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CORZZ

Core Scientific, Inc. Tranche 2 Warrants

CORZZ

Core Scientific, Inc. Tranche 2 Warrants • NASDAQ
$16.72 ▲ 2.61% (+0.43)
Market Cap $5.19 B
52w High $16.97
52w Low $16.60
Dividend Yield 0%
P/E 0
Volume 4.20K
Outstanding Shares 310.15M

Income Statement

Period Revenue Operating Expense Net Income Net Profit Margin Earnings Per Share EBITDA
Q3-2025 $81.103M ▲ $69.225M ▲ $-146.66M ▲ -180.832% ▲ $-0.46 ▼ $-127.462M ▼
Q2-2025 $78.628M ▼ $31.309M ▼ $-936.799M ▼ -1.191K% ▼ $-0.042 ▼ $-634K ▲
Q1-2025 $79.525M ▼ $50.809M ▲ $580.693M ▲ 730.202% ▲ $1.44 ▲ $-20.183M ▲
Q4-2024 $94.925M ▼ $44.546M ▲ $-265.541M ▲ -279.738% ▲ $-0.6 ▲ $-234.875M ▲
Q3-2024 $95.354M $41.063M $-455.259M -477.441% $-1.56 $-418.312M

Balance Statement

Period Cash & Short-term Total Assets Total Liabilities Total Equity
Q3-2025 $453.443M ▼ $2.296B ▲ $3.424B ▲ $-1.128B ▼
Q2-2025 $581.345M ▼ $1.978B ▲ $3.043B ▲ $-1.065B ▼
Q1-2025 $697.942M ▼ $1.625B ▲ $1.807B ▼ $-181.507M ▲
Q4-2024 $836.197M ▲ $1.599B ▲ $2.419B ▲ $-820.18M ▼
Q3-2024 $253.019M $921.851M $1.651B $-729.395M

Cash Flow Statement

Period Net Income Cash From Operations Cash From Investing Cash From Financing Net Change Free Cash Flow
Q3-2025 $-146.66M ▲ $131.781M ▲ $-254.359M ▼ $-5.324M ▲ $-127.902M ▼ $-122.836M ▼
Q2-2025 $-936.799M ▼ $34M ▲ $-119.608M ▼ $-31.772M ▼ $-117.38M ▲ $-87.279M ▲
Q1-2025 $580.693M ▲ $-40.599M ▼ $-93.458M ▼ $-4.198M ▼ $-138.255M ▼ $-129.021M ▼
Q4-2024 $-184.79M ▲ $13.805M ▲ $-28.798M ▲ $598.171M ▲ $583.178M ▲ $-14.953M ▲
Q3-2024 $-455.259M $5.713M $-31.24M $182.224M $156.697M $-25.336M

Five-Year Company Overview

Income Statement

Income Statement Revenue over the last few years has been modest and fairly flat, with no clear growth momentum yet. Profitability has been very volatile: the company swung from a brief period of meaningful operating profit to deep losses, especially during the restructuring phase around its crypto mining exposure. Even in the most recent year, the business is still loss‑making at the bottom line and at the cash‑earnings level, suggesting the core operations are not yet fully scaled or optimized for the new AI/HPC focus. The pattern shows a company in transition rather than a mature, stable earner, with execution on the AI pivot likely to drive whether margins can recover and become sustainably positive.

Balance Sheet

Balance Sheet The balance sheet shows a business that has carried a heavy financial burden from its legacy mining build‑out. Assets are sizable for a company of this revenue level, reflecting all the physical infrastructure, but debt has also been high and shareholder equity has turned negative in recent years. Negative equity is a sign that past losses and financing choices have eroded the accounting value of the company, leaving it financially stretched on paper. Cash has recently improved, which provides some breathing room, but the capital structure still looks aggressive and sensitive to setbacks if the AI expansion does not ramp as planned.

Cash Flow

Cash Flow Despite accounting losses, the company has been able to generate positive operating cash flow in recent years, which is an encouraging sign that the underlying operations can produce cash once non‑cash items are stripped out. However, heavy investment in infrastructure continues to consume cash, so free cash flow has swung between slightly positive and slightly negative. This pattern is typical of a capital‑intensive build‑out phase: money coming in from operations but quickly reinvested into facilities and equipment. The key question going forward is whether the AI data center strategy can eventually shift this from “build mode” to consistently cash‑generative, after covering expansion needs and debt service.

Competitive Edge

Competitive Edge Core Scientific is trying to turn its earlier bet on bitcoin mining infrastructure into an advantage in AI and high‑performance computing. Its main edge lies in large, power‑dense sites; deep know‑how in energy management; and cooling and software systems already proven at scale. The long‑term hosting agreements and planned acquisition by CoreWeave give it an anchor customer and a strong partner, which can provide volume and funding support but also creates customer concentration risk. Competition in AI infrastructure is intense and includes hyperscalers, traditional data center operators, and other former miners; Core Scientific’s moat will depend on how quickly and efficiently it can convert and expand its sites, and how well it diversifies its customer base beyond CoreWeave over time.

Innovation and R&D

Innovation and R&D Most of the company’s innovation is practical and infrastructure‑driven rather than traditional lab‑style R&D. It has developed proprietary software to manage very large fleets of machines, advanced liquid and thermal cooling systems, and sophisticated power optimization tools, all of which are directly reusable for AI workloads. The current roadmap is focused on turning former mining campuses into application‑specific AI and HPC data centers, scaling power capacity, and integrating tightly with CoreWeave’s cloud platform. Future differentiation will likely come from how efficiently it can run ultra‑dense GPU environments, how well it manages energy costs and uptime, and whether it can offer a smooth, turnkey experience for AI customers relative to rival data center providers.

Summary

Overall, Core Scientific (linked to CORZZ warrants) is a turnaround and transformation story: shifting from a highly cyclical, bruising bitcoin mining business to a long‑term AI infrastructure platform. The financial statements still reflect the scars of that past—volatile earnings, negative equity, and heavy leverage—while the cash flows and new contracts hint at a more stable, infrastructure‑like future if execution is strong. Its main strengths are physical scale, power access, and operational expertise in running high‑density computing environments, reinforced by the strategic partnership and pending acquisition by CoreWeave. Key risks include high capital needs, dependence on a few major customers, intense competition in AI data centers, and the challenge of converting large investments into durable, attractive returns over time.