Wipro (WIT) EBITDA (2009 - 2026)
Wipro (WIT) recorded EBITDA of $499.09 million in the quarter ended Jun 30, 2026, up 0.3% from $497.52 million a year earlier but down 5.2% from the prior quarter.
Wipro (WIT) EBITDA (2009 - 2026) Analysis & Trends
On a TTM basis, Wipro's EBITDA came in at $2.03 billion as of Jun 30, 2026, down 4.4% year-over-year; for the year ended Mar 31, 2026, it was $1.92 billion, down 9.0% from the prior year.
- Annual EBITDA has a five-year compound annual growth rate of -1.4% (years ended Mar 2021 to Mar 2026).
- Across earlier years, EBITDA came in at $2.11 billion in the year ended Mar 31, 2025 (+3.4%), $2.04 billion in the year ended Mar 31, 2024 (-2.9%), $2.11 billion in the year ended Mar 31, 2023 (-6.7%) and $2.26 billion in the year ended Mar 31, 2022 (+9.5%).
- Quarterly EBITDA has ranged from $491.68 million in the quarter ended Dec 31, 2025 to $2.96 billion in the quarter ended Dec 31, 2022 over the past five years.
- On a year-over-year basis, EBITDA rose in four of the last eight quarters, with an average decline of 0.7%.
- Peak year-over-year performance for EBITDA in the last five years was growth of 420.0% in the quarter ended Mar 31, 2023, against a decline of 82.9% in the quarter ended Dec 31, 2023 at the low end.
- Per Business Quant, the preceding three quarters came in at $526.69 million (quarter ended Mar 31, 2026), $491.68 million (quarter ended Dec 31, 2025) and $513 million (quarter ended Sep 30, 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Infosys | 50.24 Bn | 36.74 Bn | 1.60 Bn | 13.55 Bn |
| 2 | Cognizant Technology Solutions | 31.12 Bn | 24.28 Bn | 1.83 Bn | 1.02 Bn |
| 3 | Wipro | 20.11 Bn | 14.81 Bn | 738.00 Mn | 498.97 Mn |
| 4 | Td Synnex | 19.66 Bn | 13.82 Bn | 1.43 Bn | 749.12 Mn |
| 5 | Cdw | 19.39 Bn | 17.38 Bn | 1.32 Bn | 503.70 Mn |
| 6 | Cgi | 16.87 Bn | 14.67 Bn | - | 591.24 Mn |
| 7 | Arrow Electronics | 11.10 Bn | 10.05 Bn | 1.13 Bn | 412.93 Mn |
| 8 | Avnet | 7.54 Bn | 6.72 Bn | 865.03 Mn | 268.27 Mn |
| 9 | EPAM Systems | 6.64 Bn | 2.28 Bn | 429.57 Mn | 184.32 Mn |
| 10 | Ingram Micro Holding | 6.19 Bn | 1.79 Bn | 958.68 Mn | 285.25 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 498.97 Mn |
| Mar 31, 2026 | 526.69 Mn |
| Dec 31, 2025 | 488.40 Mn |
| Sep 30, 2025 | 506.30 Mn |
| Jun 30, 2025 | 497.52 Mn |
| Mar 31, 2025 | 541.34 Mn |
| Dec 31, 2024 | 541.62 Mn |
| Sep 30, 2024 | 543.19 Mn |
| Jun 30, 2024 | 519.38 Mn |
| Mar 31, 2024 | 527.15 Mn |
| Dec 31, 2023 | 506.59 Mn |
| Sep 30, 2023 | 511.88 Mn |
| Jun 30, 2023 | 509.94 Mn |
| Mar 31, 2023 | 2.94 Bn |
| Dec 31, 2022 | 2.96 Bn |
| Sep 30, 2022 | 507.63 Mn |
| Jun 30, 2022 | 513.91 Mn |
| Mar 31, 2022 | 564.63 Mn |
| Dec 31, 2021 | 573.82 Mn |
| Sep 30, 2021 | 575.44 Mn |
Wipro EBITDA 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=ebitda&ticker=WIT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "ticker": "WIT", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=ebitda&ticker=WIT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();