Lam Research (LRCX) Total Liabilities (2009 - 2026)
Lam Research (LRCX) reported Total Liabilities of $12.44 billion for fiscal Q1 2027 (quarter ended Sep 27, 2026), up 6.3% from $11.71 billion a year earlier and up 12.5% from the prior quarter.
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Analysis
Lam Research (LRCX) Total Liabilities (2009 - 2026) Analysis & Trends
At the end of FY2026 (ended Jun 28, 2026), Lam Research posted Total Liabilities of $11.06 billion, down 3.7% from FY2025.
- Total Liabilities has a five-year compound annual growth rate of 2.3% (FY2021 to FY2026).
- By fiscal year, Total Liabilities came in at $11.48 billion in FY2025 (+12.5%), $10.21 billion in FY2024 (-3.5%), $10.57 billion in FY2023 (-3.2%) and $10.92 billion in FY2022 (+10.7%).
- The fiscal Q1 2027 figure ranks as the highest quarterly Total Liabilities in data going back to fiscal Q4 2010.
- Year over year, Total Liabilities gained in six of the last eight quarters, with growth averaging 3.4%.
- The high point for year-over-year Total Liabilities in five years was fiscal Q1 2023 (growth of 16.0%); the low point was fiscal Q1 2024 (a decline of 7.2%).
- Per Business Quant data, the three fiscal quarters before Q1 2027 came in at $11.06 billion (Q4 2026), $10.21 billion (Q3 2026) and $11.25 billion (Q2 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | SK hynix | 24,576.54 Bn | 24,560.31 Bn | 43.99 Bn | 55.89 Bn |
| 2 | Taiwan Semiconductor Manufacturing | 10,284.32 Bn | 9,899.31 Bn | 27.22 Bn | 92.36 Bn |
| 3 | Nvidia | 4,083.27 Bn | 3,857.43 Bn | 72.14 Bn | 91.29 Bn |
| 4 | Broadcom | 1,582.22 Bn | 1,508.26 Bn | 20.46 Bn | 88.46 Bn |
| 5 | Advanced Micro Devices | 844.94 Bn | 793.16 Bn | 7.21 Bn | 26.42 Bn |
| 6 | Micron Technology | 820.10 Bn | 725.74 Bn | 47.05 Bn | 57.51 Bn |
| 7 | Asml Holding | 581.15 Bn | 536.84 Bn | 5.90 Bn | 36.36 Bn |
| 8 | Intel | 308.67 Bn | 171.38 Bn | 7.10 Bn | 97.02 Bn |
| 9 | Applied Materials | 295.64 Bn | 261.08 Bn | 4.59 Bn | 17.90 Bn |
| 10 | Lam Research | 277.80 Bn | 253.85 Bn | 4.30 Bn | 12.44 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 27, 2026 | 12.44 Bn |
| Jun 28, 2026 | 11.06 Bn |
| Mar 29, 2026 | 10.21 Bn |
| Dec 28, 2025 | 11.25 Bn |
| Sep 28, 2025 | 11.71 Bn |
| Jun 29, 2025 | 11.48 Bn |
| Mar 30, 2025 | 10.46 Bn |
| Dec 29, 2024 | 11.03 Bn |
| Sep 29, 2024 | 11.06 Bn |
| Jun 30, 2024 | 10.21 Bn |
| Mar 31, 2024 | 10.26 Bn |
| Dec 24, 2023 | 10.56 Bn |
| Sep 24, 2023 | 10.49 Bn |
| Jun 25, 2023 | 10.57 Bn |
| Mar 26, 2023 | 10.84 Bn |
| Dec 25, 2022 | 10.90 Bn |
| Sep 25, 2022 | 11.31 Bn |
| Jun 26, 2022 | 10.92 Bn |
| Mar 27, 2022 | 10.56 Bn |
| Dec 26, 2021 | 10.21 Bn |
API Access
Lam Research Total Liabilities 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=total-liabilities&ticker=LRCX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "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=total-liabilities&ticker=LRCX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();