Maxlinear (MXL) Accumulated Expenses (2009 - 2026)
Maxlinear's Accumulated Expenses was $64.48 million in Q3 2026, down 16.1% from $76.8 million a year earlier but up 10.7% from the prior quarter.
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Analysis
Maxlinear (MXL) Accumulated Expenses (2009 - 2026) Analysis & Trends
At the end of FY2025, Accumulated Expenses at Maxlinear came in at $72.39 million, down 17.2% from FY2024.
- Accumulated Expenses has now declined for three consecutive years, with a five-year compound annual growth rate of -7.3% (FY2020 to FY2025).
- In earlier years, Accumulated Expenses was $87.41 million in FY2024 (-11.2%), $98.47 million in FY2023 (-1.7%), $100.16 million in FY2022 (+74.9%) and $57.27 million in FY2021 (-45.9%).
- Quarterly Accumulated Expenses has moved between $57.27 million (Q4 2021) and $120.01 million (Q2 2025) over five years.
- Compared with a year earlier, Accumulated Expenses has declined for four straight quarters, with an average decline of 6.8% over the last eight quarters.
- The best year-over-year quarter for Accumulated Expenses over five years was Q4 2022 (growth of 74.9%); the worst was Q2 2026 (a decline of 51.5%).
- Per Business Quant data, MXL's Accumulated Expenses in the three quarters before Q3 2026 was $58.24 million (Q2 2026), $59.71 million (Q1 2026) and $72.39 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | SK hynix | 24,980.27 Bn | 24,964.04 Bn | 43.99 Bn |
| 2 | Taiwan Semiconductor Manufacturing | 10,337.48 Bn | 9,919.73 Bn | 31.04 Bn |
| 3 | Nvidia | 3,939.34 Bn | 3,713.50 Bn | 72.14 Bn |
| 4 | Broadcom | 1,653.85 Bn | 1,579.89 Bn | 20.46 Bn |
| 5 | Micron Technology | 880.27 Bn | 785.91 Bn | 47.05 Bn |
| 6 | Advanced Micro Devices | 875.86 Bn | 824.07 Bn | 7.21 Bn |
| 7 | Asml Holding | 576.26 Bn | 531.95 Bn | 5.90 Bn |
| 8 | Intel | 316.79 Bn | 179.50 Bn | 7.10 Bn |
| 9 | Applied Materials | 294.03 Bn | 294.03 Bn | 5.25 Bn |
| 10 | Maxlinear | 5.08 Bn | 4.80 Bn | 128.07 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 64.48 Mn |
| Jun 30, 2026 | 58.24 Mn |
| Mar 31, 2026 | 59.71 Mn |
| Dec 31, 2025 | 72.39 Mn |
| Sep 30, 2025 | 76.80 Mn |
| Jun 30, 2025 | 120.01 Mn |
| Mar 31, 2025 | 106.99 Mn |
| Dec 31, 2024 | 87.41 Mn |
| Sep 30, 2024 | 71.20 Mn |
| Jun 30, 2024 | 70.97 Mn |
| Mar 31, 2024 | 98.13 Mn |
| Dec 31, 2023 | 98.47 Mn |
| Sep 30, 2023 | 86.28 Mn |
| Jun 30, 2023 | 90.69 Mn |
| Mar 31, 2023 | 112.94 Mn |
| Dec 31, 2022 | 100.16 Mn |
| Sep 30, 2022 | 94.41 Mn |
| Jun 30, 2022 | 93.51 Mn |
| Mar 31, 2022 | 75.55 Mn |
| Dec 31, 2021 | 57.27 Mn |
API Access
Maxlinear Accumulated 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=accumulated-expenses&ticker=MXL&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "MXL", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=accumulated-expenses&ticker=MXL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();