Lyft (LYFT) Other Operating Expenses (2018 - 2026)
Lyft's Other Operating Expenses was $1.38 billion in Q2 2026, up 10.5% from $1.24 billion a year earlier and up 9.0% from the prior quarter.
Powered by 
Analysis
Lyft (LYFT) Other Operating Expenses (2018 - 2026) Analysis & Trends
On a trailing twelve-month basis, Lyft's Other Operating Expenses was $5.29 billion through Jun 30, 2026, up 9.1% year-over-year; for FY2025, it was $5.05 billion, up 10.5% from FY2024.
- Other Operating Expenses has now increased for five consecutive years, with a five-year compound annual growth rate of 16.9% (FY2020 to FY2025).
- In earlier years, Other Operating Expenses was $4.57 billion in FY2024 (+32.4%), $3.45 billion in FY2023 (+1.2%), $3.41 billion in FY2022 (+35.6%) and $2.52 billion in FY2021 (+8.5%).
- The Q2 2026 figure marks the highest quarterly Other Operating Expenses in data going back to Q1 2018.
- Compared with a year earlier, Other Operating Expenses has increased for ten straight quarters, with growth averaging 15.8% over the last eight quarters.
- The best year-over-year quarter for Other Operating Expenses over five years was Q2 2022 (growth of 65.8%); the worst was Q2 2023 (a decline of 8.1%).
- Per Business Quant data, LYFT's Other Operating Expenses in the three quarters before Q2 2026 was $1.26 billion (Q1 2026), $1.35 billion (Q4 2025) and $1.3 billion (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Alphabet | 4,164.76 Bn | 3,922.28 Bn | 73.85 Bn |
| 2 | Meta Platforms | 1,823.40 Bn | 1,525.92 Bn | 49.47 Bn |
| 3 | Netflix | 288.27 Bn | 248.47 Bn | 6.52 Bn |
| 4 | Alibaba Group Holding | 252.72 Bn | 70.58 Bn | 15.11 Bn |
| 5 | Shopify | 186.52 Bn | 163.71 Bn | 1.71 Bn |
| 6 | Uber Technologies | 139.11 Bn | 111.09 Bn | 6.38 Bn |
| 7 | Booking Holdings | 123.13 Bn | 56.18 Bn | - |
| 8 | PDD Holdings | 111.72 Bn | -140.21 Bn | 9.45 Bn |
| 9 | AppLovin | 103.35 Bn | 93.38 Bn | 1.70 Bn |
| 10 | Lyft | 5.63 Bn | -1.71 Bn | 917.12 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.38 Bn |
| Mar 31, 2026 | 1.26 Bn |
| Dec 31, 2025 | 1.35 Bn |
| Sep 30, 2025 | 1.30 Bn |
| Jun 30, 2025 | 1.24 Bn |
| Mar 31, 2025 | 1.15 Bn |
| Dec 31, 2024 | 1.23 Bn |
| Sep 30, 2024 | 1.22 Bn |
| Jun 30, 2024 | 1.11 Bn |
| Mar 31, 2024 | 1.00 Bn |
| Dec 31, 2023 | 971.71 Mn |
| Sep 30, 2023 | 893.21 Mn |
| Jun 30, 2023 | 823.42 Mn |
| Mar 31, 2023 | 763.86 Mn |
| Dec 31, 2022 | 1.03 Bn |
| Sep 30, 2022 | 823.65 Mn |
| Jun 30, 2022 | 896.42 Mn |
| Mar 31, 2022 | 665.22 Mn |
| Dec 31, 2021 | 784.94 Mn |
| Sep 30, 2021 | 610.84 Mn |
API Access
Lyft Other 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=other-operating-expenses&ticker=LYFT&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-operating-expenses", "ticker": "LYFT", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=other-operating-expenses&ticker=LYFT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();