GE Vernova (GEV) EPS (Diluted) (2023 - 2026)
GE Vernova's EPS (Diluted) was $2.47 in Q2 2026, up 32.8% from $1.86 a year earlier but down 85.8% from the prior quarter.
GE Vernova (GEV) EPS (Diluted) (2023 - 2026) Analysis & Trends
On a trailing twelve-month basis, GE Vernova's EPS (Diluted) was $35.29 through Jun 30, 2026, up 742.6% year-over-year; for FY2025, it was $17.70, up 217.0% from FY2024.
- In earlier years, EPS (Diluted) was $5.58 in FY2024, -$1.60 in FY2023 and -$9.99 in FY2022.
- Quarterly EPS (Diluted) has moved between -$1.15 (Q1 2023) and $17.44 (Q1 2026) over five years.
- Compared with a year earlier, EPS (Diluted) was higher in three of the last four quarters, with growth averaging 194.4%.
- Per Business Quant data, GEV's EPS (Diluted) in the three quarters before Q2 2026 was $17.44 (Q1 2026), $13.28 (Q4 2025) and $1.64 (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EPS (Diluted) (Qtr) |
|---|---|---|---|---|---|
| 1 | GE Vernova | 256.40 Bn | 217.48 Bn | 2.36 Bn | 2.47 |
| 2 | Bloom Energy | 85.45 Bn | 77.27 Bn | 355.57 Mn | 0.61 |
| 3 | First Solar | 19.01 Bn | 9.97 Bn | 605.00 Mn | 3.92 |
| 4 | BWX Technologies | 12.64 Bn | 10.94 Bn | 202.31 Mn | 0.97 |
| 5 | Generac Holdings | 12.53 Bn | 11.36 Bn | 521.81 Mn | 2.40 |
| 6 | Nextpower | 12.03 Bn | 7.92 Bn | 335.85 Mn | 1.07 |
| 7 | EnerSys | 6.62 Bn | 4.81 Bn | 313.36 Mn | 3.09 |
| 8 | Enphase Energy | 4.21 Bn | -653.40 Mn | 175.01 Mn | 0.27 |
| 9 | Mirion Technologies | 3.51 Bn | 1.39 Bn | 133.10 Mn | 0.03 |
| 10 | Nuscale Power | 3.18 Bn | 3.14 Bn | -152,000.00 | -0.13 |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 2.47 |
| Mar 31, 2026 | 17.44 |
| Dec 31, 2025 | 13.28 |
| Sep 30, 2025 | 1.64 |
| Jun 30, 2025 | 1.86 |
| Mar 31, 2025 | 0.91 |
| Dec 31, 2024 | 1.74 |
| Sep 30, 2024 | -0.35 |
| Jun 30, 2024 | 4.65 |
| Mar 31, 2024 | -0.47 |
| Dec 31, 2023 | 0.72 |
| Sep 30, 2023 | -0.62 |
| Jun 30, 2023 | -0.55 |
| Mar 31, 2023 | -1.15 |
GE Vernova 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=GEV&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "eps-diluted", "ticker": "GEV", "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=GEV&period=max&api_key=YOUR_API_KEY");
const data = await res.json();