Everspin Technologies (MRAM) Finished Goods (2015 - 2026)
Everspin Technologies' Finished Goods was $559,000 in Q2 2026, down 55.4% from $1.25 million a year earlier and down 37.0% from the prior quarter.
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Analysis
Everspin Technologies (MRAM) Finished Goods (2015 - 2026) Analysis & Trends
At the end of FY2025, Finished Goods at Everspin Technologies came in at $1.14 million, down 16.2% from FY2024.
- Finished Goods shows a five-year compound annual growth rate of 18.8% (FY2020 to FY2025).
- In earlier years, Finished Goods was $1.36 million in FY2024 (-7.8%), $1.48 million in FY2023 (+16.3%), $1.27 million in FY2022 (-3.1%) and $1.31 million in FY2021 (+172.2%).
- The Q2 2026 figure marks the lowest quarterly Finished Goods since Q2 2021.
- Compared with a year earlier, Finished Goods has declined for three straight quarters, with an average decline of 9.4% over the last eight quarters.
- The best year-over-year quarter for Finished Goods over five years was Q1 2022 (growth of 617.6%); the worst was Q2 2026 (a decline of 55.4%).
- Per Business Quant data, MRAM's Finished Goods in the three quarters before Q2 2026 was $887,000 (Q1 2026), $1.14 million (Q4 2025) and $1.61 million (Q3 2025).
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 | 559,000.00 |
| Mar 31, 2026 | 887,000.00 |
| Dec 31, 2025 | 1.14 Mn |
| Sep 30, 2025 | 1.61 Mn |
| Jun 30, 2025 | 1.25 Mn |
| Mar 31, 2025 | 1.71 Mn |
| Dec 31, 2024 | 1.36 Mn |
| Sep 30, 2024 | 1.11 Mn |
| Jun 30, 2024 | 1.13 Mn |
| Mar 31, 2024 | 1.31 Mn |
| Dec 31, 2023 | 1.48 Mn |
| Sep 30, 2023 | 1.71 Mn |
| Jun 30, 2023 | 1.45 Mn |
| Mar 31, 2023 | 1.12 Mn |
| Dec 31, 2022 | 1.27 Mn |
| Sep 30, 2022 | 1.11 Mn |
| Jun 30, 2022 | 1.07 Mn |
| Mar 31, 2022 | 1.35 Mn |
| Dec 31, 2021 | 1.31 Mn |
| Sep 30, 2021 | 1.23 Mn |
API Access
Everspin Technologies Finished Goods 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=finished-goods&ticker=MRAM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "finished-goods", "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=finished-goods&ticker=MRAM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();