Climb Global Solutions (CLMB) Operating Expenses (2010 - 2026)
Climb Global Solutions' Operating Expenses came in at $21.19 million for Q2 2026, up 26.3% from $16.77 million a year earlier and up 0.3% from the prior quarter.
Climb Global Solutions (CLMB) Operating Expenses (2010 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Climb Global Solutions reported Operating Expenses of $77.83 million, up 15.5% year-over-year; for FY2025, it came in at $68.36 million, up 14.5% from FY2024.
- Operating Expenses has increased in each of the last six years, with a five-year compound annual growth rate of 21.5% (FY2020 to FY2025).
- Going back by year, Operating Expenses was $59.72 million in FY2024 (+31.1%), $45.56 million in FY2023 (+29.7%), $35.13 million in FY2022 (+7.6%) and $32.64 million in FY2021 (+26.3%).
- The Q2 2026 figure represents the highest quarterly Operating Expenses in data going back to Q2 2010.
- Year-over-year, Operating Expenses increased in seven of the last eight quarters, with growth averaging 25.1%.
- The fastest year-over-year change in Operating Expenses over five years came in Q2 2023 (growth of 47.2%), and the weakest in Q2 2022 (a decline of 2.5%).
- Business Quant data shows CLMB's Operating Expenses at $21.13 million (Q1 2026), $18.29 million (Q4 2025) and $17.22 million (Q3 2025) in the three quarters before Q2 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Infosys | 42.66 Bn | 42.72 Bn | 1.60 Bn | 528.00 Mn |
| 2 | Cognizant Technology Solutions | 25.65 Bn | 18.82 Bn | 1.83 Bn | 812.00 Mn |
| 3 | Td Synnex | 20.51 Bn | 14.54 Bn | 1.34 Bn | 822.22 Mn |
| 4 | Cdw | 16.33 Bn | 14.32 Bn | 1.32 Bn | 891.20 Mn |
| 5 | Cgi | 15.07 Bn | 12.85 Bn | - | 12.44 Mn |
| 6 | Arrow Electronics | 11.72 Bn | 10.75 Bn | 1.13 Bn | 747.88 Mn |
| 7 | Avnet | 8.33 Bn | 7.51 Bn | 865.03 Mn | 634.01 Mn |
| 8 | Ingram Micro Holding | 6.23 Bn | 1.84 Bn | 958.68 Mn | 722.71 Mn |
| 9 | EPAM Systems | 5.55 Bn | 1.19 Bn | 429.57 Mn | 245.25 Mn |
| 10 | Climb Global Solutions | 608.52 Mn | 423.78 Mn | 30.16 Mn | 21.19 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 21.19 Mn |
| Mar 31, 2026 | 21.13 Mn |
| Dec 31, 2025 | 18.29 Mn |
| Sep 30, 2025 | 17.22 Mn |
| Jun 30, 2025 | 16.77 Mn |
| Mar 31, 2025 | 17.28 Mn |
| Dec 31, 2024 | 18.69 Mn |
| Sep 30, 2024 | 14.65 Mn |
| Jun 30, 2024 | 13.54 Mn |
| Mar 31, 2024 | 13.55 Mn |
| Dec 31, 2023 | 12.85 Mn |
| Sep 30, 2023 | 10.47 Mn |
| Jun 30, 2023 | 11.68 Mn |
| Mar 31, 2023 | 10.26 Mn |
| Dec 31, 2022 | 9.26 Mn |
| Sep 30, 2022 | 9.29 Mn |
| Jun 30, 2022 | 7.93 Mn |
| Mar 31, 2022 | 8.25 Mn |
| Dec 31, 2021 | 7.82 Mn |
| Sep 30, 2021 | 7.76 Mn |
Climb Global Solutions 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=CLMB&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "CLMB", "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=CLMB&period=max&api_key=YOUR_API_KEY");
const data = await res.json();