Spire Global (SPIR) Operating Expenses (2020 - 2026)
Spire Global's Operating Expenses was $26.05 million in Q2 2026, down 20.8% from $32.9 million a year earlier.
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Analysis
Spire Global (SPIR) Operating Expenses (2020 - 2026) Analysis & Trends
On a trailing twelve-month basis, Spire Global's Operating Expenses was $114.2 million through Jun 30, 2026, down 13.3% year-over-year; for FY2025, it was $125.14 million, up 14.7% from FY2024.
- Operating Expenses has now increased for five consecutive years, with a five-year compound annual growth rate of 23.1% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $109.15 million in FY2024 (+12.1%), $97.37 million in FY2023 (+1.4%), $96.02 million in FY2022 (+3.8%) and $92.48 million in FY2021 (+109.2%).
- Quarterly Operating Expenses has moved between $14.97 million (Q4 2022) and $38.23 million (Q4 2024) over five years.
- Compared with a year earlier, Operating Expenses was higher in four of the last seven quarters, with growth averaging 21.8%.
- The best year-over-year quarter for Operating Expenses over five years was Q4 2021 (growth of 150.9%); the worst was Q4 2022 (a decline of 54.2%).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 280.36 Bn | 265.44 Bn | 2.30 Bn | 2.13 Bn |
| 2 | CrowdStrike Holdings | 253.37 Bn | 233.78 Bn | 1.10 Bn | 1.13 Bn |
| 3 | Fortinet | 134.62 Bn | 120.55 Bn | 1.64 Bn | 953.90 Mn |
| 4 | Snowflake | 116.92 Bn | 104.23 Bn | 1.04 Bn | 1.30 Bn |
| 5 | Datadog | 95.78 Bn | 77.42 Bn | 881.34 Mn | 875.89 Mn |
| 6 | Okta | 36.98 Bn | 27.07 Bn | 641.00 Mn | 534.00 Mn |
| 7 | Zscaler | 35.32 Bn | 21.44 Bn | - | - |
| 8 | Axon Enterprise | 32.81 Bn | 27.33 Bn | 546.45 Mn | 499.67 Mn |
| 9 | MongoDB | 28.75 Bn | 19.21 Bn | 569.77 Mn | 541.37 Mn |
| 10 | Spire Global | 351.17 Mn | -36.66 Mn | 6.16 Mn | 26.05 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 26.05 Mn |
| Dec 31, 2025 | 29.55 Mn |
| Sep 30, 2025 | 25.69 Mn |
| Jun 30, 2025 | 32.90 Mn |
| Mar 31, 2025 | 34.21 Mn |
| Dec 31, 2024 | 38.23 Mn |
| Sep 30, 2024 | 26.44 Mn |
| Jun 30, 2024 | 23.26 Mn |
| Mar 31, 2024 | 21.22 Mn |
| Dec 31, 2023 | 19.50 Mn |
| Sep 30, 2023 | 26.30 Mn |
| Jun 30, 2023 | 25.57 Mn |
| Mar 31, 2023 | 25.99 Mn |
| Dec 31, 2022 | 14.97 Mn |
| Sep 30, 2022 | 26.58 Mn |
| Jun 30, 2022 | 26.23 Mn |
| Mar 31, 2022 | 28.25 Mn |
| Dec 31, 2021 | 32.69 Mn |
| Sep 30, 2021 | 21.60 Mn |
| Jun 30, 2021 | 18.96 Mn |
API Access
Spire Global 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=SPIR&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "SPIR", "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=SPIR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();