Quicklogic (QUIK) Operating Expenses (2010 - 2026)
Quicklogic (QUIK) posted Operating Expenses of $4.12 million for Q2 2026, up 18.6% from $3.48 million a year earlier and up 4.1% from the prior quarter.
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Analysis
Quicklogic (QUIK) Operating Expenses (2010 - 2026) Analysis & Trends
For the trailing twelve months through Jun 28, 2026, Operating Expenses at Quicklogic was $15.7 million, up 5.9% year-over-year; for FY2025, it came in at $14.65 million, up 0.3% from FY2024.
- Annual Operating Expenses has increased for three consecutive years, though with a four-year compound annual growth rate of -0.8% (FY2021 to FY2025).
- In prior years, Quicklogic's Operating Expenses was $14.61 million in FY2024 (+1.4%), $14.42 million in FY2023 (+14.4%), $12.6 million in FY2022 and $15.12 million in FY2021.
- Quarterly Operating Expenses has run from a low of $1.33 million in Q4 2022 to a high of $4.16 million in Q4 2025 over five years.
- On a year-over-year basis, Operating Expenses has increased in each of the last three quarters, with growth averaging 4.2% over the last eight quarters.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q4 2023, with growth of 174.6%; the weakest was Q3 2025, with a decline of 15.5%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $3.96 million (Q1 2026), $4.16 million (Q4 2025) and $3.46 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 | Quicklogic | 217.41 Mn | 156.68 Mn | 2.41 Mn | 4.12 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 28, 2026 | 4.12 Mn |
| Mar 29, 2026 | 3.96 Mn |
| Dec 28, 2025 | 4.16 Mn |
| Sep 28, 2025 | 3.46 Mn |
| Jun 29, 2025 | 3.48 Mn |
| Mar 30, 2025 | 3.86 Mn |
| Dec 29, 2024 | 3.41 Mn |
| Sep 29, 2024 | 4.09 Mn |
| Jun 30, 2024 | 3.44 Mn |
| Mar 31, 2024 | 3.67 Mn |
| Dec 31, 2023 | 3.65 Mn |
| Oct 1, 2023 | 3.85 Mn |
| Jul 2, 2023 | 3.43 Mn |
| Apr 2, 2023 | 3.49 Mn |
| Jan 1, 2023 | 1.33 Mn |
| Oct 2, 2022 | 2.92 Mn |
| Jul 3, 2022 | 3.17 Mn |
| Apr 3, 2022 | 3.47 Mn |
| Oct 3, 2021 | 3.99 Mn |
| Jul 4, 2021 | 3.45 Mn |
API Access
Quicklogic 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=QUIK&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "QUIK", "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=QUIK&period=max&api_key=YOUR_API_KEY");
const data = await res.json();