Lam Research (LRCX) Accumulated Expenses (2010 - 2026)
Lam Research's Accumulated Expenses was $2.35 billion in fiscal Q4 2026 (quarter ended Jun 28, 2026), down 1.8% from $2.39 billion a year earlier but up 13.3% from the prior quarter.
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Analysis
Lam Research (LRCX) Accumulated Expenses (2010 - 2026) Analysis & Trends
From fiscal Q4 2010 onward, Lam Research has reported Accumulated Expenses for 64 quarters.
- Accumulated Expenses shows a five-year compound annual growth rate of 6.5% (FY2021 to FY2026).
- In earlier fiscal years, Accumulated Expenses was $2.39 billion in FY2025 (+32.9%), $1.8 billion in FY2024 (-10.4%), $2.01 billion in FY2023 (+1.8%) and $1.97 billion in FY2022 (+14.8%).
- Quarterly Accumulated Expenses has moved between $1.63 billion (fiscal Q1 2022) and $2.44 billion (fiscal Q1 2026) over five years.
- Compared with a year earlier, Accumulated Expenses was higher in seven of the last eight quarters, with growth averaging 9.5%.
- The best year-over-year quarter for Accumulated Expenses over five years was fiscal Q4 2025 (growth of 32.9%); the worst was fiscal Q4 2024 (a decline of 10.4%).
- Per Business Quant data, LRCX's Accumulated Expenses in the three fiscal quarters before Q4 2026 was $2.08 billion (Q3 2026), $2.27 billion (Q2 2026) and $2.44 billion (Q1 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Nvidia | 5,136.26 Bn | 4,910.42 Bn | 72.14 Bn |
| 2 | Taiwan Semiconductor Manufacturing | 2,136.54 Bn | 1,761.41 Bn | 27.22 Bn |
| 3 | Broadcom | 1,540.90 Bn | 1,466.94 Bn | 20.46 Bn |
| 4 | Micron Technology | 967.10 Bn | 872.74 Bn | 47.05 Bn |
| 5 | Advanced Micro Devices | 829.08 Bn | 785.83 Bn | 6.20 Bn |
| 6 | Asml Holding | 608.19 Bn | 563.87 Bn | 5.90 Bn |
| 7 | Intel | 435.73 Bn | 304.86 Bn | 6.51 Bn |
| 8 | Applied Materials | 298.50 Bn | 263.94 Bn | 4.59 Bn |
| 9 | Lam Research | 288.46 Bn | 265.26 Bn | 3.48 Bn |
| 10 | Texas Instruments | 256.17 Bn | 234.00 Bn | 3.35 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 28, 2026 | 2.35 Bn |
| Mar 29, 2026 | 2.08 Bn |
| Dec 28, 2025 | 2.27 Bn |
| Sep 28, 2025 | 2.44 Bn |
| Jun 29, 2025 | 2.39 Bn |
| Mar 30, 2025 | 2.00 Bn |
| Dec 29, 2024 | 2.10 Bn |
| Sep 29, 2024 | 2.20 Bn |
| Jun 30, 2024 | 1.80 Bn |
| Mar 31, 2024 | 1.79 Bn |
| Dec 24, 2023 | 1.98 Bn |
| Sep 24, 2023 | 2.12 Bn |
| Jun 25, 2023 | 2.01 Bn |
| Mar 26, 2023 | 1.99 Bn |
| Dec 25, 2022 | 2.07 Bn |
| Sep 25, 2022 | 1.95 Bn |
| Jun 26, 2022 | 1.97 Bn |
| Mar 27, 2022 | 1.63 Bn |
| Dec 26, 2021 | 1.77 Bn |
| Sep 26, 2021 | 1.63 Bn |
API Access
Lam Research 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=LRCX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "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=accumulated-expenses&ticker=LRCX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();