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.
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Analysis
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 Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 413.65 Bn | 378.59 Bn | 1.93 Bn | 845.28 Mn |
| 2 | Oracle | 374.28 Bn | 246.84 Bn | - | 12.62 Bn |
| 3 | Sap Se | 294.90 Bn | 222.88 Bn | 8.64 Bn | 8.45 Bn |
| 4 | Salesforce | 186.99 Bn | 142.87 Bn | 8.70 Bn | 6.37 Bn |
| 5 | Automatic Data Processing | 120.08 Bn | 106.87 Bn | 2.53 Bn | 4.18 Bn |
| 6 | ServiceNow | 113.02 Bn | 92.28 Bn | 2.90 Bn | 2.51 Bn |
| 7 | Intuit | 95.72 Bn | 75.07 Bn | 3.44 Bn | 3.88 Bn |
| 8 | Relx | 74.73 Bn | 73.84 Bn | - | - |
| 9 | Strategy | 57.35 Bn | 44.49 Bn | 89.63 Mn | -20.82 Bn |
| 10 | Thomson Reuters | 52.16 Bn | 48.13 Bn | - | 1.18 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 845.28 Mn |
| 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 |
API Access
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_KEYimport 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();