Everspin Technologies (MRAM) Operating Leases (2019 - 2026)
Everspin Technologies' Operating Leases came in at $1.43 million for Q2 2026, down 46.2% from $2.65 million a year earlier and down 10.7% from the prior quarter.
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Analysis
Everspin Technologies (MRAM) Operating Leases (2019 - 2026) Analysis & Trends
At the end of FY2025, Everspin Technologies' Operating Leases was $1.96 million, down 41.4% from FY2024.
- Operating Leases has declined in each of the last three years, though with a five-year compound annual growth rate of 16.7% (FY2020 to FY2025).
- Going back by year, Operating Leases was $3.34 million in FY2024 (-24.0%), $4.39 million in FY2023 (-21.3%), $5.58 million in FY2022 and $68,000 in FY2021 (-92.5%).
- The Q2 2026 figure represents the lowest quarterly Operating Leases since Q4 2021.
- Year-over-year, Operating Leases has declined for 12 consecutive quarters, with an average decline of 35.2% over the last eight quarters.
- The fastest year-over-year change in Operating Leases over five years came in Q2 2022 (growth of 497.0%), and the weakest in Q4 2021 (a decline of 92.5%).
- Business Quant data shows MRAM's Operating Leases at $1.6 million (Q1 2026), $1.96 million (Q4 2025) and $2.31 million (Q3 2025) in the three quarters before Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Nvidia | 5,638.19 Bn | 5,412.36 Bn | 72.14 Bn |
| 2 | Taiwan Semiconductor Manufacturing | 2,452.80 Bn | 2,078.51 Bn | 27.22 Bn |
| 3 | Broadcom | 1,695.44 Bn | 1,621.48 Bn | 20.46 Bn |
| 4 | Micron Technology | 1,213.55 Bn | 1,152.31 Bn | 35.06 Bn |
| 5 | Advanced Micro Devices | 1,034.54 Bn | 991.29 Bn | 6.20 Bn |
| 6 | Asml Holding | 719.69 Bn | 675.53 Bn | 5.90 Bn |
| 7 | Intel | 601.78 Bn | 486.52 Bn | 6.51 Bn |
| 8 | Lam Research | 434.81 Bn | 411.60 Bn | 3.48 Bn |
| 9 | Applied Materials | 428.57 Bn | 394.02 Bn | 4.59 Bn |
| 10 | Everspin Technologies | 457.03 Mn | 282.93 Mn | 10.10 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.43 Mn |
| Mar 31, 2026 | 1.60 Mn |
| Dec 31, 2025 | 1.96 Mn |
| Sep 30, 2025 | 2.31 Mn |
| Jun 30, 2025 | 2.65 Mn |
| Mar 31, 2025 | 3.00 Mn |
| Dec 31, 2024 | 3.34 Mn |
| Sep 30, 2024 | 3.67 Mn |
| Jun 30, 2024 | 4.00 Mn |
| Mar 31, 2024 | 4.32 Mn |
| Dec 31, 2023 | 4.39 Mn |
| Sep 30, 2023 | 4.69 Mn |
| Jun 30, 2023 | 4.99 Mn |
| Mar 31, 2023 | 5.29 Mn |
| Dec 31, 2022 | 5.58 Mn |
| Sep 30, 2022 | 5.86 Mn |
| Jun 30, 2022 | 2.78 Mn |
| Mar 31, 2022 | 2.90 Mn |
| Dec 31, 2021 | 68,000.00 |
| Sep 30, 2021 | 268,000.00 |
API Access
Everspin Technologies Operating Leases 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-leases&ticker=MRAM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-leases", "ticker": "MRAM", "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-leases&ticker=MRAM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();