Flex (FLEX) Operating Expenses (2009 - 2026)
Flex (FLEX) recorded Operating Expenses of $332 million in fiscal Q1 2027 (quarter ended Jun 26, 2026), up 38.3% from $240 million a year earlier and up 3.1% from the prior quarter.
Flex (FLEX) Operating Expenses (2009 - 2026) Analysis & Trends
On a TTM basis, Flex's Operating Expenses came in at $1.23 billion as of Jun 26, 2026, up 22.2% year-over-year; for FY2026 (ended Mar 31, 2026), it was $1.14 billion, up 15.1% from FY2025.
- Annual Operating Expenses has a five-year compound annual growth rate of 4.4% (FY2021 to FY2026).
- Across earlier fiscal years, Operating Expenses came in at $990 million in FY2025 (-9.8%), $1.1 billion in FY2024 (+21.8%), $901 million in FY2023 (+6.6%) and $845 million in FY2022 (-8.0%).
- The fiscal Q1 2027 figure is the highest quarterly Operating Expenses since fiscal Q4 2024.
- On a year-over-year basis, Operating Expenses has increased for five consecutive quarters, with growth averaging 10.9% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 142.4% in fiscal Q4 2024, against a decline of 26.4% in fiscal Q4 2025 at the low end.
- Per Business Quant, the preceding three fiscal quarters came in at $322 million (Q4 2026), $276 million (Q3 2026) and $302 million (Q2 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Apple | 5,041.12 Bn | 4,788.61 Bn | 54.77 Bn | 19.08 Bn |
| 2 | Cisco Systems | 436.07 Bn | 371.99 Bn | 11.06 Bn | 6.80 Bn |
| 3 | Dell Technologies | 301.57 Bn | 257.33 Bn | 9.83 Bn | 4.45 Bn |
| 4 | Arista Networks | 222.94 Bn | 176.40 Bn | 1.91 Bn | 532.30 Mn |
| 5 | Sandisk | 184.51 Bn | 173.03 Bn | 7.58 Bn | 545.00 Mn |
| 6 | Sony | 155.70 Bn | 92.96 Bn | 6.53 Bn | 14.83 Bn |
| 7 | Seagate Technology Holdings | 140.90 Bn | 135.89 Bn | 1.90 Bn | 2.07 Bn |
| 8 | Western Digital | 130.38 Bn | 120.21 Bn | 2.53 Bn | 488.00 Mn |
| 9 | Hewlett Packard Enterprise | 78.30 Bn | 56.17 Bn | 4.93 Bn | 10.82 Bn |
| 10 | Flex | 28.17 Bn | 17.63 Bn | 747.00 Mn | 332.00 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 26, 2026 | 332.00 Mn |
| Mar 31, 2026 | 322.00 Mn |
| Dec 31, 2025 | 276.00 Mn |
| Sep 26, 2025 | 302.00 Mn |
| Jun 27, 2025 | 240.00 Mn |
| Mar 31, 2025 | 307.00 Mn |
| Dec 31, 2024 | 243.00 Mn |
| Sep 27, 2024 | 218.00 Mn |
| Jun 28, 2024 | 222.00 Mn |
| Mar 31, 2024 | 417.00 Mn |
| Dec 31, 2023 | 218.00 Mn |
| Sep 29, 2023 | 221.00 Mn |
| Jun 30, 2023 | 241.00 Mn |
| Mar 31, 2023 | 172.00 Mn |
| Dec 31, 2022 | 243.00 Mn |
| Sep 30, 2022 | 245.00 Mn |
| Jul 1, 2022 | 241.00 Mn |
| Mar 31, 2022 | 197.00 Mn |
| Dec 31, 2021 | 227.00 Mn |
| Oct 1, 2021 | 213.00 Mn |
Flex 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=FLEX&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "FLEX", "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=FLEX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();