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NASDAQ:CORZ

Core Scientific Q3 2025 Earnings Report

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$26.52 +1.26 (+4.99%)
As of 11:27 AM Eastern

Core Scientific EPS Results

Actual EPS
-$0.46
Consensus EPS
-$0.85
Beat/Miss
Beat by +$0.39
One Year Ago EPS
N/A

Core Scientific Revenue Results

Actual Revenue
$81.10 million
Expected Revenue
$107.18 million
Beat/Miss
Missed by -$26.08 million
YoY Revenue Growth
N/A

Core Scientific Announcement Details

Quarter
Q3 2025
Time
After Market Closes
Conference Call Date
Friday, October 24, 2025
Conference Call Time
4:00PM ET

Upcoming Earnings

Core Scientific's Q2 2026 earnings is estimated for Friday, August 14, 2026, based on past reporting schedules

Core Scientific Earnings Headlines

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About Core Scientific

Core Scientific (NASDAQ:CORZ) (NASDAQ: CORZ) is a leading provider of large-scale blockchain infrastructure and digital asset mining services. The company develops, owns and operates high-performance data centers optimized for the mining of Bitcoin and other proof-of-work cryptocurrencies. In addition to its core mining operations, Core Scientific offers colocation, hosting and managed services designed to support institutional clients and enterprise users in deploying and scaling blockchain nodes and computing hardware.

Core Scientific’s service portfolio includes hardware procurement, deployment and maintenance, real-time monitoring, power management and network connectivity. Its facilities are engineered for maximum energy efficiency and uptime, leveraging advanced cooling systems and redundant power feeds. This turnkey approach enables customers to focus on their blockchain strategy while relying on Core Scientific’s infrastructure expertise and operational support.

The company’s data centers are located across North America, with operations in states such as Georgia, Texas and Washington. These strategically positioned facilities provide access to competitively priced electricity markets and robust grid capacity. Core Scientific also offers high-performance computing (HPC) solutions that cater to emerging workloads in machine learning, artificial intelligence and large-scale data analytics, leveraging its existing infrastructure to meet growing demand for compute-intensive applications.

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