Rambus (RMBS) Operating Expenses (2009 - 2026)
Rambus (RMBS) reported Operating Expenses of $87.26 million for Q3 2026, up 10.9% from $78.67 million a year earlier but down 5.8% from the prior quarter.
Rambus (RMBS) Operating Expenses (2009 - 2026) Analysis & Trends
Over the twelve months ended Sep 30, 2026, Rambus' Operating Expenses came in at $341.05 million, up 15.4% year-over-year; for FY2025, it was $303 million, up 15.0% from FY2024.
- Operating Expenses has a five-year compound annual growth rate of 5.7% (FY2020 to FY2025).
- By year, Operating Expenses came in at $263.51 million in FY2024 (+29.1%), $204.06 million in FY2023 (-24.5%), $270.27 million in FY2022 (+15.7%) and $233.63 million in FY2021 (+1.7%).
- Five-year quarterly Operating Expenses spans a low of -$23.61 million in Q3 2023 and a high of $92.68 million in Q2 2026.
- Year over year, Operating Expenses has now increased in each of the last eight quarters, with growth averaging 15.7% over the last eight quarters.
- The high point for year-over-year Operating Expenses in five years was Q2 2023 (growth of 39.1%); the low point was Q2 2024 (a decline of 23.1%).
- Per Business Quant data, the three quarters before Q3 2026 came in at $92.68 million (Q2 2026), $81.9 million (Q1 2026) and $79.21 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | SK hynix | 24,980.27 Bn | 24,964.04 Bn | 43.99 Bn | 3.63 Bn |
| 2 | Taiwan Semiconductor Manufacturing | 10,337.48 Bn | 9,919.73 Bn | 31.04 Bn | 3.64 Bn |
| 3 | Nvidia | 3,939.34 Bn | 3,713.50 Bn | 72.14 Bn | 8.41 Bn |
| 4 | Broadcom | 1,653.85 Bn | 1,579.89 Bn | 20.46 Bn | 4.50 Bn |
| 5 | Micron Technology | 880.27 Bn | 785.91 Bn | 47.05 Bn | 2.77 Bn |
| 6 | Advanced Micro Devices | 875.86 Bn | 824.07 Bn | 7.21 Bn | 4.38 Bn |
| 7 | Asml Holding | 576.26 Bn | 531.95 Bn | 5.90 Bn | - |
| 8 | Intel | 316.79 Bn | 179.50 Bn | 7.10 Bn | 4.57 Bn |
| 9 | Applied Materials | 294.03 Bn | 294.03 Bn | 5.25 Bn | 1.59 Bn |
| 10 | Rambus | 353.95 Mn | -2.80 Bn | 170.91 Mn | 87.26 Mn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 87.26 Mn |
| Jun 30, 2026 | 92.68 Mn |
| Mar 31, 2026 | 81.90 Mn |
| Dec 31, 2025 | 79.21 Mn |
| Sep 30, 2025 | 78.67 Mn |
| Jun 30, 2025 | 74.45 Mn |
| Mar 31, 2025 | 70.68 Mn |
| Dec 31, 2024 | 71.73 Mn |
| Sep 30, 2024 | 62.72 Mn |
| Jun 30, 2024 | 64.99 Mn |
| Mar 31, 2024 | 64.08 Mn |
| Dec 31, 2023 | 62.98 Mn |
| Sep 30, 2023 | -23.61 Mn |
| Jun 30, 2023 | 84.54 Mn |
| Mar 31, 2023 | 80.14 Mn |
| Dec 31, 2022 | 72.85 Mn |
| Sep 30, 2022 | 68.34 Mn |
| Jun 30, 2022 | 60.76 Mn |
| Mar 31, 2022 | 68.33 Mn |
| Dec 31, 2021 | 65.07 Mn |
Rambus 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=RMBS&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "RMBS", "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=RMBS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();