EIF Dallas (July 23) is a high-signal, curated conference convening leaders across energy, compute infrastructure, and capital to map the next decade of power and data center buildout.

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There are moments in proof-of-work mining when the market briefly reminds everyone that electricity is not tied to a single digital asset, or even a business model.

The same megawatt can secure bitcoin, mine Zcash, chase Kaspa rewards or support an AI/HPC workload. Which one makes the most sense increasingly depends less on ideology than on a moving set of prices: token values, network difficulty, machine efficiency, hosting rates and power costs.

For the past year, public-market investors have largely rewarded the AI side of that equation. Bitcoin miners with large power portfolios have been repriced on the idea that their sites may be more valuable as data center infrastructure than as pure mining operations.

But Zcash’s rally, after years on the sidelines, has complicated that narrative.

The price appreciation of ZEC since late last year, followed by renewed hashrate momentum on the network, has made Equihash mining economics suddenly relevant again. In some cases, the revenue per unit of power now compares favorably not only with other proof-of-work assets, but also with estimated HPC colocation economics.

That backdrop helps explain why Fortitude Mining’s plan to go public is arriving at an interesting time.

Fortitude, a Zcash-focused digital asset mining platform under Digital Curreny Group, announced this week that it plans to list on Nasdaq through an all-stock merger with HeartSciences. The proposed company would operate under the Fortitude brand and is expected to trade under the ticker TUDE, subject to Nasdaq approval.

The transaction is still light on detailed financial disclosure. But Fortitude has released enough operating data to make the broader point clear: this is not just another crypto miner trying to attach itself to the AI trade. It is a test of whether public investors still have an appetite for a crypto-native compute business when the economics of a non-bitcoin proof-of-work network suddenly improve.

A Revenue-per-Megawatt Lens

TheEnergyMag’s latest analysis compares revenue across several proof-of-work mining rigs and a conservative estimated HPC colocation benchmark on a common basis: dollars per megawatt-hour.

The result is a useful snapshot of the compute market’s current hierarchy.

On the high end, a Zcash-focused Z15 Pro generates an estimated $373 per MWh, far above the $223 per MWh conservative estimate for HPC colocation. A next-generation bitcoin miner, the S23 Pro, comes in at about $133 per MWh, while the S21 Pro produces roughly $84 per MWh. By comparison, the DG1+ and Kaspa-focused KS5 and KS3 models generate about $65, $48 and $19 per MWh, respectively, under the assumptions used in the analysis.

That spread matters because it cuts through the usual framing of bitcoin mining versus AI infrastructure. The more precise comparison is not crypto versus AI. It is compute revenue versus power cost, with different machines and workloads competing for the same scarce input: electricity.

Over the past year, the dominant market narrative has been that bitcoin miners should redirect power toward AI and high-performance computing whenever possible. That logic is easy to understand. AI demand has created a scarcity premium for energized land, grid interconnection rights and large-scale power capacity.

But the revenue comparison shows the decision is not always straightforward.

HPC contracts may offer longer duration, lower volatility and stronger visibility than mining, provided that the business development and execution process is done well. That makes them attractive from a financing perspective, especially for public companies trying to reduce dependence on daily crypto-market swings.

Mining, however, retains optionality. When a proof-of-work asset rallies substantially faster than its network difficulty adjusts, mining revenue can temporarily exceed what infrastructure owners might earn from contracted HPC hosting.

Zcash is currently an example of that dynamic. Zcash has historically occupied a smaller niche than bitcoin, with less liquidity, fewer institutional narratives and a narrower base of industrial-scale miners. But the recent ZEC price rally has changed the revenue math for Equihash ASICs.

That does not mean Zcash mining is more valuable than HPC infrastructure on a risk-adjusted basis. Just search Zcash’s price crash and fast rebound earlier this month. Nonetheless, it perfectly shows that crypto-native compute can still produce bursts of exceptional returns, particularly in smaller networks where price and hashrate can move out of sync.

That creates both opportunity and risk for companies like Fortitude. A Zcash-focused platform may enjoy stronger near-term mining economics when ZEC outperforms, but it is also more exposed to the market volatility and the speed at which network difficulty can adjust and erode those gains.

Fortitude’s Timing

Fortitude’s public-market plan lands directly into that debate.

The company has not yet released detailed financials, leaving investors without a full view of its revenue, cost structure, power contracts or margins. But the operating metrics it has disclosed suggest it is not a small exploratory Zcash operation.

Fortitude said it began mining ZEC, the native token of the Zcash network, in 2019 and has since scaled production to an annualized run rate of 157,000 ZEC. Based on ZEC’s current price of about $400, that production rate implies a static annualized revenue of about $62 million.

Either way, the disclosed production rate gives Fortitude a meaningful operating base in a network that remains far smaller than bitcoin but has recently become more economically attractive for specialized miners. The timing is important: ZEC’s price appreciation has improved mining revenue for Equihash ASICs, while rising hashrate suggests more machines are being pointed at the network to capture those returns.

That dynamic gives Fortitude a more differentiated story than public bitcoin miners that are increasingly trying to convince investors their megawatts can be repurposed for AI. Fortitude is entering the market as a crypto-native infrastructure company with direct exposure to Zcash economics.

That identity may help it stand out, but it also narrows the questions investors will ask. Without detailed financials, the key issues will be how much of Fortitude’s revenue depends on current ZEC prices, how quickly network difficulty is rising, what its power costs look like, and whether its fleet can remain competitive as more Equihash capacity comes online.

In that sense, Fortitude’s planned listing could become a useful public-market test case for non-bitcoin proof-of-work exposure. If Zcash economics remain strong, the company may find investor appetite for a miner tied to a differentiated asset. If margins normalize quickly, the listing may instead reinforce how difficult it is for crypto-native miners to turn cyclical revenue spikes into durable infrastructure value.

Regulation News

• US to Fast-Track AI Data Centers as Power Bottleneck Becomes National Priority

• Texas Regulators Approve ERCOT Batch Process for AI Data Center Power Requests

• Thailand seeks to arrest fugitive Chinese businessman over illegal crypto mining

Hardware and Infrastructure News

• Microsoft to Build 2GW AI Data Center Campus in West Texas With Onsite Gas Power

• Constellation, Walmart Sign Nuclear Power Deal for Illinois Supply Chain Expansion

• Bitzero Adds Finland Land Reservation to Nordic AI Data Center Pipeline

• Galaxy Digital Advances $400 Million AI Data Center Plan in McGregor, Texas

• Sphere 3D Signs 30 MW Bitcoin Co-Mining Deal With Bitdeer

Corporate News

• Hut 8 Investors Reach $2.35 Million Settlement Over US Bitcoin Merger Claims

• Riot CEO Sells Another $7M as Bitcoin Miner Briefly Tops $30 on AI Rally

• DOE Announces $17.5 Billion Loan Commitment to Revive American Nuclear Supply Chain

• CoreWeave Expands Swedish Presence with Conapto Data Center Deal

• Bitcoin Miners Move to Defend Exchange Listings as Sub-$1 Shares Persist

Financial News

• DCG’s Fortitude Mining to Go Public Through HeartSciences Merger

• Cerebras Systems Reports Q1 2026 Revenue of $193.4 Million

• HIVE Lines Up Swedish AI Lease as It Seeks $100 Million Note Offering

Feature

• EIF Speaker Series: ‘AI’s Real Buildout Has Barely Begun’ with NG Zhang

• EIF Speaker Series: ‘Inference Could Shift the AI Compute Mix’ with Paul Golding

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EIF Dallas (July 23) is a high-signal, curated conference convening leaders across energy, compute infrastructure, and capital to map the next decade of power and data center buildout.

