Netflix (NFLX) Operating Expenses (2009 - 2026)
Netflix (NFLX) recorded Operating Expenses of $1.51 billion in Q2 2026, up 19.0% from $1.27 billion a year earlier but down 3.6% from the prior quarter.
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Analysis
Netflix (NFLX) Operating Expenses (2009 - 2026) Analysis & Trends
On a TTM basis, Netflix's Operating Expenses came in at $5.84 billion as of Jun 30, 2026, up 19.3% year-over-year; for FY2025, it came in at $5.28 billion, up 14.1% from FY2024.
- Annual Operating Expenses has increased for 13 straight years, with a five-year compound annual growth rate of 12.7% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $4.63 billion in FY2024 (+5.3%), $4.4 billion in FY2023 (+2.6%), $4.28 billion in FY2022 (+18.2%) and $3.63 billion in FY2021 (+24.8%).
- Quarterly Operating Expenses has ranged from $885.68 million in Q3 2021 to $1.56 billion in Q1 2026 over the past five years.
- On a year-over-year basis, Operating Expenses has increased for 12 consecutive quarters, with growth averaging 14.1% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 37.1% in Q4 2021, against a decline of 5.9% in Q2 2023 at the low end.
- Per Business Quant, the preceding three quarters came in at $1.56 billion (Q1 2026), $1.46 billion (Q4 2025) and $1.31 billion (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Alphabet | 4,164.76 Bn | 3,922.28 Bn | 73.85 Bn | 79.03 Bn |
| 2 | Meta Platforms | 1,823.40 Bn | 1,525.92 Bn | 49.47 Bn | 42.03 Bn |
| 3 | Netflix | 288.27 Bn | 248.47 Bn | 6.52 Bn | 1.51 Bn |
| 4 | Alibaba Group Holding | 252.72 Bn | 70.58 Bn | 15.11 Bn | -5.17 Bn |
| 5 | Shopify | 186.52 Bn | 163.71 Bn | 1.71 Bn | 1.22 Bn |
| 6 | Uber Technologies | 139.11 Bn | 111.09 Bn | 6.38 Bn | 12.30 Bn |
| 7 | Booking Holdings | 123.13 Bn | 56.18 Bn | - | 4.85 Bn |
| 8 | PDD Holdings | 111.72 Bn | -140.21 Bn | 9.45 Bn | -5.39 Bn |
| 9 | AppLovin | 103.35 Bn | 93.38 Bn | 1.70 Bn | 429.41 Mn |
| 10 | Spotify Technology | 102.35 Bn | 59.59 Bn | 1.86 Bn | 640.46 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.51 Bn |
| Mar 31, 2026 | 1.56 Bn |
| Dec 31, 2025 | 1.46 Bn |
| Sep 30, 2025 | 1.31 Bn |
| Jun 30, 2025 | 1.27 Bn |
| Mar 31, 2025 | 1.24 Bn |
| Dec 31, 2024 | 1.23 Bn |
| Sep 30, 2024 | 1.15 Bn |
| Jun 30, 2024 | 1.14 Bn |
| Mar 31, 2024 | 1.11 Bn |
| Dec 31, 2023 | 1.11 Bn |
| Sep 30, 2023 | 1.14 Bn |
| Jun 30, 2023 | 1.06 Bn |
| Mar 31, 2023 | 1.09 Bn |
| Dec 31, 2022 | 1.07 Bn |
| Sep 30, 2022 | 1.04 Bn |
| Jun 30, 2022 | 1.13 Bn |
| Mar 31, 2022 | 1.06 Bn |
| Dec 31, 2021 | 1.05 Bn |
| Sep 30, 2021 | 885.68 Mn |
API Access
Netflix 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=NFLX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "NFLX", "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=NFLX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();