Liquidmetal Technologies (LQMT) Operating Expenses (2011 - 2026)
Liquidmetal Technologies (LQMT) reported Operating Expenses of $1.27 million for Q2 2026, up 37.1% from $929,000 a year earlier and up 4.9% from the prior quarter.
Liquidmetal Technologies (LQMT) Operating Expenses (2011 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Liquidmetal Technologies' Operating Expenses came in at $4.55 million, up 19.5% year-over-year; for FY2025, it was $3.97 million, up 12.5% from FY2024.
- Operating Expenses has increased for three consecutive years, with a five-year compound annual growth rate of 0.5% (FY2020 to FY2025).
- By year, Operating Expenses came in at $3.53 million in FY2024 (+9.2%), $3.23 million in FY2023 (+3.7%), $3.12 million in FY2022 (-26.5%) and $4.24 million in FY2021 (+9.6%).
- The Q2 2026 figure ranks as the highest quarterly Operating Expenses since Q3 2021.
- Year over year, Operating Expenses has now increased in each of the last eight quarters, with growth averaging 21.7% over the last eight quarters.
- The high point for year-over-year Operating Expenses in five years was Q3 2021 (growth of 47.2%); the low point was Q3 2022 (a decline of 54.0%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $1.22 million (Q1 2026), $1.1 million (Q4 2025) and $965,000 (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Rio Tinto | 182.38 Bn | 151.41 Bn | - | - |
| 2 | Southern Copper | 169.38 Bn | 148.16 Bn | 2.90 Bn | 1.67 Bn |
| 3 | Rio Tinto | 143.04 Bn | 103.55 Bn | - | - |
| 4 | Newmont | 124.97 Bn | 92.97 Bn | 4.03 Bn | 3.02 Bn |
| 5 | Freeport-Mcmoran | 99.21 Bn | 83.25 Bn | 2.19 Bn | 5.03 Bn |
| 6 | Agnico Eagle Mines | 94.08 Bn | 83.71 Bn | 2.43 Bn | 119.48 Mn |
| 7 | Barrick Mining | 69.27 Bn | 44.47 Bn | 2.90 Bn | 165.00 Mn |
| 8 | Nucor | 59.42 Bn | 48.80 Bn | 2.03 Bn | 405.00 Mn |
| 9 | ArcelorMittal | 48.25 Bn | 27.27 Bn | - | -780.00 Mn |
| 10 | Liquidmetal Technologies | 68.06 Mn | 13.57 Mn | 89,000.00 | 1.27 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.27 Mn |
| Mar 31, 2026 | 1.22 Mn |
| Dec 31, 2025 | 1.10 Mn |
| Sep 30, 2025 | 965,000.00 |
| Jun 30, 2025 | 929,000.00 |
| Mar 31, 2025 | 979,000.00 |
| Dec 31, 2024 | 991,000.00 |
| Sep 30, 2024 | 910,000.00 |
| Jun 30, 2024 | 862,000.00 |
| Mar 31, 2024 | 767,000.00 |
| Dec 31, 2023 | 714,000.00 |
| Sep 30, 2023 | 751,000.00 |
| Jun 30, 2023 | 957,000.00 |
| Mar 31, 2023 | 812,000.00 |
| Dec 31, 2022 | 754,000.00 |
| Sep 30, 2022 | 763,000.00 |
| Jun 30, 2022 | 788,000.00 |
| Mar 31, 2022 | 814,000.00 |
| Dec 31, 2021 | 798,000.00 |
| Sep 30, 2021 | 1.66 Mn |
Liquidmetal Technologies Operating 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=operating-expenses&ticker=LQMT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "LQMT", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=LQMT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();