Get your tickets today and use code MNRW30 for 30% off exclusively for Miner Weekly subscribers. You can also explore sponsorship opportunities to elevate your brand and connect with leaders across energy, infrastructure, and capital.

Bitcoin’s latest difficulty adjustment was a reminder that the network still runs on a simple rule: when mining economics weaken enough, hashrate leaves.

On June 14, Bitcoin’s mining difficulty fell by 10.09% to 124.93 trillion, one of the largest downward adjustments in the network’s history by percentage terms. The drop followed a two-week period of slower block production, signaling that a meaningful amount of computing power had come offline.

But the scale matters as much as the percentage. Bitcoin’s hashrate had been hovering near the 1 ZH/s mark before the decline. At that level, a 10% drawdown implies roughly 100 EH/s of computing power was taken offline during a single difficulty epoch. For context, Bitcoin’s entire network hashrate was only around 200 EH/s four years ago. What disappeared over the past two weeks was roughly half of the total computing power securing the network at that time.

Several factors likely contributed. Bitcoin’s early-June price decline pushed hashprice back toward levels that leave less-efficient fleets near breakeven. Texas miners entered ERCOT’s 4CP summer season, when curtailing during a few peak-demand intervals can materially reduce annual transmission charges.

And across North America, another structural force is becoming harder to ignore: some of the largest public miners are no longer trying to maximize bitcoin hashrate at all costs. They are trying to decide how much of their power should still be used for bitcoin mining.

That distinction matters. If miners are merely unplugging older ASICs because hashprice is weak, the machines can come back when economics improve. But if a site is being retrofitted for high-performance computing, reserved for an AI tenant or financed as a future data center campus, that power may not return to Bitcoin mining in the next bull market.

The latest difficulty drop is therefore more than a network statistic. It is part of a broader reallocation now underway in the mining sector. Bitcoin miners are losing hashrate in one part of the market while gaining a new valuation framework in another.

The Funding Gap Behind the Repricing

This is where the latest difficulty drop connects with the equity market.

The market has already started to value certain public miners less as pure bitcoin producers and more as owners of scarce power infrastructure. That shift — from hashrate to megawatts — is familiar by now. The larger question is no longer whether miners control assets that AI developers want. Many of them do.

The harder question is who can afford to turn those assets into AI data centers.

That is the reality check behind VanEck’s latest framework for valuing bitcoin miners as AI infrastructure. The report argues that miners pursuing AI/HPC opportunities should be evaluated around energized power, execution risk and tenant quality. It also estimates that miners pursuing the transition face a roughly $50 billion near-term funding gap.

The number captures the central tension of the trade. Public miners have been rewarded for owning scarce power at a time when AI developers are desperate for it. But AI data centers require far more capital than bitcoin mining sites. A bitcoin mine can run with relatively simple buildings, modular infrastructure and ASIC fleets that tolerate fast curtailment. AI and HPC facilities require higher standards for uptime, cooling, electrical redundancy, networking and customer support.

That means the next phase of the trade will likely be more selective. Investors are moving from rewarding AI optionality to underwriting AI execution.

A miner with a large undeveloped power portfolio may still have significant strategic value, but it needs capital, customers and time. A miner with a smaller but contracted and financed project may deserve a different multiple. The distinction is between AI option value and AI execution value — and the gap between the two may be where the next repricing happens.

Why the Index Matters

This is also the backdrop for TheEnergyMag’s AI Infrastructure Growth Index.

The index is being built around a market shift that is already visible but still difficult to isolate. Public bitcoin miners are no longer trading only as bitcoin beta. Some are becoming power-backed AI infrastructure bets. Others remain primarily mining companies with optionality. A few sit in between, with operating hashrate, large power portfolios, early AI contracts and unresolved funding needs.

The point of the index is not to treat every miner with an AI slide deck as an AI infrastructure company. It is to track the companies sitting at the fault line between bitcoin mining, power markets and AI compute demand.

That includes miners with energized sites and credible conversion paths, AI infrastructure platforms whose growth depends on power access, and developers assembling land, substations and interconnection rights ahead of future demand.

The index is less a claim that miners have already become AI companies than a way to monitor how much of the market is starting to value them that way.

The Hashrate Question

There is also a consequence for Bitcoin.

The network does not reward miners for holding future AI development rights. It only rewards active hashrate. If North America’s largest public miners increasingly allocate their best sites to AI or HPC, Bitcoin does not get credit for their power portfolios. It only gets the machines that remain online.

That does not mean the AI pivot caused the latest difficulty decline by itself. It did not. Weak hashprice, older machines, seasonal curtailment and power-market dynamics all played a role. But the AI pivot changes how the next hashrate recovery may unfold.

In previous cycles, weaker mining economics pushed inefficient machines offline. When conditions improved, operators could redeploy capital into new ASICs and bring hashrate back. This cycle is different because the alternative use case for power is more compelling.

AI tenants can support longer contracts and potentially more stable revenue than mining. For public miners under pressure to improve multiples and diversify revenue, the opportunity cost of dedicating power to bitcoin mining has gone up.

That raises a strategic question: if the most institutionally visible North American miners keep shifting toward AI infrastructure, who absorbs Bitcoin’s next wave of hashrate growth, if there’s going to be growth at all?

The answer may be private miners that face less pressure to chase AI narratives. It may be lower-cost international power markets. It may be sovereign-backed or stranded-energy projects. Or it may be hybrid operators that keep mining as a bridge load while waiting for AI development to catch up.

What is clear is that the public-miner cycle is changing. The sector is no longer moving only between bitcoin bull markets and mining-margin downturns. It is being pulled into the larger AI infrastructure cycle, where power access, capital formation and data center execution matter as much as ASIC efficiency.

The market has already started repricing bitcoin miners for the AI boom. The next phase will test whether that repricing is supported by funded projects, contracted tenants and delivered capacity — or whether some of it was simply a higher multiple placed on undeveloped power.

Bitcoin’s latest difficulty decline shows that hashrate remains the foundation of the mining business. But the equity market is increasingly looking beyond hashrate.

