Td Synnex (SNX) Operating Expenses (2010 - 2026)
Td Synnex (SNX) reported Operating Expenses of $784.64 million for fiscal Q3 2026 (quarter ended Aug 31, 2026), up 4.8% from $748.5 million a year earlier but down 4.6% from the prior quarter.
Powered by 
Analysis
Td Synnex (SNX) Operating Expenses (2010 - 2026) Analysis & Trends
Over the twelve months ended Aug 31, 2026, Td Synnex's Operating Expenses came in at $3.16 billion, up 9.9% year-over-year; for FY2025 (ended Nov 30, 2025), it came in at $2.95 billion, up 6.0% from FY2024.
- Operating Expenses has a five-year compound annual growth rate of 34.4% (FY2020 to FY2025).
- By fiscal year, Operating Expenses came in at $2.79 billion in FY2024 (-3.2%), $2.88 billion in FY2023 (+1.0%), $2.85 billion in FY2022 (+125.0%) and $1.27 billion in FY2021 (+88.3%).
- Five-year quarterly Operating Expenses spans a low of $658.17 million in fiscal Q3 2024 and a high of $822.22 million in fiscal Q2 2026.
- Year over year, Operating Expenses has now increased in each of the last six quarters, with growth averaging 6.4% over the last eight quarters.
- The high point for year-over-year Operating Expenses in five years was fiscal Q4 2021 (growth of 377.0%); the low point was fiscal Q3 2024 (a decline of 10.0%).
- Per Business Quant data, the three fiscal quarters before Q3 2026 came in at $822.22 million (Q2 2026), $763.67 million (Q1 2026) and $792.06 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Infosys | 50.24 Bn | 36.74 Bn | 1.60 Bn | 528.00 Mn |
| 2 | Cognizant Technology Solutions | 31.12 Bn | 24.28 Bn | 1.83 Bn | 812.00 Mn |
| 3 | Wipro | 20.11 Bn | 14.81 Bn | 738.00 Mn | 2.23 Bn |
| 4 | Td Synnex | 19.66 Bn | 13.82 Bn | 1.43 Bn | 784.64 Mn |
| 5 | Cdw | 19.39 Bn | 17.38 Bn | 1.32 Bn | 891.20 Mn |
| 6 | Cgi | 16.87 Bn | 14.67 Bn | - | - |
| 7 | Arrow Electronics | 11.10 Bn | 10.05 Bn | 1.13 Bn | 747.88 Mn |
| 8 | Avnet | 7.54 Bn | 6.72 Bn | 865.03 Mn | 634.01 Mn |
| 9 | EPAM Systems | 6.64 Bn | 2.28 Bn | 429.57 Mn | 245.25 Mn |
| 10 | Ingram Micro Holding | 6.19 Bn | 1.79 Bn | 958.68 Mn | 722.71 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Aug 31, 2026 | 784.64 Mn |
| May 31, 2026 | 822.22 Mn |
| Feb 28, 2026 | 763.67 Mn |
| Nov 30, 2025 | 792.06 Mn |
| Aug 31, 2025 | 748.50 Mn |
| May 31, 2025 | 718.90 Mn |
| Feb 28, 2025 | 694.61 Mn |
| Nov 30, 2024 | 716.13 Mn |
| Aug 31, 2024 | 658.17 Mn |
| May 31, 2024 | 709.60 Mn |
| Feb 29, 2024 | 703.19 Mn |
| Nov 30, 2023 | 731.83 Mn |
| Aug 31, 2023 | 731.04 Mn |
| May 31, 2023 | 710.53 Mn |
| Feb 28, 2023 | 705.41 Mn |
| Nov 30, 2022 | 725.56 Mn |
| Aug 31, 2022 | 674.50 Mn |
| May 31, 2022 | 703.05 Mn |
| Feb 28, 2022 | 746.22 Mn |
| Nov 30, 2021 | 757.81 Mn |
API Access
Td Synnex 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=SNX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "SNX", "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=SNX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();