Sitime (SITM) Operating Expenses (2018 - 2026)
Sitime's Operating Expenses was $90.93 million in Q2 2026, up 49.9% from $60.66 million a year earlier and up 14.7% from the prior quarter.
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Analysis
Sitime (SITM) Operating Expenses (2018 - 2026) Analysis & Trends
On a trailing twelve-month basis, Sitime's Operating Expenses was $293.08 million through Jun 30, 2026, up 26.2% year-over-year; for FY2025, it was $241.96 million, up 10.1% from FY2024.
- Operating Expenses has now increased for seven consecutive years, with a five-year compound annual growth rate of 29.5% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $219.73 million in FY2024 (+16.1%), $189.29 million in FY2023 (+13.5%), $166.82 million in FY2022 (+56.5%) and $106.62 million in FY2021 (+60.2%).
- The Q2 2026 figure marks the highest quarterly Operating Expenses in data going back to Q4 2018.
- Compared with a year earlier, Operating Expenses has increased for 27 straight quarters, with growth averaging 20.2% over the last eight quarters.
- The year-over-year growth in Operating Expenses has ranged between 3.0% (Q3 2023) and 75.6% (Q1 2022) over the last five years.
- Per Business Quant data, SITM's Operating Expenses in the three quarters before Q2 2026 was $79.29 million (Q1 2026), $62.12 million (Q4 2025) and $60.74 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Nvidia | 5,638.19 Bn | 5,412.36 Bn | 72.14 Bn | 8.41 Bn |
| 2 | Taiwan Semiconductor Manufacturing | 2,452.80 Bn | 2,078.51 Bn | 27.22 Bn | 3.13 Bn |
| 3 | Broadcom | 1,695.44 Bn | 1,621.48 Bn | 20.46 Bn | 4.50 Bn |
| 4 | Micron Technology | 1,213.55 Bn | 1,152.31 Bn | 35.06 Bn | 1.72 Bn |
| 5 | Advanced Micro Devices | 1,034.54 Bn | 991.29 Bn | 6.20 Bn | 4.21 Bn |
| 6 | Asml Holding | 719.69 Bn | 675.53 Bn | 5.90 Bn | - |
| 7 | Intel | 601.78 Bn | 486.52 Bn | 6.51 Bn | 4.71 Bn |
| 8 | Lam Research | 434.81 Bn | 411.60 Bn | 3.48 Bn | 965.25 Mn |
| 9 | Applied Materials | 428.57 Bn | 394.02 Bn | 4.59 Bn | 1.51 Bn |
| 10 | Sitime | 18.81 Bn | 14.48 Bn | 99.14 Mn | 90.93 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 90.93 Mn |
| Mar 31, 2026 | 79.29 Mn |
| Dec 31, 2025 | 62.12 Mn |
| Sep 30, 2025 | 60.74 Mn |
| Jun 30, 2025 | 60.66 Mn |
| Mar 31, 2025 | 58.44 Mn |
| Dec 31, 2024 | 58.86 Mn |
| Sep 30, 2024 | 54.33 Mn |
| Jun 30, 2024 | 53.84 Mn |
| Mar 31, 2024 | 52.70 Mn |
| Dec 31, 2023 | 51.16 Mn |
| Sep 30, 2023 | 45.09 Mn |
| Jun 30, 2023 | 47.84 Mn |
| Mar 31, 2023 | 45.19 Mn |
| Dec 31, 2022 | 43.49 Mn |
| Sep 30, 2022 | 43.76 Mn |
| Jun 30, 2022 | 40.39 Mn |
| Mar 31, 2022 | 39.17 Mn |
| Dec 31, 2021 | 31.94 Mn |
| Sep 30, 2021 | 27.62 Mn |
API Access
Sitime 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=SITM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "SITM", "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=SITM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();