Regulation News

• North Tonawanda Extends Data Center Pause as AI Conversion Plan Faces Pushback

Hardware and Infrastructure News

• Bitcoin Mining Difficulty Set for Steep Drop as Hashrate Slides After Price Crash

• Avista Pauses Talks Over 500 MW Data Center Power Request After Community Pushback

• Sovright Launches Zcash Mining Pool Testnet With Shielded Payouts

• Bitdeer’s 750MW Ohio AI Data Center Plan Draws Local Scrutiny

• HIVE Wins Approval to Buy 32 MW Sweden Data Center as AI Push Expands

• HIVE Signs $220M AI Cloud Deal With Bell, Cohere for Canadian Sovereign Stack

Corporate News

• Hut 8 Names Former Merrill Lynch CEO Stan O’Neal as Board Chair

• IREN Completes Acquisition of Spanish AI Data Center Developer Nostrum

• Sangha Renewables Weighs M&A for Texas Bitcoin Mine as AI Demand Lifts Power Assets

• SWI Group Acquires $500 Million Stake in Genesis Digital Assets to Reposition Portfolio for AI

• Northern Data CEO to Step Down as AI Infrastructure Firm Advances Rumble Deal

• Cipher Names Former ERCOT Executive as Head of Grid Strategies

• Oman Launches National Bitcoin Mining Pool Omanhash

Financial News

• Dominion Energy Announces $1.5B Junior Subordinated Notes Offering

• OpenAI’s Spending Reportedly Hit $34 Billion in 2025 as AI Race Intensified

• Tether Trims Bitdeer Stake After AI Push Lifts Bitcoin Mining Stock

• NVIDIA Prices $25B Multi-Tranche Senior Notes Offering

Feature

• Two mayors, one $10 billion AI data center, and a growing divide in small-town Texas - Fortune

• EIF Speaker Series: “Bitcoin the Ultimate Flexible Consumer of Energy” with Sean McDonough

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EIF (July 23, Dallas) is a high-signal, curated conference convening leaders across energy, compute infrastructure, and capital to map the next decade of power and data center buildout.

Get your tickets today and use code MNRW30 for 30% off exclusively for Miner Weekly subscribers. You can also explore sponsorship opportunities to elevate your brand and connect with leaders across energy, infrastructure, and capital.

ERCOT’s Four Coincident Peak (4CP) mechanism is not new. For years, large loads in Texas have been able to lower their transmission cost exposure by reducing demand during four 15-minute intervals: the highest systemwide demand interval in each summer month from June through September.

But the old rule is becoming newly important.

Texas is preparing for a much larger transmission buildout as the grid absorbs unprecedented load growth. As detailed in a previous issue, ERCOT witnessed an exponential volume of interconnection requests from large load customers, in particular, data centers. Meanwhile, according to TheEnergyMag, North American public bitcoin miners alone had more than 5.1 GW of operational power capacity in Texas as of Q1.

For these large-load customers, even a small change in transmission cost exposure can translate into a meaningful sector-wide operating cost swing. That is why operators with large but flexible loads are incentivized to navigate the 4CP intervals by curtailing their activities. But the influx of interconnection requests since 2025 has apparently prompted policymakers to review whether large flexible loads are avoiding too much of the cost by curtailing during a narrow set of summer peaks.

The debate also comes at a difficult point for bitcoin miners, the most natural flexible load operators. Bitcoin’s mining revenue remains compressed as the network difficulty remains high. In that environment, every component of the power stack matters: energy price, uptime, curtailment revenue, demand charges, ancillary-service pass-throughs, and transmission charges.

That is why the 2026 4CP season matters even before Texas finalizes any rule change. And if the state eventually moves from the current 4CP framework toward a 12CP design, the problem could become harder. Instead of defending four summer intervals, miners and other large load customers may have to manage coincident-peak exposure across all 12 months of the year.

What 4CP is

ERCOT’s 4CP mechanism allocates transmission costs to certain large consumers based on their demand during four specific systemwide peaks. The relevant moments are the single highest 15-minute demand intervals in June, July, August and September. A large load’s average demand across those intervals becomes the basis for its transmission cost allocation in the following year.

A facility can run profitably through most low-price hours, but if it is consuming power during the wrong 15-minute interval, that load can become embedded in its fixed-cost structure for the next 12 months. Conversely, if the site is curtailed during the coincident peak, it can sharply reduce that exposure.

That is why 4CP has become a summer ritual in ERCOT. Operators watch heat, system load, day-ahead and real-time demand signals, solar output, battery charging, DC tie flows and ERCOT forecasts. They do not know the official 4CP interval in real time. They only know it after the fact. So the decision is probabilistic: curtail early enough to be offline if the interval becomes the monthly peak, but not so often that the cure becomes more expensive than the disease.

LoD’s review of the 2025 season offers a useful illustration. All four coincident peaks last summer landed on weekdays in a narrow late-afternoon window: June 19 at 5:00 p.m., July 30 at 5:00 p.m., August 18 at 5:00 p.m. and September 4 at 5:30 p.m.

The timing looked predictable in hindsight. The difficulty is that each month contained multiple hot days and broad afternoon demand plateaus where several 15-minute intervals were close enough to plausibly become the peak. “Around 5 p.m.” is not precise enough when a quarter-hour interval can set a year of transmission costs.

The 2026 4CP watch has already started

Luxor said in a LinkedIn update that June’s early high-water mark had reached 81.3 GW on the first day of the season last week, prompting the first curtailment dispatch of 2026 for Luxor Energy members. The next day, ERCOT load peaked near 80.0 GW around 3 p.m. CT, close enough to the prior mark to trigger a second dispatch from Luxor’s 4CP engine.

The next test is coming soon. ERCOT’s public dashboard showed demand forecast at 80,343 MW around 6:00 p.m. CT on June 11.

None of those data points means that any specific interval will ultimately become June’s 4CP interval. The official coincident peak is only known after the fact. But the early-June data shows how quickly the monthly peak-defense problem can become active. Even before Texas reaches the hottest stretch of summer, ERCOT can produce demand levels high enough to force curtailment decisions.

For miners, the decision is not simply whether power prices are high enough to justify shutting down. LoD’s 2025 review showed that the largest demand moment of the year occurred around 84 GW while power at that moment settled near $25/MWh. Prices rose later in the evening. That means the 4CP interval can be one of the most financially important moments of the month even when real-time energy prices are not flashing red.

This is the central 4CP tension. Curtailing for 4CP is not about dodging expensive power. It is about giving up potentially profitable runtime to avoid a transmission charge that may not be confirmed until after the season ends.

Why the rule is under pressure

4CP was designed to give large loads an incentive to reduce demand during the system’s summer peaks. In theory, that reduces the need to build transmission infrastructure that only serves a few extreme demand intervals.

But the Texas grid has changed.

Solar generation has shifted parts of ERCOT’s daily risk profile. The system’s highest demand can occur while solar is still contributing enough generation to keep real-time prices relatively low. The more stressful price intervals can arrive later, as solar output fades and evening demand remains elevated.

At the same time, large flexible loads have become better at predicting and avoiding 4CP intervals. That has raised a policy question: if data centers, bitcoin mines and other large loads are part of the reason Texas needs new transmission investment, should they be able to avoid a large share of transmission charges by curtailing during four 15-minute summer intervals?

That is the backdrop for the 4CP-to-12CP discussion. A 12CP design would generally spread the cost-allocation signal across the highest-demand interval in each month of the year, rather than only the four summer months. Depending on the final design, the proposal could also involve a longer measurement interval.

The policy goal would be to make cost allocation broader and harder to avoid, while preserving some incentive for large loads to reduce demand when the grid is strained.

Why transmission cost matters now

Transmission cost is not the same thing as wholesale energy price. Operators can buy power at attractive headline prices and still carry a meaningful all-in power cost once transmission, congestion, retail adders, ancillary services, demand charges and other pass-through items are included.

LoD estimated full 4CP exposure at roughly $50,000 per MW per year, or about $1.25 million annually for a 25 MW site. For a continuously running load, that converts to roughly $5.70/MWh before considering site-specific tariffs, retail structures, hedges, behind-the-meter arrangements, or curtailment behavior.

