Goldman Sachs (GS) Operating Expenses (2009 - 2026)
Goldman Sachs (GS) reported Operating Expenses of $11.31 billion for Q3 2026, up 19.6% from $9.45 billion a year earlier but down 3.1% from the prior quarter.
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Analysis
Goldman Sachs (GS) Operating Expenses (2009 - 2026) Analysis & Trends
Over the twelve months ended Sep 30, 2026, Goldman Sachs' Operating Expenses came in at $43.13 billion, up 19.5% year-over-year; for FY2025, it came in at $37.54 billion, up 11.2% from FY2024.
- Operating Expenses has a five-year compound annual growth rate of 5.3% (FY2020 to FY2025).
- By year, Operating Expenses came in at $33.77 billion in FY2024 (-2.1%), $34.49 billion in FY2023 (+10.7%), $31.16 billion in FY2022 (-2.4%) and $31.94 billion in FY2021 (+10.2%).
- Five-year quarterly Operating Expenses spans a low of $7.27 billion in Q4 2021 and a high of $11.67 billion in Q2 2026.
- Year over year, Operating Expenses has now increased in each of the last seven quarters, with growth averaging 12.8% over the last eight quarters.
- The high point for year-over-year Operating Expenses in five years was Q2 2026 (growth of 26.3%); the low point was Q1 2022 (a decline of 18.2%).
- Per Business Quant data, the three quarters before Q3 2026 came in at $11.67 billion (Q2 2026), $10.43 billion (Q1 2026) and $9.72 billion (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Jpmorgan Chase | 920.14 Bn | 897.90 Bn | - | 27.30 Bn |
| 2 | Banco Santander Chile | 407.42 Bn | -7,109.68 Bn | - | - |
| 3 | Bank Of America | 353.20 Bn | -2,022.91 Bn | - | 19.72 Bn |
| 4 | Hsbc Holdings | 307.88 Bn | -2,967.28 Bn | - | 8.82 Bn |
| 5 | Morgan Stanley | 298.41 Bn | -244.41 Bn | - | 13.71 Bn |
| 6 | Royal Bank Of Canada | 283.46 Bn | -546.54 Bn | - | 7.02 Bn |
| 7 | Goldman Sachs | 264.45 Bn | -3,478.99 Bn | - | 11.31 Bn |
| 8 | Mitsubishi Ufj Financial | 259.19 Bn | -159.36 Bn | 5.24 Bn | 2.13 Bn |
| 9 | Wells Fargo & Company | 258.28 Bn | 93.72 Bn | - | 13.74 Bn |
| 10 | American Express | 215.12 Bn | 14.60 Bn | - | 14.55 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 11.31 Bn |
| Jun 30, 2026 | 11.67 Bn |
| Mar 31, 2026 | 10.43 Bn |
| Dec 31, 2025 | 9.72 Bn |
| Sep 30, 2025 | 9.45 Bn |
| Jun 30, 2025 | 9.24 Bn |
| Mar 31, 2025 | 9.13 Bn |
| Dec 31, 2024 | 8.26 Bn |
| Sep 30, 2024 | 8.32 Bn |
| Jun 30, 2024 | 8.53 Bn |
| Mar 31, 2024 | 8.66 Bn |
| Dec 31, 2023 | 8.49 Bn |
| Sep 30, 2023 | 9.05 Bn |
| Jun 30, 2023 | 8.54 Bn |
| Mar 31, 2023 | 8.40 Bn |
| Dec 31, 2022 | 8.09 Bn |
| Sep 30, 2022 | 7.70 Bn |
| Jun 30, 2022 | 7.65 Bn |
| Mar 31, 2022 | 7.72 Bn |
| Dec 31, 2021 | 7.27 Bn |
API Access
Goldman Sachs 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=GS&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "GS", "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=GS&period=max&api_key=YOUR_API_KEY");
const data = await res.json();