ConnectM Technology Solutions (CNTM) Operating Expenses (2022 - 2026)
ConnectM Technology Solutions' Operating Expenses came in at $5.4 million for Q2 2026, down 17.9% from $6.58 million a year earlier.
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Analysis
ConnectM Technology Solutions (CNTM) Operating Expenses (2022 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, ConnectM Technology Solutions reported Operating Expenses of $22.9 million, up 3.9% year-over-year; for FY2025, it was $23.5 million, down 31.4% from FY2024.
- Operating Expenses carries a four-year compound annual growth rate of 486.3% (FY2021 to FY2025).
- Going back by year, Operating Expenses was $34.26 million in FY2024 (+24.9%), $27.44 million in FY2023, $2.1 million in FY2022 and $19,889 in FY2021.
- The five-year range for quarterly Operating Expenses is $27,021 (Q1 2022) to $6.58 million (Q2 2025).
- Year-over-year, Operating Expenses increased in six of the last seven quarters, with growth averaging 46.5%.
- The fastest year-over-year change in Operating Expenses over five years came in Q2 2024 (growth of 480.3%), and the weakest in Q2 2026 (a decline of 17.9%).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 255.42 Bn | 240.49 Bn | 2.30 Bn | 2.13 Bn |
| 2 | CrowdStrike Holdings | 232.07 Bn | 212.47 Bn | 1.10 Bn | 1.13 Bn |
| 3 | Fortinet | 125.35 Bn | 111.28 Bn | 1.64 Bn | 953.90 Mn |
| 4 | Snowflake | 111.63 Bn | 98.94 Bn | 1.04 Bn | 1.30 Bn |
| 5 | Datadog | 91.35 Bn | 72.99 Bn | 881.34 Mn | 875.89 Mn |
| 6 | Zscaler | 34.43 Bn | 20.55 Bn | - | - |
| 7 | Okta | 33.87 Bn | 23.97 Bn | 641.00 Mn | 534.00 Mn |
| 8 | Axon Enterprise | 31.65 Bn | 26.18 Bn | 546.45 Mn | 499.67 Mn |
| 9 | MongoDB | 29.46 Bn | 19.93 Bn | 569.77 Mn | 541.37 Mn |
| 10 | ConnectM Technology Solutions | 24.76 Mn | 14.76 Mn | 2.80 Mn | 5.40 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 5.40 Mn |
| Dec 31, 2025 | 5.23 Mn |
| Sep 30, 2025 | 5.69 Mn |
| Jun 30, 2025 | 6.58 Mn |
| Mar 31, 2025 | 6.34 Mn |
| Dec 31, 2024 | 4.78 Mn |
| Sep 30, 2024 | 4.33 Mn |
| Jun 30, 2024 | 3.15 Mn |
| Mar 31, 2024 | 3.08 Mn |
| Dec 31, 2023 | 3.54 Mn |
| Sep 30, 2023 | 2.84 Mn |
| Jun 30, 2023 | 543,038.00 |
| Mar 31, 2023 | 809,927.00 |
| Dec 31, 2022 | 1.04 Mn |
| Sep 30, 2022 | 515,626.00 |
| Jun 30, 2022 | 515,881.00 |
| Mar 31, 2022 | 27,021.00 |
API Access
ConnectM Technology Solutions 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=CNTM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "CNTM", "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=CNTM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();