That may not sound large in isolation. But it becomes meaningful when scaled across a fleet and when margins are thin, especially for bitcoin miners today.

In a high-hash-price market, operators can tolerate more inefficiency. A miner may still care about 4CP, but a few extra dollars per MWh or some unnecessary curtailment can be absorbed by strong mining revenue.

That cushion is much thinner today with Bitcoin’s mining revenue per unit of compute staying near all-time lows.

The 4CP decision also interacts with hashprice in a direct way. Curtailment is not free. Every hour offline means forgone bitcoin production. When hashprice is high, the opportunity cost of curtailment is high. When hashprice is low, the relative value of avoiding a fixed transmission charge rises.

That creates a narrow optimization problem. Large mining sites are flexible loads, but flexibility only has value if it can be controlled precisely. Shutting down too late misses the transmission benefit. Shutting down too early or too often sacrifices uptime. Repeated stop-start cycles also introduce operational complexity, thermal cycling and potential wear.

In a 12CP world, that only gets more complicated.

For Texas miners, 4CP has always been a hidden margin lever. In 2026, it is becoming something larger: a test of whether operators can monetize load flexibility without sacrificing too much uptime, and whether the Texas market will continue to reward that flexibility under the same rule structure.

Hardware and Infrastructure News

• Nebius to Invest £1.7 Billion in UK AI Compute Expansion

• Applied Digital Signs $5.2 Billion AI Data Center Lease for New Southern Campus

• Soluna Formalizes Metrobloks JV for 350 MW Texas AI Data Center Campus

• Crusoe Touts Contracted AI Infrastructure Capacity Nears 5 GW

• OpenAI Weighs 10-Gigawatt Ohio Data Center Lease in Potential Nvidia-Backed Deal

• Texas Adds 456 MW of Gas-Fired Power in Houston as ERCOT Braces for Summer Demand

Corporate News

• Keel Infrastructure to raise $350 million through convertible debt offering

• Dominion Energy Agrees to $825 Million Senior Notes Issuance

• CoreWeave Files Automatic Shelf Registration for Multi-Security Offerings

• Bitzero Wins Nasdaq Listing Approval as AI Infrastructure Push Expands

• Bitdeer Discloses Leadership Shake-Up Amid Deeper Push Into AI Infrastructure

• OpenAI Files Confidentially for IPO, Following Anthropic’s Move Toward Public Markets

• Sphere 3D Taps EA Advisors as Post-Merger AI Push Takes Shape

• KKR, Nvidia and Vistra Launch $10 Billion AI Infrastructure Platform Helix

Financial News

• Hut 8 Plans $4.25B Debt Raise for Texas AI Data Center

• TransAlta Prices C$350 Million Equity Offering for Colorado Gas Asset Acquisition

• Cipher Digital Seeks $810M Debt Raise to Fund Stingray Data Center

• Applied Digital Secures $350M Revolver as CoreWeave Lease Move Takes Shape

• Applied Digital Seeks $1.59 Billion Debt Raise for Fourth Ellendale AI Data Center

• CoreWeave Eyes $3.5B Debt Raise as AI Buildout Stretches Balance Sheet

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Energy Investors Forum (July 23, Dallas) is a high-signal, curated conference convening leaders across energy, compute infrastructure, and capital to map the next decade of power and data center buildout.

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Bitcoin has slumped over the past several days, extending its decline this year. But many of the largest public bitcoin mining stocks have moved in the opposite direction, underscoring a growing split between bitcoin and the companies that were once viewed as one of the most leveraged ways to trade it.

The divergence marks a notable change from the 2021 cycle, when listed miners were largely treated as high-beta proxies for bitcoin. This time, the market is increasingly rewarding miners with credible AI data-center strategies, large power portfolios or sites that can be converted from bitcoin mining to high-density computing.

The irony is hard to miss: bitcoin mining stocks are rallying because investors are starting to care less about bitcoin mining.

A basket of major public miners tracked by TheEnergyMag has broadly outperformed bitcoin since January, with the most notable divergence beginning to emerge in early May. Bitcoin is down about 28% year-to-date, while several mining and mining-adjacent equities are up sharply. Hut 8, Keel, TeraWulf, Riot Platforms, Core Scientific, Applied Digital, HIVE, Bitdeer, Cipher Mining, IREN, CleanSpark and MARA are all trading higher. Hut 8 and Keel have more than doubled.

But the rally is not uniform across the bitcoin mining complex. The market has not stopped treating all bitcoin miners as bitcoin proxies. It has stopped treating some of them that way.

American Bitcoin, Cango and Canaan are all down over the same period, even as many larger mining peers have rallied. These names are still trading more like bitcoin-mining stocks in the old 2021 sense: levered bets on bitcoin and mining economics. When bitcoin falls, their shares fall harder. When hashprice weakens, they have fewer alternative narratives to absorb the pressure. Plus, they have significantly smaller market capitalization, which makes them more vulnerable to bitcoin’s price swings.

The result is a two-speed market. One group is still being valued as bitcoin beta. The other is being recast as a backdoor way to own AI’s physical infrastructure buildout.

The broader equity market backdrop is reinforcing that shift. AI-themed stocks far beyond the mining sector have also surged. Micron, Nebius, CoreWeave and Coherent have all been swept into the same AI-infrastructure rally, reflecting investor demand for exposure to memory, cloud capacity, optical components, data centers and compute supply chains. In that context, the strongest mining stocks are not rallying in isolation. They are being pulled into a much larger trade around the physical bottlenecks of artificial intelligence.

That trade is built on a simple premise: AI needs power, space, fiber, cooling and time-to-market. Bitcoin miners happen to own some of those ingredients.

The result is a strange inversion. Bitcoin miners used to be valued for their ability to turn electricity into bitcoin. Now, some are being valued for their ability to stop doing that.

This does not mean the whole sector has successfully crossed over into AI. The actual conversion from bitcoin mining to high-performance computing remains difficult, expensive and uneven. Some miners may lack the locations, fiber access or reliability profile needed to attract AI tenants. Others may have the power but not the capital required for data-center upgrades. Some may use AI language more aggressively than their actual project pipeline justifies.

That makes the current rally both rational and speculative, and shows why the old sector labels are becoming less useful. Traditional AI indexes tend to be dominated by the largest chipmakers, cloud platforms and established technology names. But the AI buildout is also creating a more specialized group of infrastructure-exposed growth companies: power-rich bitcoin miners, data-center developers, compute providers and other listed names tied to the physical constraints of AI.

The question is not just which companies sell chips or train models. It is which companies control the bottlenecks — power, land, interconnection, cooling and time-to-market — that determine how quickly AI capacity can actually be built.

For now, capital appears to be rotating toward that bottleneck and away from bitcoin itself. That does not mean bitcoin is irrelevant. But in public equities, the center of gravity has shifted. Bitcoin is no longer the only source of excitement, and in recent weeks, it has not been the main one.

The phrase “bitcoin mining stock” may now describe a company’s history better than its valuation.

The final test may come from outside the mining sector altogether. Anthropic said this week it confidentially submitted a draft registration statement for a U.S. IPO, setting up what could become one of the most important public-market tests of the AI boom. The company’s latest funding round valued it at $965 billion, putting it within reach of becoming one of the most highly valued companies ever to enter public markets.

