Snowflake (SNOW) Operating Expenses (2019 - 2026)
Snowflake's (SNOW) quarterly Operating Expenses came in at $1.3 billion in Q3 2026, up 16.73% year-over-year from $1.1 billion in Q3 2025, and up 3.76% quarter-over-quarter from $1.3 billion in Q2 2026.
Snowflake (SNOW) Operating Expenses (2019 - 2026) Analysis & Trends
Snowflake has disclosed Operating Expenses across 8 years of filings, most recently posting $1.3 billion for Q3 2026.
- In Q3 2026, Operating Expenses rose 16.73% year-over-year to $1.3 billion; the TTM figure through Jul 2026 stood at $4.9 billion (up 13.99% YoY), while the FY2026 annual figure was $4.6 billion, up 18.45% from the prior year.
- Operating Expenses came in at $1.3 billion for Q3 2026 at Snowflake, up from $1.3 billion in the prior quarter.
- In the past five years, Operating Expenses ranged from a high of $1.3 billion in Q3 2026 to a low of $401.6 million in Q1 2022.
- Average Operating Expenses over 5 years is $873.5 million, with a median of $904.8 million recorded in 2024.
- Year-over-year, Operating Expenses soared 55.15% in 2023 and advanced 9.83% in 2026.
- Over 5 years, Operating Expenses stood at $572.3 million in 2022, then jumped by 33.81% to $765.8 million in 2023, then gained by 28.83% to $986.7 million in 2024, then rose by 16.71% to $1.2 billion in 2025, then advanced by 12.87% to $1.3 billion in 2026.
- Per Business Quant data, the three most recent Operating Expenses figures were $1.3 billion in Q3 2026, $1.3 billion in Q2 2026, and $1.2 billion in Q1 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 320.54 Bn | 317.47 Bn | 2.30 Bn | 2.13 Bn |
| 2 | CrowdStrike Holdings | 268.77 Bn | 263.80 Bn | 1.10 Bn | 1.13 Bn |
| 3 | Fortinet | 131.12 Bn | 127.05 Bn | 1.64 Bn | 953.90 Mn |
| 4 | Snowflake | 118.02 Bn | 115.67 Bn | 1.04 Bn | 1.30 Bn |
| 5 | Datadog | 90.27 Bn | 85.29 Bn | 881.34 Mn | 875.89 Mn |
| 6 | Axon Enterprise | 36.61 Bn | 35.93 Bn | 546.45 Mn | 499.67 Mn |
| 7 | Zscaler | 34.97 Bn | 31.49 Bn | - | - |
| 8 | MongoDB | 34.51 Bn | 32.10 Bn | 569.77 Mn | 541.37 Mn |
| 9 | Okta | 34.32 Bn | 32.02 Bn | 641.00 Mn | 534.00 Mn |
| 10 | Baidu | 30.55 Bn | 8.15 Bn | 1.76 Mn | 4.17 Bn |
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | 1.30 Bn |
| Apr 30, 2026 | 1.25 Bn |
| Jan 31, 2026 | 1.18 Bn |
| Oct 31, 2025 | 1.15 Bn |
| Jul 31, 2025 | 1.11 Bn |
| Apr 30, 2025 | 1.14 Bn |
| Jan 31, 2025 | 1.04 Bn |
| Oct 31, 2024 | 986.66 Mn |
| Jul 31, 2024 | 936.05 Mn |
| Apr 30, 2024 | 904.76 Mn |
| Jan 31, 2024 | 808.40 Mn |
| Oct 31, 2023 | 765.85 Mn |
| Jul 31, 2023 | 741.03 Mn |
| Apr 30, 2023 | 687.42 Mn |
| Jan 31, 2023 | 623.11 Mn |
| Oct 31, 2022 | 572.33 Mn |
| Jul 31, 2022 | 531.75 Mn |
| Apr 30, 2022 | 463.21 Mn |
| Jan 31, 2022 | 401.62 Mn |
| Oct 31, 2021 | 370.93 Mn |
Snowflake 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=SNOW&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "SNOW", "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=SNOW&period=max&api_key=YOUR_API_KEY");
const data = await res.json();