Nvidia (NVDA) Operating Expenses (2009 - 2026)
Nvidia (NVDA) reported Operating Expenses of $8.41 billion for fiscal Q2 2027 (quarter ended Jul 26, 2026), up 55.3% from $5.41 billion a year earlier and up 10.3% from the prior quarter.
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Analysis
Nvidia (NVDA) Operating Expenses (2009 - 2026) Analysis & Trends
Over the twelve months ended Jul 26, 2026, Nvidia's Operating Expenses came in at $28.66 billion, up 47.6% year-over-year; for FY2026 (ended Jan 25, 2026), it was $23.08 billion, up 40.7% from FY2025.
- Operating Expenses has increased for 15 consecutive fiscal years, with a five-year compound annual growth rate of 31.5% (FY2021 to FY2026).
- By fiscal year, Operating Expenses came in at $16.41 billion in FY2025 (+44.8%), $11.33 billion in FY2024 (+1.8%), $11.13 billion in FY2023 (+49.7%) and $7.43 billion in FY2022 (+26.8%).
- The fiscal Q2 2027 figure ranks as the highest quarterly Operating Expenses in data going back to fiscal Q4 2009.
- Year over year, Operating Expenses has now increased in each of the last 13 quarters, with growth averaging 45.1% over the last eight quarters.
- The high point for year-over-year Operating Expenses in five years was fiscal Q1 2023 (growth of 113.0%); the low point was fiscal Q1 2024 (a decline of 29.6%).
- Per Business Quant data, the three fiscal quarters before Q2 2027 came in at $7.62 billion (Q1 2027), $6.79 billion (Q4 2026) and $5.84 billion (Q3 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Nvidia | 5,638.19 Bn | 5,412.36 Bn | 72.14 Bn | 8.41 Bn |
| 2 | Taiwan Semiconductor Manufacturing | 2,452.80 Bn | 2,078.51 Bn | 27.22 Bn | 3.13 Bn |
| 3 | Broadcom | 1,695.44 Bn | 1,621.48 Bn | 20.46 Bn | 4.50 Bn |
| 4 | Micron Technology | 1,213.55 Bn | 1,152.31 Bn | 35.06 Bn | 1.72 Bn |
| 5 | Advanced Micro Devices | 1,034.54 Bn | 991.29 Bn | 6.20 Bn | 4.21 Bn |
| 6 | Asml Holding | 719.69 Bn | 675.53 Bn | 5.90 Bn | - |
| 7 | Intel | 601.78 Bn | 486.52 Bn | 6.51 Bn | 4.71 Bn |
| 8 | Lam Research | 434.81 Bn | 411.60 Bn | 3.48 Bn | 965.25 Mn |
| 9 | Applied Materials | 428.57 Bn | 394.02 Bn | 4.59 Bn | 1.51 Bn |
| 10 | Arm Holdings | 326.25 Bn | 311.96 Bn | 1.25 Bn | -1.16 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 26, 2026 | 8.41 Bn |
| Apr 26, 2026 | 7.62 Bn |
| Jan 25, 2026 | 6.79 Bn |
| Oct 26, 2025 | 5.84 Bn |
| Jul 27, 2025 | 5.41 Bn |
| Apr 27, 2025 | 5.03 Bn |
| Jan 26, 2025 | 4.69 Bn |
| Oct 27, 2024 | 4.29 Bn |
| Jul 28, 2024 | 3.93 Bn |
| Apr 28, 2024 | 3.50 Bn |
| Jan 28, 2024 | 3.18 Bn |
| Oct 29, 2023 | 2.98 Bn |
| Jul 30, 2023 | 2.66 Bn |
| Apr 30, 2023 | 2.51 Bn |
| Jan 29, 2023 | 2.58 Bn |
| Oct 30, 2022 | 2.58 Bn |
| Jul 31, 2022 | 2.42 Bn |
| May 1, 2022 | 3.56 Bn |
| Jan 30, 2022 | 2.03 Bn |
| Oct 31, 2021 | 1.96 Bn |
API Access
Nvidia 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=NVDA&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "NVDA", "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=NVDA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();