That raises the question hanging over miners, AI infrastructure stocks and the wider equity rally: if a near-trillion-dollar AI IPO finally reaches public markets, will it validate the boom by giving investors the pure exposure they have been chasing — or will it mark the moment when the market has to decide how much of the AI future has already been priced in?

Regulation News

• North Dakota officials say data center concerns fueled by misinformation

Hardware and Infrastructure News

• Core Scientific CEO: AI Data Center Build Costs Climb Toward $12M Per MW

• SoftBank Commits Up to €75 Billion for 5 GW AI Data Center Buildout in France

• DMG Plans 50 MW Bitcoin-to-AI Conversion at Christina Lake Site

• Cango’s Bitcoin Mining Pullback Drove 30% Drop in Realized Hashrate

• Bitdeer Breaks Ground on 100 MW Alberta Site With On-Site Gas Power

• HIVE’s Bitcoin-Backed Bitmain Deal Fueled 18 EH/s Growth Spurt

• IREN Secures Connection for 800MW AI Data Center in South Australia

Corporate News

• NVIDIA Launches DSX Platform to Standardize AI Factory Infrastructure and Grid Interaction

• NVIDIA and Microsoft Launch RTX Spark Superchip for Local AI Agent Integration

• NVIDIA and TSMC Integrate AI and Accelerated Computing into Semiconductor Fabs

• Sphere 3D, Cathedra Complete Merger to Build 53 MW Bitcoin Mining Platform

• Google and Voltus Partner on 100 MW Virtual Power Plant to Support Data Center Growth

• Hut 8 Hires Former NextEra IR Chief as It Pursues Investment-Grade Rating

Financial News

• IREN Secures $3.6B Financing for Microsoft GPU AI Buildout at ~5.9% Cost

• Anthropic Files Confidentially for U.S. IPO Amid Race for Public Market Capital

• TransAlta to Acquire Colorado Natural Gas Assets for US$1 Billion

Email us

EIF Dallas (July 23, 2026) is a high-signal, curated conference convening leaders across energy, compute infrastructure, and capital to map the next decade of power and data center buildout.

Get your tickets today and use code MNRW30 for 30% off exclusively for Miner Weekly subscribers. You can also explore sponsorship opportunities to elevate your brand and connect with leaders across energy, infrastructure, and capital.

For years, the story of Bitcoin mining and power grids was relatively simple: miners wanted cheap electricity, grids wanted flexibility, and the debate centered on whether large compute loads helped or hurt the system.

The AI data center boom is making that conversation much more complicated.

A new first-quarter – and 937-page(!!) – report from Monitoring Analytics, the Independent Market Monitor (IMM) for PJM Interconnection, offers one of the clearest warnings yet about what happens when large compute loads arrive faster than the grid can add a reliable power supply.

PJM is the largest US grid operator, serving all or parts of 13 states and Washington, DC. Its territory includes Northern Virginia, the world’s densest data center market, as well as major demand centers across the Mid-Atlantic and Midwest.

In fact, this report reads like the sequel to PJM’s earlier rule-change proposal, as covered in a previous Miner Weekly issue in March, which detailed PJM’s move to overhaul how large electricity users connect to and pay for the grid. Now the market monitor is putting numbers behind the concern: data center load is not just testing interconnection rules, it is already reshaping capacity-market costs.

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At a high level, the report’s message is blunt but nuanced: PJM’s energy market still worked competitively in the first three months of 2026, but its capacity market is under strain.

That distinction matters.

The energy market is where electricity is bought and sold for near-term use — essentially the day-to-day market for power. The capacity market is different. It pays for power plants and other resources to be available in the future, especially during peak demand or emergencies. In plain English: energy pays for the electricity used today; capacity pays for the insurance policy that enough electricity will be there tomorrow.

That insurance policy is getting much more expensive.

PJM’s total wholesale power cost rose 75.5% in the first quarter from a year earlier, from $77.78/MWh to $136.53/MWh. Wholesale power cost is the all-in market cost of serving electricity demand through PJM. It includes energy, capacity, transmission, ancillary services and administrative fees, but the first three categories dominate the total.

Energy is the cost of the electricity itself. Capacity is the cost of making sure enough power resources are available in the future. Transmission is the cost of moving electricity across the high-voltage grid. Together, those three categories made up 98.3% of PJM’s wholesale power cost in Q1.

Each contributed to the increase. Energy costs rose 78.5%, from $54.67/MWh to $97.56/MWh. Capacity costs jumped 398.1%, from $3.57/MWh to $17.78/MWh. Transmission costs rose 5.3%, from $17.86/MWh to $18.80/MWh. Energy drove the largest dollar increase, while capacity had by far the steepest percentage increase.

That does not mean households will see their electric bills rise by 75.5%. Retail power bills include many other items, including local distribution charges, state-regulated utility costs, taxes, riders and long-term power contracts. Wholesale costs also flow through at different speeds depending on the state, the utility and the type of customer.

But the direction seems clear – at least according to PJM’s IMM – that the cost stack pressure behind customer bills is getting heavier.

Not just “supply and demand”

The most interesting part of the report is not simply that power costs are rising. It is how the Market Monitor explains why.

The report pushes back on two easy explanations at once.

The first is the argument that high capacity prices are just supply and demand: demand is rising, supply is tight, so prices should go up. The second is the opposite argument: that high prices prove PJM’s capacity market is broken.

The Market Monitor’s view is more specific. PJM’s capacity market was designed to handle normal load growth — the gradual increase in electricity demand from homes, businesses, factories, weather and broader economic activity. What it is facing now is different: large data center loads arriving in concentrated blocks, backed by customers with deep pockets and urgent timelines.

In that context, “supply and demand” is true but incomplete. The demand is real, but it is not organic. It is being driven by a new class of power buyer whose need for electricity may look almost unlimited compared with the grid’s ability to add dependable capacity.

The report says current capacity-market conditions are “almost entirely” the result of large data center load additions, both actual and forecast. It also says data center load growth is “unique and unprecedented and uncertain,” requiring a different approach than simply treating the results as ordinary supply and demand.

That is the nuance: the Market Monitor is not saying competitive markets should be abandoned. It is saying the market is being asked to absorb a kind of demand it was not designed for.

The report even argues that, without the “paradigm shift” represented by what it calls the almost inexhaustible demand for power from data centers, PJM’s capacity market would have produced reliability at prices more consistent with normal load growth and the cost of new capacity.

In other words, the issue is not whether data centers should get power. The issue is how they should get power — and who should pay for the reliability cushion needed to serve them.

The $23 billion question

The scale of that cost shift appears to be no longer theoretical.

The Market Monitor estimated that existing and forecast data center load increased capacity-market revenues by a combined $23.1 billion across the 2025/2026, 2026/2027 and 2027/2028 capacity auctions. It also said the inclusion of data center load in the last two auctions increased customer bills by $13.8 billion, even after a price cap under the Pennsylvania-PJM agreement limited the impact.

A capacity auction is the process PJM uses to make sure enough power resources will be available years ahead. Utilities and power suppliers buy capacity obligations, and generators get paid for being available. When large new loads are added to the forecast, PJM needs more capacity to serve them. If supply is tight, prices rise.

It’s important to note that the $13.8 billion figure is not charged to every household as a simple flat fee. Capacity costs flow through utilities and load-serving entities, and the actual impact varies by state, utility, customer class and capacity zone. But as a rough systemwide equivalent, spreading $13.8 billion across about two years of PJM electricity demand works out to roughly 0.85 cents per kWh.

