Vertex (VERX) Operating Expenses (2019 - 2026)
Vertex (VERX) reported Operating Expenses of $135.74 million for Q2 2026, up 8.5% from $125.06 million a year earlier and up 0.2% from the prior quarter.
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Analysis
Vertex (VERX) Operating Expenses (2019 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Vertex's Operating Expenses came in at $516.92 million, up 10.1% year-over-year; for FY2025, it was $479.27 million, up 11.9% from FY2024.
- Operating Expenses has increased for four consecutive years, with a five-year compound annual growth rate of 8.8% (FY2020 to FY2025).
- By year, Operating Expenses came in at $428.35 million in FY2024 (+17.0%), $366.09 million in FY2023 (+19.4%), $306.57 million in FY2022 (+15.0%) and $266.6 million in FY2021 (-15.1%).
- The Q2 2026 figure ranks as the highest quarterly Operating Expenses in data going back to Q2 2019.
- Year over year, Operating Expenses gained in seven of the last eight quarters, with growth averaging 17.3%.
- The high point for year-over-year Operating Expenses in five years was Q4 2024 (growth of 35.5%); the low point was Q3 2021 (a decline of 27.2%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $135.48 million (Q1 2026), $128.7 million (Q4 2025) and $117 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 450.50 Bn | 419.56 Bn | 1.64 Bn | 726.59 Mn |
| 2 | Oracle | 401.01 Bn | 273.57 Bn | - | 12.62 Bn |
| 3 | Sap Se | 257.03 Bn | 178.11 Bn | 8.40 Bn | -8.41 Bn |
| 4 | Salesforce | 187.04 Bn | 142.92 Bn | 8.70 Bn | 6.37 Bn |
| 5 | ServiceNow | 135.91 Bn | 114.37 Bn | 2.82 Bn | 2.66 Bn |
| 6 | Automatic Data Processing | 104.14 Bn | 86.27 Bn | 2.51 Bn | 4.34 Bn |
| 7 | Intuit | 72.30 Bn | 51.65 Bn | 3.44 Bn | 3.88 Bn |
| 8 | Relx | 60.17 Bn | 57.14 Bn | - | - |
| 9 | Strategy | 55.31 Bn | 48.30 Bn | 81.55 Mn | 8.41 Bn |
| 10 | Vertex | 1.78 Bn | 644.01 Mn | 131.30 Mn | 135.74 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 135.74 Mn |
| Mar 31, 2026 | 135.48 Mn |
| Dec 31, 2025 | 128.70 Mn |
| Sep 30, 2025 | 117.00 Mn |
| Jun 30, 2025 | 125.06 Mn |
| Mar 31, 2025 | 108.51 Mn |
| Dec 31, 2024 | 130.23 Mn |
| Sep 30, 2024 | 105.63 Mn |
| Jun 30, 2024 | 95.14 Mn |
| Mar 31, 2024 | 97.36 Mn |
| Dec 31, 2023 | 96.09 Mn |
| Sep 30, 2023 | 90.17 Mn |
| Jun 30, 2023 | 89.89 Mn |
| Mar 31, 2023 | 89.93 Mn |
| Dec 31, 2022 | 85.03 Mn |
| Sep 30, 2022 | 76.45 Mn |
| Jun 30, 2022 | 75.44 Mn |
| Mar 31, 2022 | 69.65 Mn |
| Dec 31, 2021 | 68.03 Mn |
| Sep 30, 2021 | 70.39 Mn |
API Access
Vertex 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=VERX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "VERX", "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=VERX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();