Schrodinger (SDGR) Operating Expenses (2019 - 2026)
Schrodinger (SDGR) recorded Operating Expenses of $73.98 million in Q2 2026, down 6.4% from $79.06 million a year earlier and down 5.6% from the prior quarter.
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Analysis
Schrodinger (SDGR) Operating Expenses (2019 - 2026) Analysis & Trends
On a TTM basis, Schrodinger's Operating Expenses came in at $300.76 million as of Jun 30, 2026, down 9.4% year-over-year; for FY2025, it was $309.51 million, down 9.3% from FY2024.
- Annual Operating Expenses has a five-year compound annual growth rate of 20.0% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $341.38 million in FY2024 (+7.3%), $318.14 million in FY2023 (+28.4%), $247.84 million in FY2022 (+40.0%) and $177.06 million in FY2021 (+42.3%).
- The Q2 2026 figure is the lowest quarterly Operating Expenses since Q4 2022.
- On a year-over-year basis, Operating Expenses has declined for seven consecutive quarters, with an average decline of 5.4% over the last eight quarters.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 49.1% in Q3 2021, against a decline of 14.1% in Q3 2025 at the low end.
- Per Business Quant, the preceding three quarters came in at $78.34 million (Q1 2026), $74.45 million (Q4 2025) and $73.99 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Bryn | 945.00 Bn | 945.00 Bn | - | 178,646.00 |
| 2 | Veeva Systems | 45.35 Bn | 17.59 Bn | 695.95 Mn | 420.93 Mn |
| 3 | Samsara | 22.20 Bn | 18.97 Bn | 392.58 Mn | 387.71 Mn |
| 4 | Toast | 17.53 Bn | 10.20 Bn | 516.00 Mn | 364.00 Mn |
| 5 | Ptc | 15.47 Bn | 14.28 Bn | 490.47 Mn | 323.96 Mn |
| 6 | Trimble | 13.41 Bn | 12.48 Bn | 674.90 Mn | 542.90 Mn |
| 7 | Duolingo | 12.56 Bn | 7.73 Bn | 216.74 Mn | 182.80 Mn |
| 8 | Manhattan Associates | 11.77 Bn | 10.77 Bn | 168.33 Mn | 231.56 Mn |
| 9 | Costar | 10.95 Bn | 4.91 Bn | 728.00 Mn | 652.00 Mn |
| 10 | Schrodinger | 1.94 Bn | 336.25 Mn | 32.43 Mn | 73.98 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 73.98 Mn |
| Mar 31, 2026 | 78.34 Mn |
| Dec 31, 2025 | 74.45 Mn |
| Sep 30, 2025 | 73.99 Mn |
| Jun 30, 2025 | 79.06 Mn |
| Mar 31, 2025 | 82.01 Mn |
| Dec 31, 2024 | 84.84 Mn |
| Sep 30, 2024 | 86.15 Mn |
| Jun 30, 2024 | 84.06 Mn |
| Mar 31, 2024 | 86.32 Mn |
| Dec 31, 2023 | 87.17 Mn |
| Sep 30, 2023 | 79.83 Mn |
| Jun 30, 2023 | 74.94 Mn |
| Mar 31, 2023 | 76.19 Mn |
| Dec 31, 2022 | 67.24 Mn |
| Sep 30, 2022 | 63.36 Mn |
| Jun 30, 2022 | 60.61 Mn |
| Mar 31, 2022 | 56.63 Mn |
| Dec 31, 2021 | 48.88 Mn |
| Sep 30, 2021 | 45.79 Mn |
API Access
Schrodinger 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=SDGR&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "SDGR", "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=SDGR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();