The Market Monitor’s concern is that forecast data center demand is being included in the regular auction before enough new generation exists to serve it. In that setup, other customers can end up paying higher capacity costs created by the arrival of large data centers.

This does not mean data centers are the only reason power costs rose in the first quarter. The report also points to higher fuel costs, transmission constraints and winter weather. PJM’s real-time electricity price, known as LMP, rose 67.8% from a year earlier. LMP stands for locational marginal price. In plain English, it is the wholesale price of electricity at a specific place and time. It reflects the cost of generating power, congestion on the grid, and losses from moving electricity.

Natural gas remained the biggest driver of real-time prices. Gas costs accounted for 47.0% of PJM’s real-time load-weighted LMP in the first quarter, and gas plants were the marginal resource in most real-time intervals. A marginal resource is the last and often most expensive power plant needed to meet demand. That plant often sets the market price.

So the cleaner read is this: AI data centers did not single-handedly cause PJM power costs to rise. But they are becoming one of the biggest reasons the region’s future reliability looks more expensive and politically difficult.

PJM wants data centers to bring their own power

The report’s proposed answer is direct: large new data centers should bring their own new generation or be fully curtailable.

Curtailable means the customer can be required to reduce or shut off load when the grid is under stress. “Bring your own new generation” means a data center would need to contract for new power supply that matches its demand, instead of relying on the existing grid and pushing the cost of new capacity onto everyone else.

The Market Monitor recommends that PJM establish a load queue for large new data centers so they are not added until there is adequate generation capacity to serve them. It also recommends an expedited queue option for data centers that bring their own new generation with location and timing characteristics reasonably matched to their load profile.

That recommendation has obvious implications for the computing industry.

For years, Bitcoin miners have had to think like power developers. They searched for cheap or stranded power, built near substations, negotiated curtailment, managed price volatility and learned that energization matters more than equipment announcements.

AI data centers are now running into a similar reality, but at a much larger scale and with less tolerance for interruption.

The lesson from PJM is not that data centers are bad for the grid. It is that large new loads cannot be treated as ordinary demand growth when they arrive in gigawatt-scale clusters and expect firm service. Someone has to pay for the generation, transmission and reliability cushion needed to serve them.

The fight is over who that someone should be.

Why this matters beyond PJM

PJM is not the only grid facing this issue. Across the US, utilities and grid operators are trying to reconcile three forces that do not move at the same speed.

• AI data center demand is moving fast.

• Generation and transmission development move slowly.

• Customer affordability is becoming politically sensitive.

That mismatch is why the PJM report matters beyond its own footprint. It gives a data-rich version of the same question now emerging in other power markets: when a hyperscale data center wants to connect quickly, should the broader customer base help pay for the system upgrades and capacity needed to serve it?

The Market Monitor’s answer is no — or at least, not without clearer rules. Its view is that data centers should bear their own costs and risks, rather than shifting them to households, small businesses and other industrial customers.

That framing is likely to spread.

For Bitcoin miners, the report is both a warning and an opportunity.

The warning is that large-load scrutiny is intensifying. Mining, AI, cloud and high-performance computing will all face more questions about whether they are adding costs to the grid or bringing real flexibility and power supply.

The opportunity is that miners already understand the power-first playbook. As more mining companies pivot toward AI and HPC, their experience with power procurement, curtailment and interconnection could become a competitive advantage.

The AI boom may have started as a race for GPUs. PJM’s report suggests the next phase will be a race for credible power.

And in that race, the most important question may not be who can build the biggest data center. It may be who can prove they are not leaving everyone else with the bill.

Hardware and Infrastructure News

• New West Data Eyes Alberta Oil Deal to Power AI and Bitcoin Mining Expansion

• Texas Towns Pray To Jesus That Land Will Not Become AI Data Centers

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• Enlight Secures 200 MW Solar PPA with Google for Oklahoma Data Center Operations

Corporate News

• Bitdeer Brings In Ex-Corsair CFO as Bitcoin Miner Pushes Further Into AI

• TeraWulf Stock Rises After 1 GW Kentucky AI Campus Acquisition

• Core Scientific Adds Former Equinix CEO to Board as AI Buildout Scales

Financial News

• Satoshi-era bitcoin whale moves over $200 million in BTC to FalconX, Cumberland: Onchain Lens

• Nebius Jumps as AI Hedge Fund Situational Awareness Reveals 5.6% Stake

• WhiteFiber Secures $100 Million Credit Facility for Data Center Expansion

Feature

• The Future of Bitcoin Mining Is Bigger Than Bitcoin

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Situational Awareness LP has quickly become one of the more closely watched names in the AI investment world.

Founded by former OpenAI researcher Leopold Aschenbrenner, the Artificial General Intelligence (AGI)-focused investment firm has drawn attention for both its explosive growth and the controversy surrounding its founder’s dramatic firing from OpenAI and his subsequent polarizing manifesto about the future of AI.

Its latest SEC filing this week only adds to the intrigue.

The fund’s reported 13F portfolio more than doubled in the first quarter, rising to about $13.68 billion from about $5.52 billion at the end of 2025. Much of that increase came from a larger options book tied to semiconductors and AI infrastructure.

But buried inside the direct equity portfolio was another notable trend: Situational Awareness has been loading up on Bitcoin miners – and former miners. Not just any miners, either.

Across the past few quarters, the fund has built or expanded positions in companies that sit near the center of the Bitcoin-to-AI infrastructure trade: Applied Digital, Bitdeer, Keel (formerly Bitfarms), CleanSpark, Core Scientific, HIVE Digital, IREN, and Riot Platforms. Many of these companies are either actively expanding into AI and high-performance computing or are trying to reposition their power and data center footprints for that market.

At the same time, Situational Awareness has not treated the sector as a single basket. In Q1, it exited Cipher Digital and Hut 8 and trimmed Core Scientific. That makes the filing more interesting than a simple “AI fund buys miners” story.

It suggests the fund may be sorting the sector by a sharper question: which companies offer the most attractive exposure to monetized power infrastructure?

The Miners Situational Awareness Bought and Exited

The biggest increases in Q1 came from names that still have large Bitcoin mining footprints but also meaningful AI or HPC optionality.

Situational Awareness increased its Keel position to 19.88 million shares from 6.90 million at the end of 2025. It boosted CleanSpark to 12.28 million shares from 1.64 million, Riot to 11.50 million from 6.17 million, IREN to 11.70 million from 8.70 million and Bitdeer to 3.44 million from 1.79 million. It also opened a new 3.39 million-share position in HIVE Digital.

The fund also added to Applied Digital, raising its stake to 13.48 million shares from 11.34 million, and increased CoreWeave to 7.18 million shares from 6.10 million.

That group spans several versions of the same broader theme.

Applied Digital is increasingly an AI data center developer. IREN is moving deeper into AI neocloud and AI data centers while still operating a large Bitcoin mining base. Bitdeer combines self-mining, hosting, ASIC manufacturing and early AI cloud exposure. HIVE, while still mining-heavy, is also becoming more active on the HPC cloud front through BUZZ HPC, which has announced AI cloud contracts, a fiber upgrade, and a planned 320 MW sovereign AI infrastructure project in the Greater Toronto Area. Riot has moved beyond pure mining after signing AMD as its first hyperscale data center tenant at Rockdale. Keel has laid out plans to convert existing bitcoin mining facilities to HPC data centers and wind down mining operations altogether. CleanSpark remains more mining-heavy, but each controls energized infrastructure that could become more valuable if power remains the bottleneck for compute growth.

