Vivid Seats (SEAT) Operating Expenses (2020 - 2026)
Vivid Seats (SEAT) reported Operating Expenses of $136.3 million for Q2 2026, down 71.3% from $475.29 million a year earlier but up 1.3% from the prior quarter.
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Analysis
Vivid Seats (SEAT) Operating Expenses (2020 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Vivid Seats' Operating Expenses came in at $977.53 million, down 3.8% year-over-year; for FY2025, it came in at $1.35 billion, up 84.1% from FY2024.
- Operating Expenses has increased for five consecutive years, with a five-year compound annual growth rate of 82.4% (FY2020 to FY2025).
- By year, Operating Expenses came in at $733.36 million in FY2024 (+16.1%), $631.54 million in FY2023 (+20.9%), $522.17 million in FY2022 (+465.9%) and $92.27 million in FY2021 (+38.1%).
- Five-year quarterly Operating Expenses spans a low of $4.68 million in Q4 2021 and a high of $547.44 million in Q4 2025.
- Year over year, Operating Expenses gained in four of the last eight quarters, with growth averaging 110.4%.
- The high point for year-over-year Operating Expenses in five years was Q4 2022 (growth of 581.0%); the low point was Q2 2026 (a decline of 71.3%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $134.57 million (Q1 2026), $547.44 million (Q4 2025) and $159.22 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Alphabet | 4,056.92 Bn | 3,814.44 Bn | 73.85 Bn | 79.03 Bn |
| 2 | Meta Platforms | 1,810.97 Bn | 1,513.49 Bn | 49.47 Bn | 42.03 Bn |
| 3 | Netflix | 274.15 Bn | 234.34 Bn | 6.52 Bn | 1.51 Bn |
| 4 | Alibaba Group Holding | 243.05 Bn | 56.82 Bn | 15.11 Bn | -5.17 Bn |
| 5 | Shopify | 230.06 Bn | 207.24 Bn | 1.71 Bn | 1.22 Bn |
| 6 | Uber Technologies | 139.17 Bn | 110.97 Bn | 6.38 Bn | 12.30 Bn |
| 7 | Booking Holdings | 121.90 Bn | 54.95 Bn | - | 4.85 Bn |
| 8 | PDD Holdings | 110.14 Bn | -133.63 Bn | 9.45 Bn | -5.39 Bn |
| 9 | Spotify Technology | 108.32 Bn | 65.82 Bn | 1.86 Bn | 640.46 Mn |
| 10 | Vivid Seats | 31.16 Mn | -499.60 Mn | 91.22 Mn | 136.30 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 136.30 Mn |
| Mar 31, 2026 | 134.57 Mn |
| Dec 31, 2025 | 547.44 Mn |
| Sep 30, 2025 | 159.22 Mn |
| Jun 30, 2025 | 475.29 Mn |
| Mar 31, 2025 | 168.34 Mn |
| Dec 31, 2024 | 196.91 Mn |
| Sep 30, 2024 | 175.84 Mn |
| Jun 30, 2024 | 190.43 Mn |
| Mar 31, 2024 | 170.18 Mn |
| Dec 31, 2023 | 51.16 Mn |
| Sep 30, 2023 | 37.23 Mn |
| Jun 30, 2023 | 38.31 Mn |
| Mar 31, 2023 | 32.39 Mn |
| Dec 31, 2022 | 31.90 Mn |
| Sep 30, 2022 | 30.24 Mn |
| Jun 30, 2022 | 36.21 Mn |
| Mar 31, 2022 | 29.28 Mn |
| Dec 31, 2021 | 4.68 Mn |
| Sep 30, 2021 | 42.51 Mn |
API Access
Vivid Seats Operating Expenses 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=operating-expenses&ticker=SEAT&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "SEAT", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=SEAT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();