Axcelis Technologies (ACLS) Operating Expenses (2010 - 2026)
Axcelis Technologies (ACLS) reported Operating Expenses of $70.91 million for Q2 2026, up 21.5% from $58.38 million a year earlier but down 2.4% from the prior quarter.
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Analysis
Axcelis Technologies (ACLS) Operating Expenses (2010 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Axcelis Technologies' Operating Expenses came in at $283.09 million, up 16.6% year-over-year; for FY2025, it came in at $257.53 million, up 5.6% from FY2024.
- Operating Expenses has increased for 11 consecutive years, with a five-year compound annual growth rate of 12.9% (FY2020 to FY2025).
- By year, Operating Expenses came in at $243.86 million in FY2024 (+8.1%), $225.51 million in FY2023 (+19.0%), $189.43 million in FY2022 (+19.0%) and $159.12 million in FY2021 (+13.2%).
- Five-year quarterly Operating Expenses spans a low of $40.12 million in Q3 2021 and a high of $75.76 million in Q4 2025.
- Year over year, Operating Expenses has now increased in each of the last four quarters, with growth averaging 9.9% over the last eight quarters.
- The high point for year-over-year Operating Expenses in five years was Q1 2023 (growth of 28.9%); the low point was Q2 2025 (a decline of 2.0%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $72.63 million (Q1 2026), $75.76 million (Q4 2025) and $63.79 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Nvidia | 5,757.49 Bn | 5,531.65 Bn | 72.14 Bn | 8.41 Bn |
| 2 | Taiwan Semiconductor Manufacturing | 2,520.17 Bn | 2,145.88 Bn | 27.22 Bn | 3.13 Bn |
| 3 | Broadcom | 1,730.62 Bn | 1,656.67 Bn | 20.46 Bn | 4.50 Bn |
| 4 | Micron Technology | 1,201.21 Bn | 1,139.97 Bn | 35.06 Bn | 1.72 Bn |
| 5 | Advanced Micro Devices | 1,031.02 Bn | 987.76 Bn | 6.20 Bn | 4.21 Bn |
| 6 | Asml Holding | 716.82 Bn | 672.66 Bn | 5.90 Bn | - |
| 7 | Intel | 585.95 Bn | 470.68 Bn | 6.51 Bn | 4.71 Bn |
| 8 | Lam Research | 432.69 Bn | 409.49 Bn | 3.48 Bn | 965.25 Mn |
| 9 | Applied Materials | 430.35 Bn | 395.79 Bn | 4.59 Bn | 1.51 Bn |
| 10 | Axcelis Technologies | 4.39 Bn | 2.80 Bn | 91.19 Mn | 70.91 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 70.91 Mn |
| Mar 31, 2026 | 72.63 Mn |
| Dec 31, 2025 | 75.76 Mn |
| Sep 30, 2025 | 63.79 Mn |
| Jun 30, 2025 | 58.38 Mn |
| Mar 31, 2025 | 59.61 Mn |
| Dec 31, 2024 | 61.69 Mn |
| Sep 30, 2024 | 63.06 Mn |
| Jun 30, 2024 | 59.60 Mn |
| Mar 31, 2024 | 59.51 Mn |
| Dec 31, 2023 | 58.85 Mn |
| Sep 30, 2023 | 58.00 Mn |
| Jun 30, 2023 | 56.00 Mn |
| Mar 31, 2023 | 52.66 Mn |
| Dec 31, 2022 | 53.43 Mn |
| Sep 30, 2022 | 50.12 Mn |
| Jun 30, 2022 | 45.04 Mn |
| Mar 31, 2022 | 40.84 Mn |
| Dec 31, 2021 | 42.90 Mn |
| Sep 30, 2021 | 40.12 Mn |
API Access
Axcelis Technologies 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=ACLS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "ACLS", "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=ACLS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();