In other words, Situational Awareness appears to be buying across the power-to-compute stack, not merely the Bitcoin mining trade. But the fund’s exits and trims make the pattern more nuanced.

Situational Awareness fully exited Cipher Digital after holding 10.47 million shares at year-end. That is notable because Cipher has one of the sector’s most prominent AI/HPC pivot stories, including major contracted data center capacity.

It also exited Hut 8, another company that has attracted attention for its power-first AI data center strategy. Core Scientific, one of the highest-profile Bitcoin-to-AI colocation conversions, was trimmed slightly to 26.01 million shares from 28.76 million.

So the filing does not read like a blanket bet on every miner with an AI narrative. It looks more like a valuation-sensitive rotation within the group.

One Way to Read the Trade: Enterprise Value per Monetized MW

The market has increasingly valued miners based on power access. But “power access” is a loose term. Some megawatts are already energized and producing revenue. Some are contracted but still under construction. Some are tied to future AI leases. Others remain part of a development pipeline that may take years to monetize.

A stricter way to compare these companies is to look at enterprise value against revenue-generating megawatts: capacity that is already energized and producing revenue through Bitcoin mining, hosting, colocation, AI cloud or HPC services.

That lens helps explain why some of Situational Awareness’ largest additions were in names that look relatively cheaper on currently monetized power. The lower end of the table is where the fund did some of its most aggressive buying.

HIVE was a new position and screened as one of the cheapest names on this basis. Bitdeer, Keel, CleanSpark and Riot also had relatively low enterprise value per revenue-generating megawatt. Those are not all identical businesses, but they share one thing: the market was assigning less value to each currently monetized MW than it was for the more AI-branded infrastructure names.

That may be part of the appeal.

For an AI-focused fund, the bet does not have to be that every miner becomes the next CoreWeave. It may be enough that energized power, operating sites and data center know-how become more valuable as AI demand keeps colliding with grid constraints.

The other side: unpriced HPC optionality

There is another layer to the trade.

Situational Awareness may not simply be buying the cheapest revenue-generating megawatts. It may be buying the cheaper megawatts where future HPC conversion has not yet been fully priced in.

That distinction matters. A miner with a low EV per revenue-generating MW can be cheap for two very different reasons. It may be overlooked, or it may lack a credible path to higher-value AI/HPC monetization. The interesting names are the ones that still screen cheaply on current monetized capacity but also have enough power, sites, management credibility or customer pipeline to plausibly become HPC candidates.

Once a miner signs a major hyperscaler contract, the market quickly stops valuing it like a Bitcoin miner and starts valuing it like an AI infrastructure developer. Enterprise value rises, EV per current revenue-generating MW expands and the “cheap power” trade becomes less obvious.

Cipher may be the cleanest example. The company has one of the strongest AI/HPC pivot stories in the group, with hundreds of megawatts already contracted to hyperscale customers. Cipher disclosed a 907 MW current portfolio, including 700 MW of contracted gross HPC capacity and operating Bitcoin mining capacity. It also pointed to about 3.3 GW of grid pipeline capacity expected to be energized across 2027 to 2030 and beyond.

That success may also help explain why Situational Awareness exited the position. By the end of Q1, Cipher’s future HPC capacity was no longer just an idea. It was tied to announced customer agreements, and a large portion of that upside appeared to have been capitalized into the stock. On current revenue-generating MW, Cipher screened as one of the most expensive names in the group.

In other words, the exit may not have been a rejection of Cipher’s AI strategy. It may have been a valuation call after the market had already rewarded that strategy.

The same logic helps explain why lower EV/MW names such as Bitdeer, CleanSpark, Riot, HIVE and Keel may still be attractive to an AI-focused investor. They have large operating power footprints, but many have not yet announced the same scale of investment-grade hyperscaler contracts. If even a portion of those megawatts can be converted from Bitcoin mining to higher-value HPC or AI data center use, the rerating potential could be meaningful.

That may be the optionality Situational Awareness is buying: not just monetized power today, but monetized power that has not yet been fully repriced as AI infrastructure.

Hut 8 shows the risk of reading 13F filings too literally

Hut 8 is the counterexample.

Situational Awareness exited Hut 8 during Q1, before the company announced a major AI data center lease in May. That later announcement changed the way investors could value Hut 8’s power pipeline.

On May 6, Hut 8 said it had signed a 15-year, 352 MW AI data center lease at its Beacon Point campus in Texas with a confidential high-investment-grade tenant. The company said the base-term contract value was $9.8 billion, inclusive of a 3% annual base rent escalator. The market reaction was immediate with Hut 8 shares jumping nearly 30% to all-time highs over $100.

With the benefit of hindsight, Situational Awareness may have exited too early.

Before the Beacon Point contract, Hut 8 may have looked less compelling on currently monetized capacity compared with the lower EV/MW mining peers. After the announcement, the market had a clearer basis to value its development pipeline as contracted AI data center revenue.

That is exactly how the miner-to-AI trade can reprice.

First, companies get credit for energized power. Then they get credit for secured power. Then they get a much larger premium when that power becomes contracted to investment-grade AI/HPC customers.

Cipher appears to have already moved further into the third stage by the end of Q1. Hut 8 arguably moved there after the quarter ended. Some of the lower EV/MW miners remain earlier in that progression.

The bigger signal

The bigger story is that Situational Awareness’ miner exposure has become another sign of how deeply the AI trade has moved into energy infrastructure.

The fund is not just buying chip stocks. It is buying companies tied to the physical bottlenecks of AI growth: power, data centers, substations, energized land and operating compute sites.

Bitcoin miners happen to own a lot of that infrastructure. Some have cheap power. Some have large campuses. Some have interconnection rights. Some have teams that know how to operate high-density electrical load. That makes them relevant to an AI investor even when their core revenue is still Bitcoin mining.

But the Q1 filing also shows that the trade is becoming more selective.

The first phase of the miner AI pivot was about who had power. The next phase may be about whose power is already monetized, whose power can be upgraded for HPC, and whose future AI value has already been priced in.

The market may be buying the miners where the power is already working, the valuation is still reasonable and the AI optionality has not yet been fully priced in. At the same time, Cipher and Hut 8 show what can happen once that optionality becomes contracted AI data center revenue: the rerating can arrive fast, and sometimes after the 13F snapshot has already moved on.

