Vital Farms (VITL) Total Current Liabilities (2019 - 2026)
Vital Farms (VITL) recorded Total Current Liabilities of $147.58 million in Q2 2026, up 33.1% from $110.85 million a year earlier and up 24.6% from the prior quarter.
Vital Farms (VITL) Total Current Liabilities (2019 - 2026) Analysis & Trends
At the end of FY2025, Vital Farms reported Total Current Liabilities of $121.58 million, up 54.8% from FY2024.
- Annual Total Current Liabilities has increased for six straight years, with a five-year compound annual growth rate of 36.2% (FY2020 to FY2025).
- Across earlier years, Total Current Liabilities came in at $78.53 million in FY2024 (+20.4%), $65.22 million in FY2023 (+36.9%), $47.65 million in FY2022 (+25.4%) and $37.99 million in FY2021 (+46.6%).
- The Q2 2026 figure is the highest quarterly Total Current Liabilities in data going back to Q4 2019.
- On a year-over-year basis, Total Current Liabilities has increased for 21 consecutive quarters, with growth averaging 39.4% over the last eight quarters.
- Across the past five years, year-over-year growth in Total Current Liabilities ran from 4.2% in Q3 2023 to 71.1% in Q2 2022.
- Per Business Quant, the preceding three quarters came in at $118.42 million (Q1 2026), $121.58 million (Q4 2025) and $102.59 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Current Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Unilever | 136.33 Bn | 111.70 Bn | - | 33.58 Bn |
| 2 | Mondelez International | 76.81 Bn | 70.13 Bn | 3.99 Bn | 21.59 Bn |
| 3 | Hershey | 33.25 Bn | 29.49 Bn | 1.26 Bn | 3.35 Bn |
| 4 | Kraft Heinz | 27.93 Bn | 14.46 Bn | 2.03 Bn | 8.72 Bn |
| 5 | General Mills | 17.97 Bn | 15.62 Bn | 1.49 Bn | 6.94 Bn |
| 6 | Mccormick | 13.05 Bn | 12.93 Bn | 778.20 Mn | 3.57 Bn |
| 7 | J M Smucker | 12.89 Bn | 12.67 Bn | 979.60 Mn | 2.29 Bn |
| 8 | Hormel Foods | 10.99 Bn | 7.67 Bn | 471.52 Mn | 1.87 Bn |
| 9 | Chewy | 7.48 Bn | 4.77 Bn | 1.01 Bn | 2.20 Bn |
| 10 | Vital Farms | 415.11 Mn | 214.62 Mn | 10.93 Mn | 147.58 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 28, 2026 | 147.58 Mn |
| Mar 29, 2026 | 118.42 Mn |
| Dec 28, 2025 | 121.58 Mn |
| Sep 28, 2025 | 102.59 Mn |
| Jun 29, 2025 | 110.85 Mn |
| Mar 30, 2025 | 77.51 Mn |
| Dec 29, 2024 | 78.53 Mn |
| Sep 29, 2024 | 77.75 Mn |
| Jun 30, 2024 | 66.99 Mn |
| Mar 31, 2024 | 70.37 Mn |
| Dec 31, 2023 | 65.22 Mn |
| Sep 24, 2023 | 52.96 Mn |
| Jun 25, 2023 | 51.70 Mn |
| Mar 26, 2023 | 50.52 Mn |
| Dec 25, 2022 | 47.65 Mn |
| Sep 25, 2022 | 50.81 Mn |
| Jun 26, 2022 | 46.03 Mn |
| Mar 27, 2022 | 38.33 Mn |
| Dec 26, 2021 | 37.99 Mn |
| Sep 26, 2021 | 32.32 Mn |
Vital Farms Total Current 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-current-liabilities&ticker=VITL&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-current-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-current-liabilities&ticker=VITL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();