Smith Micro Software (SMSI) Operating Expenses (2010 - 2026)
Smith Micro Software's Operating Expenses came in at $5.9 million for Q2 2026, down 67.6% from $18.2 million a year earlier and down 11.7% from the prior quarter.
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Analysis
Smith Micro Software (SMSI) Operating Expenses (2010 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Smith Micro Software reported Operating Expenses of $27.68 million, down 38.3% year-over-year; for FY2025, it was $41.87 million, down 34.4% from FY2024.
- Operating Expenses carries a five-year compound annual growth rate of -0.3% (FY2020 to FY2025).
- Going back by year, Operating Expenses was $63.82 million in FY2024 (+32.0%), $48.36 million in FY2023 (-25.9%), $65.23 million in FY2022 (-14.9%) and $76.66 million in FY2021 (+80.0%).
- The Q2 2026 figure represents the lowest quarterly Operating Expenses since Q4 2018.
- Year-over-year, Operating Expenses has declined for four consecutive quarters, with an average decline of 20.5% over the last eight quarters.
- The fastest year-over-year change in Operating Expenses over five years came in Q3 2021 (growth of 181.0%), and the weakest in Q1 2025 (a decline of 75.7%).
- Business Quant data shows SMSI's Operating Expenses at $6.68 million (Q1 2026), $7.4 million (Q4 2025) and $7.7 million (Q3 2025) in the three quarters before Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Adobe | 90.32 Bn | 65.57 Bn | 6.00 Bn | 3.64 Bn |
| 2 | Atlassian | 46.45 Bn | 39.73 Bn | 1.53 Bn | 1.32 Bn |
| 3 | Twilio | 44.08 Bn | 34.07 Bn | 725.87 Mn | 641.32 Mn |
| 4 | Autodesk | 43.30 Bn | 31.34 Bn | 1.87 Bn | 1.27 Bn |
| 5 | Zoom Communications | 25.52 Bn | -5.27 Bn | 985.50 Mn | 671.18 Mn |
| 6 | Figma | 10.74 Bn | 4.24 Bn | 309.61 Mn | 426.90 Mn |
| 7 | Dropbox | 7.01 Bn | 2.65 Bn | 506.50 Mn | 341.70 Mn |
| 8 | Nice | 6.59 Bn | 5.06 Bn | 995.81 Mn | 765.06 Mn |
| 9 | RingCentral | 6.37 Bn | 5.87 Bn | 472.31 Mn | 422.02 Mn |
| 10 | Smith Micro Software | 14.81 Mn | 7.39 Mn | 3.53 Mn | 5.90 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 5.90 Mn |
| Mar 31, 2026 | 6.68 Mn |
| Dec 31, 2025 | 7.40 Mn |
| Sep 30, 2025 | 7.70 Mn |
| Jun 30, 2025 | 18.20 Mn |
| Mar 31, 2025 | 8.57 Mn |
| Dec 31, 2024 | 8.22 Mn |
| Sep 30, 2024 | 9.83 Mn |
| Jun 30, 2024 | 10.51 Mn |
| Mar 31, 2024 | 35.26 Mn |
| Dec 31, 2023 | 12.13 Mn |
| Sep 30, 2023 | 10.65 Mn |
| Jun 30, 2023 | 10.99 Mn |
| Mar 31, 2023 | 14.58 Mn |
| Dec 31, 2022 | 15.24 Mn |
| Sep 30, 2022 | 16.43 Mn |
| Jun 30, 2022 | 17.43 Mn |
| Mar 31, 2022 | 16.14 Mn |
| Dec 31, 2021 | 14.61 Mn |
| Sep 30, 2021 | 31.21 Mn |
API Access
Smith Micro Software 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=SMSI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "SMSI", "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=SMSI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();