Nova (NVMI) EPS (Diluted) (2009 - 2026)
Nova's EPS (Diluted) was $2.29 in the quarter ended Jun 30, 2026, up 7.6% from $2.12 a year earlier and up 8.3% from the prior quarter.
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Analysis
Nova (NVMI) EPS (Diluted) (2009 - 2026) Analysis & Trends
On a trailing twelve-month basis, Nova's EPS (Diluted) was $8.24 through Jun 30, 2026, up 12.8% year-over-year; for the year ended Dec 31, 2025, it was $7.90, up 38.2% from the prior year.
- EPS (Diluted) shows a five-year compound annual growth rate of 36.7% (years ended Dec 2020 to Dec 2025).
- In earlier years, EPS (Diluted) was $5.72 in the year ended Dec 31, 2024 (+34.6%), $4.25 in the year ended Dec 31, 2023 (-3.4%), $4.40 in the year ended Dec 31, 2022 (+40.9%) and $3.12 in the year ended Dec 31, 2021 (+88.7%).
- The figure for the quarter ended Jun 30, 2026 marks the highest quarterly EPS (Diluted) in data going back to the quarter ended Dec 31, 2009.
- Compared with a year earlier, EPS (Diluted) has increased for 11 straight quarters, with growth averaging 33.5% over the last eight quarters.
- The best year-over-year quarter for EPS (Diluted) over five years was the quarter ended Sep 30, 2021 (growth of 115.5%); the worst was the quarter ended Jun 30, 2023 (a decline of 19.7%).
- Per Business Quant data, NVMI's EPS (Diluted) in the three quarters before the quarter ended Jun 30, 2026 was $2.11 (quarter ended Mar 31, 2026), $1.97 (quarter ended Dec 31, 2025) and $1.91 (quarter ended Sep 30, 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EPS (Diluted) (Qtr) |
|---|---|---|---|---|---|
| 1 | Nvidia | 5,257.94 Bn | 5,032.10 Bn | 72.14 Bn | 2.46 |
| 2 | Taiwan Semiconductor Manufacturing | 2,182.39 Bn | 1,807.25 Bn | 27.22 Bn | 4.31 |
| 3 | Broadcom | 1,596.71 Bn | 1,522.75 Bn | 20.46 Bn | 2.68 |
| 4 | Micron Technology | 1,020.41 Bn | 926.05 Bn | 47.05 Bn | 32.98 |
| 5 | Advanced Micro Devices | 879.62 Bn | 836.36 Bn | 6.20 Bn | 1.38 |
| 6 | Asml Holding | 640.55 Bn | 596.23 Bn | 5.90 Bn | 8.50 |
| 7 | Intel | 470.49 Bn | 339.62 Bn | 6.51 Bn | -2.16 |
| 8 | Lam Research | 342.11 Bn | 318.91 Bn | 3.48 Bn | 1.81 |
| 9 | Applied Materials | 328.25 Bn | 293.69 Bn | 4.59 Bn | 3.17 |
| 10 | Nova | 9.62 Bn | 6.78 Bn | 144.16 Mn | 2.29 |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 2.29 |
| Mar 31, 2026 | 2.11 |
| Dec 31, 2025 | 1.97 |
| Sep 30, 2025 | 1.91 |
| Jun 30, 2025 | 2.12 |
| Mar 31, 2025 | 2.02 |
| Dec 31, 2024 | 1.57 |
| Sep 30, 2024 | 1.60 |
| Jun 30, 2024 | 1.41 |
| Mar 31, 2024 | 1.15 |
| Dec 31, 2023 | 1.19 |
| Sep 30, 2023 | 1.06 |
| Jun 30, 2023 | 0.94 |
| Mar 31, 2023 | 1.09 |
| Dec 31, 2022 | 1.13 |
| Sep 30, 2022 | 1.18 |
| Jun 30, 2022 | 1.17 |
| Mar 31, 2022 | 1.15 |
| Dec 31, 2021 | 0.75 |
| Sep 30, 2021 | 1.05 |
API Access
Nova EPS (Diluted) 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=eps-diluted&ticker=NVMI&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "eps-diluted", "ticker": "NVMI", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=eps-diluted&ticker=NVMI&period=max&api_key=YOUR_API_KEY");
const data = await res.json();