Materialise (MTLS) Operating Expenses (2013 - 2026)
Materialise's Operating Expenses came in at -$26.21 million for the quarter ended Jun 30, 2026, compared with -$23.62 million a year earlier.
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Analysis
Materialise (MTLS) Operating Expenses (2013 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Materialise reported Operating Expenses of -$102.33 million; for the year ended Dec 31, 2025, it came in at -$97.4 million.
- Going back by year, Operating Expenses was -$90.52 million in the year ended Dec 31, 2024, -$81.31 million in the year ended Dec 31, 2023, -$21.91 million in the year ended Dec 31, 2022 and -$67.38 million in the year ended Dec 31, 2021.
- The five-year range for quarterly Operating Expenses is -$26.46 million (the quarter ended Dec 31, 2025) to -$16.77 million (the quarter ended Sep 30, 2021).
- Business Quant data shows MTLS's Operating Expenses at -$24.91 million (quarter ended Mar 31, 2026), -$26.46 million (quarter ended Dec 31, 2025) and -$24.75 million (quarter ended Sep 30, 2025) in the three quarters before the quarter ended Jun 30, 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Palantir Technologies | 466.13 Bn | 435.08 Bn | 1.64 Bn | 726.59 Mn |
| 2 | Oracle | 383.82 Bn | 255.95 Bn | - | 12.62 Bn |
| 3 | Sap Se | 263.61 Bn | 191.39 Bn | 8.40 Bn | -8.41 Bn |
| 4 | Salesforce | 198.89 Bn | 154.76 Bn | 8.70 Bn | 6.37 Bn |
| 5 | ServiceNow | 149.64 Bn | 128.10 Bn | 2.82 Bn | 2.66 Bn |
| 6 | Automatic Data Processing | 115.45 Bn | 97.58 Bn | 2.51 Bn | 4.34 Bn |
| 7 | Intuit | 89.90 Bn | 69.25 Bn | 3.44 Bn | 3.88 Bn |
| 8 | Relx | 71.97 Bn | 71.07 Bn | - | - |
| 9 | Thomson Reuters | 48.55 Bn | 45.33 Bn | - | -1.21 Bn |
| 10 | Materialise | 478.74 Mn | -138.58 Mn | 46.23 Mn | -26.21 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | -26.21 Mn |
| Mar 31, 2026 | -24.91 Mn |
| Dec 31, 2025 | -26.46 Mn |
| Sep 30, 2025 | -24.75 Mn |
| Jun 30, 2025 | -23.62 Mn |
| Mar 31, 2025 | -22.55 Mn |
| Dec 31, 2024 | -24.04 Mn |
| Sep 30, 2024 | -22.99 Mn |
| Jun 30, 2024 | -22.61 Mn |
| Mar 31, 2024 | -21.23 Mn |
| Dec 31, 2023 | -21.49 Mn |
| Sep 30, 2023 | -19.72 Mn |
| Jun 30, 2023 | -20.71 Mn |
| Mar 31, 2023 | -19.40 Mn |
| Dec 31, 2022 | -20.96 Mn |
| Sep 30, 2022 | -18.44 Mn |
| Jun 30, 2022 | -19.91 Mn |
| Mar 31, 2022 | -18.25 Mn |
| Dec 31, 2021 | -18.37 Mn |
| Sep 30, 2021 | -17.08 Mn |
API Access
Materialise 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=MTLS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "MTLS", "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=MTLS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();