Infosys (INFY) EPS (Diluted) (2011 - 2026)
Infosys (INFY) reported EPS (Diluted) of $0.20 for the quarter ended Jun 30, 2026, up 2.3% from $0.19 a year earlier but down 10.7% from the prior quarter.
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Analysis
Infosys (INFY) EPS (Diluted) (2011 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Infosys' EPS (Diluted) came in at $0.81, up 6.0% year-over-year; for the year ended Mar 31, 2026, it came in at $1.06, up 42.9% from the prior year.
- EPS (Diluted) has a five-year compound annual growth rate of 11.5% (years ended Mar 2021 to Mar 2026).
- By year, EPS (Diluted) came in at $0.74 in the year ended Mar 31, 2025 (-2.5%), $0.76 in the year ended Mar 31, 2024 (+8.8%), $0.70 in the year ended Mar 31, 2023 (-0.5%) and $0.70 in the year ended Mar 31, 2022 (+14.0%).
- Five-year quarterly EPS (Diluted) spans a low of $0.16 in the quarter ended Jun 30, 2022 and a high of $13.70 in the quarter ended Dec 31, 2021.
- Year over year, EPS (Diluted) gained in six of the last eight quarters, with growth averaging 3.9%.
- The high point for year-over-year EPS (Diluted) in five years was the quarter ended Mar 31, 2024 (growth of 30.0%); the low point was the quarter ended Dec 31, 2022 (a decline of 98.6%).
- Per Business Quant data, the three quarters before the quarter ended Jun 30, 2026 came in at $0.22 (quarter ended Mar 31, 2026), $0.18 (quarter ended Dec 31, 2025) and $0.20 (quarter ended Sep 30, 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EPS (Diluted) (Qtr) |
|---|---|---|---|---|---|
| 1 | Infosys | 53.61 Bn | 40.11 Bn | 1.60 Bn | 18.86 |
| 2 | Cognizant Technology Solutions | 33.57 Bn | 26.73 Bn | 1.83 Bn | 1.36 |
| 3 | Wipro | 22.73 Bn | 17.88 Bn | 745.00 Mn | 0.03 |
| 4 | Cdw | 20.26 Bn | 18.25 Bn | 1.32 Bn | 2.15 |
| 5 | Td Synnex | 19.43 Bn | 13.59 Bn | 1.43 Bn | 5.24 |
| 6 | Cgi | 18.11 Bn | 15.91 Bn | - | 1.49 |
| 7 | Arrow Electronics | 10.73 Bn | 9.68 Bn | 1.13 Bn | 5.26 |
| 8 | Avnet | 7.28 Bn | 6.46 Bn | 865.03 Mn | 1.52 |
| 9 | EPAM Systems | 7.14 Bn | 2.78 Bn | 429.57 Mn | 1.97 |
| 10 | ExlService Holdings | 6.51 Bn | 5.26 Bn | 225.96 Mn | 0.42 |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 18.86 |
| Mar 31, 2026 | 20.63 |
| Dec 31, 2025 | 16.03 |
| Sep 30, 2025 | 17.74 |
| Jun 30, 2025 | 0.19 |
| Mar 31, 2025 | 0.20 |
| Dec 31, 2024 | 16.42 |
| Sep 30, 2024 | 0.19 |
| Jun 30, 2024 | 0.18 |
| Mar 31, 2024 | 0.23 |
| Dec 31, 2023 | 14.58 |
| Sep 30, 2023 | 0.18 |
| Jun 30, 2023 | 0.17 |
| Mar 31, 2023 | 14.63 |
| Dec 31, 2022 | 15.61 |
| Sep 30, 2022 | 0.18 |
| Jun 30, 2022 | 0.16 |
| Mar 31, 2022 | 0.18 |
| Dec 31, 2021 | 0.18 |
| Sep 30, 2021 | 0.17 |
API Access
Infosys 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=INFY&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "eps-diluted", "ticker": "INFY", "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=INFY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();