Quantum Computing (QUBT) Operating Expenses (2018 - 2026)
Quantum Computing's Operating Expenses was $21.85 million in Q2 2026, up 114.2% from $10.2 million a year earlier and up 10.2% from the prior quarter.
Quantum Computing (QUBT) Operating Expenses (2018 - 2026) Analysis & Trends
On a trailing twelve-month basis, Quantum Computing's Operating Expenses was $74.32 million through Jun 30, 2026, up 126.0% year-over-year; for FY2025, it came in at $51.14 million, up 96.3% from FY2024.
- Operating Expenses shows a five-year compound annual growth rate of 24.1% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $26.05 million in FY2024 (-1.3%), $26.41 million in FY2023 (-8.1%), $28.72 million in FY2022 (+67.7%) and $17.13 million in FY2021 (-1.2%).
- Quarterly Operating Expenses has moved between $4.63 million (Q4 2021) and $22.12 million (Q4 2025) over five years.
- Compared with a year earlier, Operating Expenses has increased for seven straight quarters, with growth averaging 79.3% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q4 2025 (growth of 147.2%); the worst was Q3 2021 (a decline of 44.9%).
- Per Business Quant data, QUBT's Operating Expenses in the three quarters before Q2 2026 was $19.83 million (Q1 2026), $22.12 million (Q4 2025) and $10.53 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 255.94 Bn | 241.02 Bn | 2.30 Bn | 2.13 Bn |
| 2 | CrowdStrike Holdings | 232.94 Bn | 213.35 Bn | 1.10 Bn | 1.13 Bn |
| 3 | Fortinet | 124.91 Bn | 110.84 Bn | 1.64 Bn | 953.90 Mn |
| 4 | Snowflake | 112.07 Bn | 99.38 Bn | 1.04 Bn | 1.30 Bn |
| 5 | Datadog | 91.70 Bn | 73.34 Bn | 881.34 Mn | 875.89 Mn |
| 6 | Zscaler | 34.52 Bn | 20.64 Bn | - | - |
| 7 | Okta | 33.89 Bn | 23.98 Bn | 641.00 Mn | 534.00 Mn |
| 8 | Axon Enterprise | 32.10 Bn | 26.62 Bn | 546.45 Mn | 499.67 Mn |
| 9 | MongoDB | 29.30 Bn | 19.76 Bn | 569.77 Mn | 541.37 Mn |
| 10 | Quantum Computing | 1.46 Bn | -2.15 Bn | -1.17 Mn | 21.85 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 21.85 Mn |
| Mar 31, 2026 | 19.83 Mn |
| Dec 31, 2025 | 22.12 Mn |
| Sep 30, 2025 | 10.53 Mn |
| Jun 30, 2025 | 10.20 Mn |
| Mar 31, 2025 | 8.30 Mn |
| Dec 31, 2024 | 8.95 Mn |
| Sep 30, 2024 | 5.45 Mn |
| Jun 30, 2024 | 5.33 Mn |
| Mar 31, 2024 | 6.33 Mn |
| Dec 31, 2023 | 6.59 Mn |
| Sep 30, 2023 | 6.64 Mn |
| Jun 30, 2023 | 7.02 Mn |
| Mar 31, 2023 | 6.16 Mn |
| Dec 31, 2022 | 10.28 Mn |
| Sep 30, 2022 | 6.85 Mn |
| Jun 30, 2022 | 4.87 Mn |
| Mar 31, 2022 | 6.73 Mn |
| Dec 31, 2021 | 4.63 Mn |
| Sep 30, 2021 | 4.78 Mn |
Quantum Computing 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=QUBT&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "QUBT", "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=QUBT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();