Lam Research (LRCX) Tax Provisions (2009 - 2026)
Lam Research's Tax Provisions was $277.86 million in fiscal Q4 2026 (quarter ended Jun 28, 2026), up 371.8% from $58.89 million a year earlier and up 49.3% from the prior quarter.
Lam Research (LRCX) Tax Provisions (2009 - 2026) Analysis & Trends
For FY2026 (ended Jun 28, 2026), Tax Provisions at Lam Research came in at $997.08 million, up 66.2% from FY2025.
- Tax Provisions shows a five-year compound annual growth rate of 16.6% (FY2021 to FY2026).
- In earlier fiscal years, Tax Provisions was $599.91 million in FY2025 (+12.7%), $532.45 million in FY2024 (-11.0%), $598.28 million in FY2023 (+1.8%) and $587.83 million in FY2022 (+27.1%).
- Quarterly Tax Provisions has moved between $58.89 million (fiscal Q4 2025) and $290.5 million (fiscal Q1 2026) over five years.
- Compared with a year earlier, Tax Provisions was higher in six of the last eight quarters, with growth averaging 66.6%.
- The best year-over-year quarter for Tax Provisions over five years was fiscal Q4 2026 (growth of 371.8%); the worst was fiscal Q4 2023 (a decline of 59.3%).
- Per Business Quant data, LRCX's Tax Provisions in the three fiscal quarters before Q4 2026 was $186.1 million (Q3 2026), $242.62 million (Q2 2026) and $290.5 million (Q1 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Taxes (Qtr) |
|---|---|---|---|---|---|
| 1 | Nvidia | 5,503.96 Bn | 5,278.12 Bn | 72.14 Bn | 11.82 Bn |
| 2 | Taiwan Semiconductor Manufacturing | 2,366.45 Bn | 1,992.15 Bn | 27.22 Bn | 4.92 Bn |
| 3 | Broadcom | 1,676.58 Bn | 1,602.63 Bn | 20.46 Bn | 2.19 Bn |
| 4 | Micron Technology | 1,202.51 Bn | 1,141.27 Bn | 35.06 Bn | 4.98 Bn |
| 5 | Advanced Micro Devices | 998.39 Bn | 955.14 Bn | 6.20 Bn | 252.00 Mn |
| 6 | Asml Holding | 698.25 Bn | 654.08 Bn | 5.90 Bn | - |
| 7 | Intel | 606.32 Bn | 491.05 Bn | 6.51 Bn | 29.00 Mn |
| 8 | Lam Research | 411.06 Bn | 387.85 Bn | 3.48 Bn | 277.86 Mn |
| 9 | Applied Materials | 405.83 Bn | 371.27 Bn | 4.59 Bn | 369.00 Mn |
| 10 | Arm Holdings | 307.33 Bn | 293.04 Bn | 1.25 Bn | 17.00 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 28, 2026 | 277.86 Mn |
| Mar 29, 2026 | 186.10 Mn |
| Dec 28, 2025 | 242.62 Mn |
| Sep 28, 2025 | 290.50 Mn |
| Jun 29, 2025 | 58.89 Mn |
| Mar 30, 2025 | 206.06 Mn |
| Dec 29, 2024 | 157.13 Mn |
| Sep 29, 2024 | 177.83 Mn |
| Jun 30, 2024 | 134.07 Mn |
| Mar 31, 2024 | 127.36 Mn |
| Dec 24, 2023 | 132.79 Mn |
| Sep 24, 2023 | 138.23 Mn |
| Jun 25, 2023 | 61.08 Mn |
| Mar 26, 2023 | 124.91 Mn |
| Dec 25, 2022 | 183.42 Mn |
| Sep 25, 2022 | 228.87 Mn |
| Jun 26, 2022 | 149.97 Mn |
| Mar 27, 2022 | 112.92 Mn |
| Dec 26, 2021 | 161.31 Mn |
| Sep 26, 2021 | 163.63 Mn |
Lam Research Tax Provisions 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=tax-provisions&ticker=LRCX&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "tax-provisions", "ticker": "LRCX", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=tax-provisions&ticker=LRCX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();