Lam Research (LRCX) Tax Provisions (2009 - 2026)
Lam Research's Tax Provisions was $559.08 million in fiscal Q1 2027 (quarter ended Sep 27, 2026), up 92.5% from $290.5 million a year earlier and up 101.2% from the prior quarter.
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Analysis
Lam Research (LRCX) Tax Provisions (2009 - 2026) Analysis & Trends
On a trailing twelve-month basis, Lam Research's Tax Provisions was $1.27 billion through Sep 27, 2026, up 77.6% year-over-year; for FY2026 (ended Jun 28, 2026), it 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%).
- The fiscal Q1 2027 figure marks the highest quarterly Tax Provisions since fiscal Q2 2018.
- Compared with a year earlier, Tax Provisions was higher in six of the last eight quarters, with growth averaging 74.5%.
- 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 Q1 2027 was $277.86 million (Q4 2026), $186.1 million (Q3 2026) and $242.62 million (Q2 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Taxes (Qtr) |
|---|---|---|---|---|---|
| 1 | SK hynix | 24,980.27 Bn | 24,964.04 Bn | 43.99 Bn | 19.19 Bn |
| 2 | Taiwan Semiconductor Manufacturing | 10,337.48 Bn | 9,919.73 Bn | 31.04 Bn | 4.62 Bn |
| 3 | Nvidia | 3,939.34 Bn | 3,713.50 Bn | 72.14 Bn | 11.82 Bn |
| 4 | Broadcom | 1,653.85 Bn | 1,579.89 Bn | 20.46 Bn | 2.19 Bn |
| 5 | Micron Technology | 880.27 Bn | 785.91 Bn | 47.05 Bn | 6.58 Bn |
| 6 | Advanced Micro Devices | 875.86 Bn | 824.07 Bn | 7.21 Bn | -555.00 Mn |
| 7 | Asml Holding | 576.26 Bn | 531.95 Bn | 5.90 Bn | - |
| 8 | Intel | 316.79 Bn | 179.50 Bn | 7.10 Bn | 462.00 Mn |
| 9 | Applied Materials | 294.03 Bn | 294.03 Bn | 5.25 Bn | 359.00 Mn |
| 10 | Lam Research | 282.21 Bn | 258.26 Bn | 4.30 Bn | 559.08 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 27, 2026 | 559.08 Mn |
| 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 |
API Access
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_KEYimport 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();