Xometry (XMTR) Operating Expenses (2020 - 2026)
Xometry (XMTR) posted Operating Expenses of $92.7 million for Q2 2026, up 22.8% from $75.47 million a year earlier and up 10.7% from the prior quarter.
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Analysis
Xometry (XMTR) Operating Expenses (2020 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Xometry was $343.51 million, up 20.5% year-over-year; for FY2025, it came in at $314.29 million, up 15.6% from FY2024.
- Annual Operating Expenses has increased for six consecutive years, with a five-year compound annual growth rate of 38.1% (FY2020 to FY2025).
- In prior years, Xometry's Operating Expenses was $271.77 million in FY2024 (+7.9%), $251.84 million in FY2023 (+12.9%), $223.08 million in FY2022 (+92.6%) and $115.83 million in FY2021 (+85.3%).
- The Q2 2026 figure stands as the highest quarterly Operating Expenses in data going back to Q2 2020.
- On a year-over-year basis, Operating Expenses has increased in each of the last eight quarters, with growth averaging 16.2% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q1 2022, with growth of 161.0%; the weakest was Q2 2024, with a decline of 4.8%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $83.71 million (Q1 2026), $84.01 million (Q4 2025) and $83.09 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Alphabet | 4,126.42 Bn | 3,883.94 Bn | 73.85 Bn | 79.03 Bn |
| 2 | Meta Platforms | 1,763.57 Bn | 1,466.09 Bn | 49.47 Bn | 42.03 Bn |
| 3 | Netflix | 287.17 Bn | 247.37 Bn | 6.52 Bn | 1.51 Bn |
| 4 | Alibaba Group Holding | 252.08 Bn | 65.86 Bn | 15.11 Bn | -5.17 Bn |
| 5 | Shopify | 224.54 Bn | 201.72 Bn | 1.71 Bn | 1.22 Bn |
| 6 | Uber Technologies | 140.28 Bn | 112.08 Bn | 6.38 Bn | 12.30 Bn |
| 7 | Booking Holdings | 125.81 Bn | 58.86 Bn | - | 4.85 Bn |
| 8 | PDD Holdings | 114.10 Bn | -129.68 Bn | 9.45 Bn | -5.39 Bn |
| 9 | Spotify Technology | 108.24 Bn | 65.74 Bn | 1.86 Bn | 640.46 Mn |
| 10 | Xometry | 5.09 Bn | 3.90 Bn | 87.15 Mn | 92.70 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 92.70 Mn |
| Mar 31, 2026 | 83.71 Mn |
| Dec 31, 2025 | 84.01 Mn |
| Sep 30, 2025 | 83.09 Mn |
| Jun 30, 2025 | 75.47 Mn |
| Mar 31, 2025 | 71.72 Mn |
| Dec 31, 2024 | 70.54 Mn |
| Sep 30, 2024 | 67.31 Mn |
| Jun 30, 2024 | 68.17 Mn |
| Mar 31, 2024 | 65.76 Mn |
| Dec 31, 2023 | 61.62 Mn |
| Sep 30, 2023 | 59.45 Mn |
| Jun 30, 2023 | 71.61 Mn |
| Mar 31, 2023 | 59.16 Mn |
| Dec 31, 2022 | 61.79 Mn |
| Sep 30, 2022 | 56.10 Mn |
| Jun 30, 2022 | 53.30 Mn |
| Mar 31, 2022 | 51.89 Mn |
| Dec 31, 2021 | 43.51 Mn |
| Sep 30, 2021 | 28.76 Mn |
API Access
Xometry 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=XMTR&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "XMTR", "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=XMTR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();