Vital Farms (VITL) Total Liabilities (2019 - 2026)
Vital Farms (VITL) recorded Total Liabilities of $218.43 million in Q2 2026, up 80.6% from $120.97 million a year earlier and up 35.1% from the prior quarter.
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Analysis
Vital Farms (VITL) Total Liabilities (2019 - 2026) Analysis & Trends
At the end of FY2025, Vital Farms reported Total Liabilities of $167.48 million, up 86.0% from FY2024.
- Annual Total Liabilities has increased for five straight years, with a five-year compound annual growth rate of 41.8% (FY2020 to FY2025).
- Across earlier years, Total Liabilities came in at $90.03 million in FY2024 (+9.1%), $82.5 million in FY2023 (+46.4%), $56.33 million in FY2022 (+46.9%) and $38.36 million in FY2021 (+31.5%).
- The Q2 2026 figure is the highest quarterly Total Liabilities in data going back to Q4 2019.
- On a year-over-year basis, Total Liabilities has increased for 19 consecutive quarters, with growth averaging 51.1% over the last eight quarters.
- Peak year-over-year performance for Total Liabilities in the last five years was growth of 86.0% in Q4 2025, against a decline of 6.2% in Q3 2021 at the low end.
- Per Business Quant, the preceding three quarters came in at $161.74 million (Q1 2026), $167.48 million (Q4 2025) and $150.29 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Unilever | 136.33 Bn | 111.70 Bn | - | 68.14 Bn |
| 2 | Mondelez International | 76.81 Bn | 70.13 Bn | 3.99 Bn | 44.56 Bn |
| 3 | Hershey | 33.25 Bn | 29.49 Bn | 1.26 Bn | 9.41 Bn |
| 4 | Kraft Heinz | 27.93 Bn | 14.46 Bn | 2.03 Bn | 36.95 Bn |
| 5 | General Mills | 17.97 Bn | 15.62 Bn | 1.49 Bn | 22.81 Bn |
| 6 | Mccormick | 13.05 Bn | 12.93 Bn | 778.20 Mn | 8.90 Bn |
| 7 | J M Smucker | 12.89 Bn | 12.67 Bn | 979.60 Mn | 10.45 Bn |
| 8 | Hormel Foods | 10.99 Bn | 7.67 Bn | 471.52 Mn | 5.43 Bn |
| 9 | Chewy | 7.48 Bn | 4.77 Bn | 1.01 Bn | 3.37 Bn |
| 10 | Vital Farms | 415.11 Mn | 214.62 Mn | 10.93 Mn | 218.43 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 28, 2026 | 218.43 Mn |
| Mar 29, 2026 | 161.74 Mn |
| Dec 28, 2025 | 167.48 Mn |
| Sep 28, 2025 | 150.29 Mn |
| Jun 29, 2025 | 120.97 Mn |
| Mar 30, 2025 | 87.98 Mn |
| Dec 29, 2024 | 90.03 Mn |
| Sep 29, 2024 | 91.31 Mn |
| Jun 30, 2024 | 82.07 Mn |
| Mar 31, 2024 | 86.85 Mn |
| Dec 31, 2023 | 82.50 Mn |
| Sep 24, 2023 | 67.16 Mn |
| Jun 25, 2023 | 60.28 Mn |
| Mar 26, 2023 | 59.25 Mn |
| Dec 25, 2022 | 56.33 Mn |
| Sep 25, 2022 | 52.03 Mn |
| Jun 26, 2022 | 47.79 Mn |
| Mar 27, 2022 | 40.45 Mn |
| Dec 26, 2021 | 38.36 Mn |
| Sep 26, 2021 | 33.53 Mn |
API Access
Vital Farms Total Liabilities 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=total-liabilities&ticker=VITL&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "VITL", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=total-liabilities&ticker=VITL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();