+18.8%), $1.67 billion in FY2023 (+0.9%), $1.66 billion in FY2022 (+2.8%) and $1.61 billion in FY2021 (-15.7%).
- The Q2 2026 figure ranks as the highest quarterly Operating Expenses since Q3 2020.
- Year over year, Operating Expenses gained in seven of the last eight quarters, with growth averaging 23.0%.
- The high point for year-over-year Operating Expenses in five years was Q4 2024 (growth of 47.9%); the low point was Q3 2021 (a decline of 59.8%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $662.79 million (Q1 2026), $615.44 million (Q4 2025) and $580.53 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 480.73 Bn | 449.68 Bn | 1.64 Bn | 726.59 Mn |
| 2 | Oracle | 399.91 Bn | 272.04 Bn | - | 12.62 Bn |
| 3 | Sap Se | 262.30 Bn | 190.08 Bn | 8.40 Bn | -8.41 Bn |
| 4 | Salesforce | 202.26 Bn | 158.13 Bn | 8.70 Bn | 6.37 Bn |
| 5 | ServiceNow | 153.84 Bn | 132.30 Bn | 2.82 Bn | 2.66 Bn |
| 6 | Automatic Data Processing | 114.84 Bn | 96.97 Bn | 2.51 Bn | 4.34 Bn |
| 7 | Intuit | 91.04 Bn | 70.38 Bn | 3.44 Bn | 3.88 Bn |
| 8 | Relx | 70.51 Bn | 69.60 Bn | - | - |
| 9 | Strategy | 53.24 Bn | 46.23 Bn | 81.55 Mn | 8.41 Bn |
| 10 | Thomson Reuters | 48.40 Bn | 45.18 Bn | - | -1.21 Bn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 726.59 Mn |
| Mar 31, 2026 | 662.79 Mn |
| Dec 31, 2025 | 615.44 Mn |
| Sep 30, 2025 | 580.53 Mn |
| Jun 30, 2025 | 541.45 Mn |
| Mar 31, 2025 | 534.84 Mn |
| Dec 31, 2024 | 641.94 Mn |
| Sep 30, 2024 | 465.74 Mn |
| Jun 30, 2024 | 444.23 Mn |
| Mar 31, 2024 | 437.20 Mn |
| Dec 31, 2023 | 433.92 Mn |
| Sep 30, 2023 | 410.25 Mn |
| Jun 30, 2023 | 416.34 Mn |
| Mar 31, 2023 | 413.43 Mn |
| Dec 31, 2022 | 422.14 Mn |
| Sep 30, 2022 | 432.46 Mn |
| Jun 30, 2022 | 412.53 Mn |
| Mar 31, 2022 | 391.39 Mn |
| Dec 31, 2021 | 404.25 Mn |
| Sep 30, 2021 | 397.28 Mn |
Palantir 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=PLTR&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "PLTR", "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=PLTR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();