Everspin Technologies (MRAM) Cash & Equivalents (2015 - 2026)
Everspin Technologies (MRAM) posted Cash & Equivalents of $43.9 million for Q2 2026, down 2.4% from $44.96 million a year earlier but up 8.4% from the prior quarter.
Everspin Technologies (MRAM) Cash & Equivalents (2015 - 2026) Analysis & Trends
At the end of FY2025, Everspin Technologies' Cash & Equivalents came in at $44.45 million, up 5.6% from FY2024.
- Annual Cash & Equivalents has increased for six consecutive years, with a five-year compound annual growth rate of 24.9% (FY2020 to FY2025).
- In prior years, Everspin Technologies' Cash & Equivalents was $42.1 million in FY2024 (+13.9%), $36.95 million in FY2023 (+37.9%), $26.8 million in FY2022 (+25.2%) and $21.41 million in FY2021 (+46.6%).
- Quarterly Cash & Equivalents has run from a low of $14.56 million in Q3 2021 to a high of $45.26 million in Q3 2025 over five years.
- On a year-over-year basis, Cash & Equivalents increased in six of the last eight quarters, with growth averaging 10.5%.
- The strongest year-over-year quarter for Cash & Equivalents in the past five years was Q2 2022, with growth of 62.1%; the weakest was Q1 2026, with a decline of 3.9%.
- According to Business Quant data, Cash & Equivalents for the three prior quarters was $40.49 million (Q1 2026), $44.45 million (Q4 2025) and $45.26 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Cash & Equiv. (Qtr) |
|---|---|---|---|---|---|
| 1 | Nvidia | 5,638.19 Bn | 5,412.36 Bn | 72.14 Bn | 22.44 Bn |
| 2 | Taiwan Semiconductor Manufacturing | 2,452.80 Bn | 2,078.51 Bn | 27.22 Bn | 99.16 Bn |
| 3 | Broadcom | 1,695.44 Bn | 1,621.48 Bn | 20.46 Bn | 23.98 Bn |
| 4 | Micron Technology | 1,213.55 Bn | 1,152.31 Bn | 35.06 Bn | 25.00 Bn |
| 5 | Advanced Micro Devices | 1,034.54 Bn | 991.29 Bn | 6.20 Bn | 5.09 Bn |
| 6 | Asml Holding | 719.69 Bn | 675.53 Bn | 5.90 Bn | 15.03 Bn |
| 7 | Intel | 601.78 Bn | 486.52 Bn | 6.51 Bn | 12.87 Bn |
| 8 | Lam Research | 434.81 Bn | 411.60 Bn | 3.48 Bn | 5.58 Bn |
| 9 | Applied Materials | 428.57 Bn | 394.02 Bn | 4.59 Bn | 7.04 Bn |
| 10 | Everspin Technologies | 457.03 Mn | 282.93 Mn | 10.10 Mn | 43.90 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 43.90 Mn |
| Mar 31, 2026 | 40.49 Mn |
| Dec 31, 2025 | 44.45 Mn |
| Sep 30, 2025 | 45.26 Mn |
| Jun 30, 2025 | 44.96 Mn |
| Mar 31, 2025 | 42.16 Mn |
| Dec 31, 2024 | 42.10 Mn |
| Sep 30, 2024 | 39.59 Mn |
| Jun 30, 2024 | 36.76 Mn |
| Mar 31, 2024 | 34.80 Mn |
| Dec 31, 2023 | 36.95 Mn |
| Sep 30, 2023 | 34.93 Mn |
| Jun 30, 2023 | 30.83 Mn |
| Mar 31, 2023 | 24.21 Mn |
| Dec 31, 2022 | 26.80 Mn |
| Sep 30, 2022 | 23.44 Mn |
| Jun 30, 2022 | 23.05 Mn |
| Mar 31, 2022 | 19.89 Mn |
| Dec 31, 2021 | 21.41 Mn |
| Sep 30, 2021 | 14.56 Mn |
Everspin Technologies Cash & Equivalents 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=cash-and-equivalents&ticker=MRAM&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "cash-and-equivalents", "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=cash-and-equivalents&ticker=MRAM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();