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.
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 Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Nvidia | 5,503.96 Bn | 5,278.12 Bn | 72.14 Bn |
| 2 | Taiwan Semiconductor Manufacturing | 2,366.45 Bn | 1,992.15 Bn | 27.22 Bn |
| 3 | Broadcom | 1,676.58 Bn | 1,602.63 Bn | 20.46 Bn |
| 4 | Micron Technology | 1,202.51 Bn | 1,141.27 Bn | 35.06 Bn |
| 5 | Advanced Micro Devices | 998.39 Bn | 955.14 Bn | 6.20 Bn |
| 6 | Asml Holding | 698.25 Bn | 654.08 Bn | 5.90 Bn |
| 7 | Intel | 606.32 Bn | 491.05 Bn | 6.51 Bn |
| 8 | Lam Research | 411.06 Bn | 387.85 Bn | 3.48 Bn |
| 9 | Applied Materials | 405.83 Bn | 371.27 Bn | 4.59 Bn |
| 10 | Arm Holdings | 307.33 Bn | 293.04 Bn | 1.25 Bn |
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 |
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_KEY
import 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();