Rambus (RMBS) Operating Expenses (2009 - 2026)
Rambus (RMBS) reported Operating Expenses of $92.68 million for Q2 2026, up 24.5% from $74.45 million a year earlier and up 13.2% from the prior quarter.
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Analysis
Rambus (RMBS) Operating Expenses (2009 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Rambus' Operating Expenses came in at $332.45 million, up 18.9% 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%).
- The Q2 2026 figure ranks as the highest quarterly Operating Expenses since Q4 2016.
- Year over year, Operating Expenses has now increased in each of the last seven quarters, with growth averaging 16.4% over the last seven 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 Q2 2026 came in at $81.9 million (Q1 2026), $79.21 million (Q4 2025) and $78.67 million (Q3 2025).
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 | Rambus | 12.14 Bn | 9.58 Bn | 165.41 Mn | 92.68 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| 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 |
| Sep 30, 2021 | 58.16 Mn |
API Access
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_KEYimport 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();