MARA Sells 20,880 BTC for $1.5B in Q1 2026, Shifts Focus to AI Infrastructure

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MARA sold 20,880 BTC for $1.5B in Q1 2026, using proceeds for debt buybacks and leverage reduction. The firm also acquired a $1.5B Ohio power plant to build AI data centers. MARA posted a $1.26B net loss and cut 15% of staff. Traders using TA for crypto are analyzing the risk-to-reward ratio of MARA’s strategic pivot.

MARA Holdings, the digital asset technology company formerly known as Marathon Digital Holdings, sold 20,880 Bitcoin for $1.5 billion in the first quarter of 2026, the miner disclosed in a recent filing.

Proceeds from the sales were mainly used to fund debt buybacks and reduce leverage, including repurchasing convertible notes. These actions were part of MARA’s balance sheet optimization and capital restructuring efforts.

The company may continue to sell portions of its holdings depending on market conditions and capital priorities.

“Bitcoin is not only a reserve asset on our balance sheet; it is also a source of strategic financial flexibility,” Salman Khan, Chief Financial Officer of MARA Holdings, said during the company’s earnings call. “We will continue to deploy it thoughtfully when doing so creates measurable value for shareholders, and we intend to use it selectively to strengthen the balance sheet and fund strategic priorities.”

As of March 31, MARA held 35,303 Bitcoin worth $2.9 billion, with nearly 10,000 coins either loaned out or pledged as collateral. The company now ranks as the fourth largest corporate holder of Bitcoin, per BitcoinTreasuries.NET.

MARA makes $1.5B bet on AI data centers with Ohio power plant acquisition

MARA has entered a $1.5 billion agreement to buy Long Ridge Energy & Power from FTAI Infrastructure, expanding its push into AI data centers and energy-backed digital infrastructure. The deal includes a 505 MW gas-fired power plant in Ohio and 1,600+ acres for future AI and HPC development.

MARA said the acquisition supports its strategy of controlling large-scale power assets needed for AI workloads, with plans to develop a campus that could scale beyond 1 gigawatt. The company expects to start initial AI buildout in 2027, with capacity coming online around mid-2028.

MARA said the deal will close in the second half of 2026 pending regulatory approvals and will be financed in part through a $785 million Barclays bridge facility. The asset base is expected to generate roughly $144 million in annualized EBITDA.

The quarterly numbers tell a rough story

MARA posted a net loss of $1.26 billion in Q1 2026, compared with a $533 million net loss in Q1 2025. Revenue fell 18% year over year to $175 million, reflecting lower Bitcoin prices, while total Bitcoin mined declined slightly to 2,247 BTC from 2,286 BTC.

The company’s total assets stood at $4.95 billion versus $7.29 billion at year-end 2025, mainly due to fair value changes and balance sheet deleveraging.

MARA reduced debt by repurchasing about $1 billion of convertible notes, recording a $71 million gain on extinguishment, bringing total debt to $2.45 billion including a $150 million Bitcoin-backed credit line. It generated $1.19 billion in investing cash flow, largely from selling 20,880 BTC for nearly $1.5 billion.

The company maintained 72.2 EH/s of energized hashrate and continued expanding into AI infrastructure through the Exaion acquisition, Starwood joint venture, and a $46 million restructuring program.

MARA cuts 15% of staff as it pivots to AI and critical IT focus

As part of its transition toward AI and digital infrastructure, the company confirmed it had reduced its workforce by 15%, targeting $12 million in annualized cost savings.

The restructuring resulted in a $45.9 million charge linked to the closure of select business initiatives and internal realignment.

Management said the changes reflect a shift away from a Bitcoin mining-centric operating model toward one focused on scaling AI and critical IT infrastructure.

The company expects its adjusted G&A run rate, excluding stock-based compensation and acquisition-related expenses, to decline below Q1 levels as cost efficiencies are realized over time.

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