Atomera (ATOM) Operating Expenses (2015 - 2026)
Atomera (ATOM) recorded Operating Expenses of $6.89 million in Q2 2026, up 32.7% from $5.19 million a year earlier and up 11.0% from the prior quarter.
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Analysis
Atomera (ATOM) Operating Expenses (2015 - 2026) Analysis & Trends
On a TTM basis, Atomera's Operating Expenses came in at $23.31 million as of Jun 30, 2026, up 14.5% year-over-year; for FY2025, it came in at $20.87 million, up 7.9% from FY2024.
- Annual Operating Expenses has a five-year compound annual growth rate of 6.9% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $19.35 million in FY2024 (-8.7%), $21.2 million in FY2023 (+18.9%), $17.83 million in FY2022 (+11.9%) and $15.93 million in FY2021 (+6.4%).
- The Q2 2026 figure is the highest quarterly Operating Expenses in data going back to Q3 2015.
- On a year-over-year basis, Operating Expenses rose in five of the last eight quarters, with growth averaging 7.5%.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 32.7% in Q2 2026, against a decline of 13.7% in Q2 2024 at the low end.
- Per Business Quant, the preceding three quarters came in at $6.21 million (Q1 2026), $4.53 million (Q4 2025) and $5.68 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Nvidia | 5,235.65 Bn | 5,009.82 Bn | 72.14 Bn | 8.41 Bn |
| 2 | Taiwan Semiconductor Manufacturing | 2,206.84 Bn | 1,831.70 Bn | 27.22 Bn | 3.13 Bn |
| 3 | Broadcom | 1,595.23 Bn | 1,521.27 Bn | 20.46 Bn | 4.50 Bn |
| 4 | Micron Technology | 1,011.16 Bn | 916.79 Bn | 47.05 Bn | 2.77 Bn |
| 5 | Advanced Micro Devices | 874.75 Bn | 831.50 Bn | 6.20 Bn | 4.21 Bn |
| 6 | Asml Holding | 634.65 Bn | 590.34 Bn | 5.90 Bn | - |
| 7 | Intel | 469.01 Bn | 338.14 Bn | 6.51 Bn | 4.71 Bn |
| 8 | Lam Research | 331.52 Bn | 308.31 Bn | 3.48 Bn | 965.25 Mn |
| 9 | Applied Materials | 321.88 Bn | 287.32 Bn | 4.59 Bn | 1.51 Bn |
| 10 | Atomera | 116.71 Mn | 78.31 Mn | 132,000.00 | 6.89 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 6.89 Mn |
| Mar 31, 2026 | 6.21 Mn |
| Dec 31, 2025 | 4.53 Mn |
| Sep 30, 2025 | 5.68 Mn |
| Jun 30, 2025 | 5.19 Mn |
| Mar 31, 2025 | 5.47 Mn |
| Dec 31, 2024 | 4.88 Mn |
| Sep 30, 2024 | 4.82 Mn |
| Jun 30, 2024 | 4.63 Mn |
| Mar 31, 2024 | 5.02 Mn |
| Dec 31, 2023 | 5.32 Mn |
| Sep 30, 2023 | 5.35 Mn |
| Jun 30, 2023 | 5.36 Mn |
| Mar 31, 2023 | 5.17 Mn |
| Dec 31, 2022 | 4.41 Mn |
| Sep 30, 2022 | 4.66 Mn |
| Jun 30, 2022 | 4.45 Mn |
| Mar 31, 2022 | 4.31 Mn |
| Dec 31, 2021 | 4.07 Mn |
| Sep 30, 2021 | 4.14 Mn |
API Access
Atomera 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=ATOM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "ATOM", "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=ATOM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();