Cryoport (CYRX) Operating Expenses (2010 - 2026)
Cryoport (CYRX) posted Operating Expenses of $32.86 million for Q2 2026, up 5.9% from $31.03 million a year earlier and up 4.2% from the prior quarter.
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Analysis
Cryoport (CYRX) Operating Expenses (2010 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Cryoport was $127.39 million, up 6.2% year-over-year; for FY2025, it was $119.86 million, down 37.4% from FY2024.
- Annual Operating Expenses shows a five-year compound annual growth rate of 12.6% (FY2020 to FY2025).
- In prior years, Cryoport's Operating Expenses was $191.33 million in FY2024 (+8.8%), $175.87 million in FY2023 (+29.5%), $135.78 million in FY2022 (+18.7%) and $114.41 million in FY2021 (+72.4%).
- The Q2 2026 figure stands as the highest quarterly Operating Expenses since Q2 2024.
- On a year-over-year basis, Operating Expenses increased in three of the last eight quarters, with an average decline of 15.8%.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q2 2024, with growth of 122.2%; the weakest was Q2 2025, with a decline of 67.6%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $31.53 million (Q1 2026), $31.74 million (Q4 2025) and $31.26 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Union Pacific | 162.83 Bn | 157.35 Bn | - | 4.10 Bn |
| 2 | Csx | 86.94 Bn | 83.15 Bn | - | 2.43 Bn |
| 3 | Canadian Pacific Kansas City | 76.07 Bn | 75.78 Bn | - | 1.95 Bn |
| 4 | United Parcel Service | 70.39 Bn | 47.31 Bn | - | 21.90 Bn |
| 5 | Norfolk Southern | 70.35 Bn | 64.99 Bn | - | 2.34 Bn |
| 6 | Fedex | 68.01 Bn | 33.95 Bn | - | 23.46 Bn |
| 7 | Delta Air Lines | 55.83 Bn | 38.01 Bn | - | 17.89 Bn |
| 8 | Old Dominion Freight Line | 36.82 Bn | 36.08 Bn | - | 1.09 Bn |
| 9 | Ryanair Holdings | 28.96 Bn | 12.97 Bn | 3.13 Bn | 4.43 Bn |
| 10 | Cryoport | 877.23 Mn | -755.62 Mn | 22.82 Mn | 32.86 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 32.86 Mn |
| Mar 31, 2026 | 31.53 Mn |
| Dec 31, 2025 | 31.74 Mn |
| Sep 30, 2025 | 31.26 Mn |
| Jun 30, 2025 | 31.03 Mn |
| Mar 31, 2025 | 25.84 Mn |
| Dec 31, 2024 | 32.24 Mn |
| Sep 30, 2024 | 30.83 Mn |
| Jun 30, 2024 | 95.69 Mn |
| Mar 31, 2024 | 32.57 Mn |
| Dec 31, 2023 | 54.51 Mn |
| Sep 30, 2023 | 41.18 Mn |
| Jun 30, 2023 | 43.07 Mn |
| Mar 31, 2023 | 37.12 Mn |
| Dec 31, 2022 | 37.31 Mn |
| Sep 30, 2022 | 34.22 Mn |
| Jun 30, 2022 | 34.09 Mn |
| Mar 31, 2022 | 30.16 Mn |
| Dec 31, 2021 | 31.48 Mn |
| Sep 30, 2021 | 28.09 Mn |
API Access
Cryoport 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=CYRX&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "CYRX", "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=CYRX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();