Core Scientific (CORZ) Accumulated Expenses (2020 - 2026)
Core Scientific (CORZ) recorded Accumulated Expenses of $509.19 million in Q2 2026, up 181.9% from $180.64 million a year earlier and up 39.7% from the prior quarter.
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Analysis
Core Scientific (CORZ) Accumulated Expenses (2020 - 2026) Analysis & Trends
At the end of FY2025, Core Scientific reported Accumulated Expenses of $511.96 million, up 691.6% from FY2024.
- Annual Accumulated Expenses has a five-year compound annual growth rate of 1565.1% (FY2020 to FY2025).
- Across earlier years, Accumulated Expenses came in at $64.67 million in FY2024 (-64.0%), $179.64 million in FY2023 (+900.6%), $17.95 million in FY2022 (-73.5%) and $67.86 million in FY2021.
- Quarterly Accumulated Expenses has ranged from $3.23 million in Q3 2021 to $511.96 million in Q4 2025 over the past five years.
- On a year-over-year basis, Accumulated Expenses has increased for three consecutive quarters, with growth averaging 230.3% over the last seven quarters.
- Peak year-over-year performance for Accumulated Expenses in the last five years was growth of 900.6% in Q4 2023, against a decline of 73.5% in Q4 2022 at the low end.
- Per Business Quant, the preceding three quarters came in at $364.48 million (Q1 2026), $511.96 million (Q4 2025) and $358.27 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Microsoft | 3,809.31 Bn | 3,732.47 Bn | 60.48 Bn |
| 2 | International Business Machines | 207.26 Bn | 158.16 Bn | 9.91 Bn |
| 3 | Cloudflare | 111.87 Bn | 95.40 Bn | 499.52 Mn |
| 4 | Equinix | 99.81 Bn | 88.37 Bn | 1.40 Bn |
| 5 | Nebius | 59.68 Bn | 33.11 Bn | 448.70 Mn |
| 6 | CoreWeave | 48.00 Bn | 35.10 Bn | 1.70 Bn |
| 7 | Verisign | 25.49 Bn | 22.71 Bn | 384.60 Mn |
| 8 | Nutanix | 19.05 Bn | 10.74 Bn | 651.35 Mn |
| 9 | Akamai Technologies | 15.27 Bn | 8.68 Bn | 613.75 Mn |
| 10 | Core Scientific | 5.11 Bn | 1.57 Bn | 70.04 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 509.19 Mn |
| Mar 31, 2026 | 364.48 Mn |
| Dec 31, 2025 | 511.96 Mn |
| Sep 30, 2025 | 358.27 Mn |
| Jun 30, 2025 | 180.64 Mn |
| Mar 31, 2025 | 95.49 Mn |
| Dec 31, 2024 | 64.67 Mn |
| Sep 30, 2024 | 31.73 Mn |
| Jun 30, 2024 | 28.95 Mn |
| Mar 31, 2024 | 68.22 Mn |
| Dec 31, 2023 | 179.64 Mn |
| Sep 30, 2023 | 55.61 Mn |
| Jun 30, 2023 | 41.27 Mn |
| Mar 31, 2023 | 47.30 Mn |
| Dec 31, 2022 | 17.95 Mn |
| Sep 30, 2022 | 102.21 Mn |
| Jun 30, 2022 | 124.49 Mn |
| Mar 31, 2022 | 72.81 Mn |
| Dec 31, 2021 | 67.86 Mn |
| Sep 30, 2021 | 3.23 Mn |
API Access
Core Scientific Accumulated 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=accumulated-expenses&ticker=CORZ&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "CORZ", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=accumulated-expenses&ticker=CORZ&period=max&api_key=YOUR_API_KEY");
const data = await res.json();