Everspin Technologies (MRAM) Research & Development (2015 - 2026)
Everspin Technologies (MRAM) recorded Research & Development of $4.84 million in Q2 2026, up 35.1% from $3.58 million a year earlier and up 34.2% from the prior quarter.
Everspin Technologies (MRAM) Research & Development (2015 - 2026) Analysis & Trends
On a TTM basis, Everspin Technologies' Research & Development came in at $15.59 million as of Jun 30, 2026, up 13.4% year-over-year; for FY2025, it was $14.09 million, up 2.9% from FY2024.
- Annual Research & Development has increased for three straight years, with a five-year compound annual growth rate of 5.3% (FY2020 to FY2025).
- Across earlier years, Research & Development came in at $13.69 million in FY2024 (+16.2%), $11.78 million in FY2023 (+6.0%), $11.11 million in FY2022 (-12.0%) and $12.63 million in FY2021 (+15.9%).
- The Q2 2026 figure is the highest quarterly Research & Development since Q3 2018.
- On a year-over-year basis, Research & Development has increased for five consecutive quarters, with growth averaging 11.0% over the last eight quarters.
- Peak year-over-year performance for Research & Development in the last five years was growth of 48.3% in Q4 2021, against a decline of 19.6% in Q2 2022 at the low end.
- Per Business Quant, the preceding three quarters came in at $3.61 million (Q1 2026), $3.57 million (Q4 2025) and $3.58 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | R&D (Qtr) |
|---|---|---|---|---|---|
| 1 | Nvidia | 5,638.19 Bn | 5,412.36 Bn | 72.14 Bn | 7.05 Bn |
| 2 | Taiwan Semiconductor Manufacturing | 2,452.80 Bn | 2,078.51 Bn | 27.22 Bn | 2.31 Bn |
| 3 | Broadcom | 1,695.44 Bn | 1,621.48 Bn | 20.46 Bn | 2.90 Bn |
| 4 | Micron Technology | 1,213.55 Bn | 1,152.31 Bn | 35.06 Bn | 1.32 Bn |
| 5 | Advanced Micro Devices | 1,034.54 Bn | 991.29 Bn | 6.20 Bn | 2.53 Bn |
| 6 | Asml Holding | 719.69 Bn | 675.53 Bn | 5.90 Bn | - |
| 7 | Intel | 601.78 Bn | 486.52 Bn | 6.51 Bn | 3.37 Bn |
| 8 | Lam Research | 434.81 Bn | 411.60 Bn | 3.48 Bn | 642.92 Mn |
| 9 | Applied Materials | 428.57 Bn | 394.02 Bn | 4.59 Bn | 1.10 Bn |
| 10 | Everspin Technologies | 457.03 Mn | 282.93 Mn | 10.10 Mn | 4.84 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 4.84 Mn |
| Mar 31, 2026 | 3.61 Mn |
| Dec 31, 2025 | 3.57 Mn |
| Sep 30, 2025 | 3.58 Mn |
| Jun 30, 2025 | 3.58 Mn |
| Mar 31, 2025 | 3.36 Mn |
| Dec 31, 2024 | 3.43 Mn |
| Sep 30, 2024 | 3.38 Mn |
| Jun 30, 2024 | 3.46 Mn |
| Mar 31, 2024 | 3.42 Mn |
| Dec 31, 2023 | 3.21 Mn |
| Sep 30, 2023 | 2.66 Mn |
| Jun 30, 2023 | 2.71 Mn |
| Mar 31, 2023 | 3.20 Mn |
| Dec 31, 2022 | 3.09 Mn |
| Sep 30, 2022 | 2.88 Mn |
| Jun 30, 2022 | 2.70 Mn |
| Mar 31, 2022 | 2.44 Mn |
| Dec 31, 2021 | 3.73 Mn |
| Sep 30, 2021 | 3.11 Mn |
Everspin Technologies Research & Development 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=research-and-development&ticker=MRAM&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "research-and-development", "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=research-and-development&ticker=MRAM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();