Walmart (WMT) EBITDA (2009 - 2026)
Walmart (WMT) recorded EBITDA of $13.31 billion in fiscal Q2 2027 (quarter ended Jul 31, 2026), up 23.5% from $10.77 billion a year earlier and up 17.6% from the prior quarter.
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Analysis
Walmart (WMT) EBITDA (2009 - 2026) Analysis & Trends
On a TTM basis, Walmart's EBITDA came in at $47.37 billion as of Jul 31, 2026, up 11.5% year-over-year; for FY2026 (ended Jan 31, 2026), it was $44.03 billion, up 4.0% from FY2025.
- Annual EBITDA has increased for three straight fiscal years, with a five-year compound annual growth rate of 5.5% (FY2021 to FY2026).
- Across earlier fiscal years, EBITDA came in at $42.35 billion in FY2025 (+8.8%), $38.91 billion in FY2024 (+24.0%), $31.37 billion in FY2023 (-14.4%) and $36.64 billion in FY2022 (+8.6%).
- The fiscal Q2 2027 figure is the highest quarterly EBITDA in data going back to fiscal Q4 2009.
- On a year-over-year basis, EBITDA has increased for four consecutive quarters, with growth averaging 8.0% over the last eight quarters.
- Peak year-over-year performance for EBITDA in the last five years was growth of 68.6% in fiscal Q3 2024, against a decline of 35.4% in fiscal Q3 2023 at the low end.
- Per Business Quant, the preceding three fiscal quarters came in at $11.31 billion (Q1 2027), $12.45 billion (Q4 2026) and $10.3 billion (Q3 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Walmart | 936.41 Bn | 892.84 Bn | 49.13 Bn | 13.31 Bn |
| 2 | Costco Wholesale | 440.73 Bn | 364.01 Bn | 12.19 Bn | 4.68 Bn |
| 3 | Sysco | 39.69 Bn | 33.94 Bn | 4.13 Bn | 1.27 Bn |
| 4 | Kroger | 38.21 Bn | 24.36 Bn | 7.86 Bn | 1.71 Bn |
| 5 | Dollar General | 29.54 Bn | 24.22 Bn | 3.68 Bn | 1.05 Bn |
| 6 | Caseys General Stores | 25.34 Bn | 23.33 Bn | 1.24 Bn | 601.59 Mn |
| 7 | Dollar Tree | 23.81 Bn | 20.43 Bn | 2.10 Bn | 869.90 Mn |
| 8 | US Foods Holding | 22.49 Bn | 22.29 Bn | 1.92 Bn | 561.00 Mn |
| 9 | Tractor Supply | 17.20 Bn | 16.37 Bn | 1.68 Bn | 597.96 Mn |
| 10 | Performance Food | 15.21 Bn | 14.99 Bn | 2.17 Bn | 540.10 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | 13.31 Bn |
| Apr 30, 2026 | 11.31 Bn |
| Jan 31, 2026 | 12.45 Bn |
| Oct 31, 2025 | 10.30 Bn |
| Jul 31, 2025 | 10.77 Bn |
| Apr 30, 2025 | 10.50 Bn |
| Jan 31, 2025 | 11.26 Bn |
| Oct 31, 2024 | 9.97 Bn |
| Jul 31, 2024 | 11.15 Bn |
| Apr 30, 2024 | 9.97 Bn |
| Jan 31, 2024 | 10.42 Bn |
| Oct 31, 2023 | 9.19 Bn |
| Jul 31, 2023 | 10.22 Bn |
| Apr 30, 2023 | 9.09 Bn |
| Jan 31, 2023 | 8.37 Bn |
| Oct 31, 2022 | 5.45 Bn |
| Jul 31, 2022 | 9.55 Bn |
| Apr 30, 2022 | 8.00 Bn |
| Jan 31, 2022 | 8.64 Bn |
| Oct 31, 2021 | 8.44 Bn |
API Access
Walmart 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=WMT&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "ticker": "WMT", "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=WMT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();