Figs (FIGS) EBITDA (2020 - 2026)
Figs (FIGS) posted EBITDA of $37.63 million for Q2 2026, up 211.8% from $12.07 million a year earlier and up 376.7% from the prior quarter.
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Analysis
Figs (FIGS) EBITDA (2020 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, EBITDA at Figs was $78.85 million, up 318.1% year-over-year; for FY2025, it was $47.18 million, up 426.6% from FY2024.
- Annual EBITDA shows a five-year compound annual growth rate of -4.3% (FY2020 to FY2025).
- In prior years, Figs' EBITDA was $8.96 million in FY2024 (-75.8%), $36.99 million in FY2023 (-6.6%), $39.59 million in FY2022 (+219.1%) and $12.41 million in FY2021 (-78.9%).
- The Q2 2026 figure stands as the highest quarterly EBITDA in data going back to Q3 2020.
- On a year-over-year basis, EBITDA has increased in each of the last three quarters, with growth averaging 169.1% over the last six quarters.
- The strongest year-over-year quarter for EBITDA in the past five years was Q2 2025, with growth of 352.7%; the weakest was Q4 2022, with a decline of 76.9%.
- According to Business Quant data, EBITDA for the three prior quarters was $7.89 million (Q1 2026), $21.37 million (Q4 2025) and $11.96 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Nike | 56.23 Bn | 22.43 Bn | 4.80 Bn | 1.08 Bn |
| 2 | Tapestry | 23.69 Bn | 19.65 Bn | 1.56 Bn | 500.90 Mn |
| 3 | Ralph Lauren | 22.48 Bn | 14.58 Bn | 1.44 Bn | 401.30 Mn |
| 4 | Deckers Outdoor | 12.63 Bn | 5.50 Bn | - | - |
| 5 | Lululemon Athletica | 11.17 Bn | 5.42 Bn | 1.46 Bn | 595.99 Mn |
| 6 | Levi Strauss | 7.99 Bn | 4.58 Bn | 1.07 Bn | 277.10 Mn |
| 7 | V F | 6.76 Bn | 3.38 Bn | 917.04 Mn | -25.29 Mn |
| 8 | Gildan Activewear | 6.57 Bn | 5.49 Bn | 459.76 Mn | 244.22 Mn |
| 9 | Birkenstock Holding | 6.14 Bn | 4.46 Bn | 493.89 Mn | 326.23 Mn |
| 10 | Figs | 3.31 Bn | 2.19 Bn | 147.86 Mn | 37.63 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 37.63 Mn |
| Mar 31, 2026 | 7.89 Mn |
| Dec 31, 2025 | 21.37 Mn |
| Sep 30, 2025 | 11.96 Mn |
| Jun 30, 2025 | 12.07 Mn |
| Mar 31, 2025 | 1.79 Mn |
| Dec 31, 2024 | 10.75 Mn |
| Sep 30, 2024 | -5.74 Mn |
| Jun 30, 2024 | 2.67 Mn |
| Mar 31, 2024 | 1.29 Mn |
| Dec 31, 2023 | 15.04 Mn |
| Sep 30, 2023 | 10.71 Mn |
| Jun 30, 2023 | 7.28 Mn |
| Mar 31, 2023 | 3.96 Mn |
| Dec 31, 2022 | 3.90 Mn |
| Sep 30, 2022 | 11.69 Mn |
| Jun 30, 2022 | 9.88 Mn |
| Mar 31, 2022 | 14.12 Mn |
| Dec 31, 2021 | 16.84 Mn |
| Sep 30, 2021 | 10.91 Mn |
API Access
Figs 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=FIGS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "ticker": "FIGS", "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=FIGS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();