Hardware and Infrastructure News

• LU-VE Expands Texas Cooling Plant as AI Data Centers Drive Demand

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• Hut 8 to fund $16 million water infrastructure project for Louisiana AI site

• Soluna Buys Out Dorothy 1B as Bitcoin-to-AI Campus Conversion Advances

• Applied Digital Inks $7.5B Lease for 300 MW at Polaris Forge 3, Expanding AI Factory Footprint

Corporate News

• HIVE Plans CAD $3.5B Ontario AI Factory With 320 MW Power Allocation

• NextEra Energy Confirms Deal to Acquire Dominion Energy in $400 Billion Utility Merger Fueled by AI Power Demand

• Bitfury Entities Secure $81 Million Through Cipher Digital Forward Sale Agreements

• Situational Awareness Deepens AI Power Bets, Adds Bitcoin Miners in Q1 Portfolio Shift

• NextEra Energy and Dominion Energy Outline Post-Merger Leadership and Structure

Financial News

• Bitdeer Reports Q1 2026 Revenue of $188.9 Million and Positive Adjusted EBITDA

• IREN Closes $3 Billion Convertible Deal after AI Push Draws Bigger Backing

• Fluence Energy Announces $420 Million Secondary Offering by Selling Securityholders

• CoreWeave’s New $3.1B Loan Tests Wider Market for AI Infrastructure Debt

• Canaan Posts $62.7M in Q1 Revenue as Mining Footprint Expands to 11 EH/s

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EIF Dallas (July 23-24) is a high-signal, curated conference convening leaders across energy, compute infrastructure, and capital to map the next decade of power and data center buildout.

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Public Bitcoin miners spent years racing to add more hashrate to the network. In the first quarter of 2026, many of them did the opposite.

Bitcoin’s average network hashrate, based on public blockchain data, declined from roughly 985 EH/s in Q4 2025 to 873 EH/s in Q1 2026. Separately, TheEnergyMag compiled quarterly production disclosures from major publicly traded miners to calculate their respective realized hashrate implied from Bitcoin production results.

At first glance, the aggregate change among large public miners appeared relatively modest. The combined realized hashrate of 10 major ones tracked by TheEnergyMag declined only slightly from approximately 297 EH/s in Q4 2025 to 291 EH/s in Q1 2026. HIVE and Cango were excluded from the comparison because their first-quarter production data was incomplete.

But beneath that seemingly stable aggregate figure was a much more notable redistribution of industrial-scale hashing power.

While companies such as Core Scientific, IREN, Cipher Digital, TeraWulf and Keel Infrastructure sharply reduced realized hashrate as they dismantled or repurposed mining fleets for AI and HPC infrastructure, others, including Bitdeer, MARA and American Bitcoin expanded aggressively to absorb part of the displaced network share.

Among the biggest decliners, IREN’s realized hashrate fell from 42.96 EH/s to 35.83 EH/s, while Cipher dropped from 16.55 EH/s to 11.14 EH/s after fully decommissioning mining operations at its Black Pearl facility in February to begin retrofitting the site for HPC infrastructure. Keel Infrastructure, formerly Bitfarms, declined from 16.52 EH/s to 11.51 EH/s as it continued winding down legacy mining operations and shifting toward North American AI infrastructure development.

CleanSpark witnessed a modest drop but similarly signaled it intends to continue monetizing Bitcoin infrastructure while selectively pursuing AI opportunities. Executives said older ASIC fleets may eventually be sold or relocated once AI deployments become fully operational, though the company acknowledged future site conversions could result in additional impairment charges.

By contrast, Riot Platforms increased realized hashrate from 34.21 EH/s to 42.29 EH/s during the quarter. Bitdeer climbed from 43.20 EH/s to 50.26 EH/s with energization of its SEALMINERs, while MARA rose from 51.92 EH/s to 55.52 EH/s despite simultaneous expansion efforts of their businesses around AI and HPC initiatives.

The divergence highlighted a growing split within the public mining sector and that shift became especially visible in corporate filings and earnings calls, where several miners disclosed large-scale fleet dismantling efforts, asset write-downs and mining infrastructure impairments tied directly to AI conversions.

Core Scientific said mining operations will continue winding down throughout 2026, with management expecting only one or two sites to remain operational for Bitcoin mining by year-end as the company prioritizes high-density colocation infrastructure for CoreWeave. The company recorded a $266.5 million impairment charge during Q1 2026, including $151.6 million related to mining equipment and $114.9 million tied to mining infrastructure.

Cipher Digital separately disclosed $30.8 million worth of mining rigs classified as held for sale after shutting down Black Pearl mining operations. TeraWulf owned approximately 54,100 Bitcoin miners as of March 31, but only around 35,500 were operational at its Lake Mariner campus. The remaining roughly 18,600 miners were categorized as undergoing maintenance, awaiting disposal, or held on standby to replace units under repair.

Instead of merely idling rigs during periods of weak economics, operators are permanently repurposing substations, cooling systems and data center layouts for AI deployments. Once infrastructure is converted for GPU workloads, it is unlikely to quickly return to Bitcoin mining.

American Bitcoin, one of the few companies still expanding its mining fleet, argued the transition could create a long-term opportunity for dedicated Bitcoin miners willing to continue scaling while competitors unplug fleets.

The company increased its owned fleet capacity from 25 EH/s to 28.1 EH/s in April following the reenergization of its Drumheller site, which had remained offline since 2024. Much of that growth, similar to its 2025 ramp-up, was financed through an unconventional structure that used pledged bitcoin rather than cash to acquire new-generation ASIC miners from Bitmain.

As of March 31, 2026, ABTC had pledged a total of 3,090 bitcoin to Bitmain for the purchase of 18 EH/s computing power, which alone represented nearly 64% of ABTC’s 28.1 EH/s proprietary mining fleet. ABTC mined 817 bitcoin during Q1 2026, up 505% from a year earlier. At the current production pace, and assuming Bitcoin network hashrate remains roughly stable, the company could theoretically mine back the equivalent of its originally pledged bitcoin collateral in about six quarters.

If network hashrate continues declining as industrial miners unplug more hashrate to pivot toward AI infrastructure, ABTC’s payback period in bitcoin terms could accelerate even further as remaining miners capture a larger share of block rewards.

All in all, the ongoing migration has altered the financial logic of industrial mining. During previous downcycles, miners typically unplugged rigs because falling Bitcoin prices or rising energy costs rendered operations uneconomic. In 2026, however, miners are increasingly shutting down fleets because AI infrastructure offers more stable long-duration cash flows, stronger financing conditions and higher expected returns on power capacity.

It will be worth watching how the dynamics play out in the quarters to come. But for now, the system remains balanced.

Hardware and Infrastructure News

• HIVE Advances Canadian Sovereign AI Push With New Brunswick Fiber Network Upgrade

• Zcash’s Price Revival Turns ZEC Miners Into Crypto’s Top Power Earners

• Canada Plans 150 MW AI Data Center Expansion in British Columbia Amid Sovereignty Push

• Bitdeer Reports $69M AI Cloud ARR and 783 Bitcoin Mined in April

• Nebius Commences Construction of Gigawatt-Scale AI Factory in Missouri

• Phoenix Group Launches European AI Data Center Push With 18MW France Buildout

Corporate News

• IREN Deepens NVIDIA Partnership With $3.4 Billion AI Cloud Agreement

• KEEL Spent $52M on HPC Expansion, Sold Bitcoin and Latin America Assets to Fund AI Pivot

• CleanSpark Reports $136.4 Million in Q2 Revenue; ERCOT Pipeline Expands to 585 MW

• MARA Signals More Bitcoin Sales as Long Ridge Deal Looms; Confirms 15% Layoffs in AI Pivot

• Riot’s AI-Fueled Bitcoin Mining Rally Triggers CEO’s Trading Plan to Cash Out $4.2M

• Braiins Acquires Commodity Fund CAMMS Capital, Bridging Mining and Traditional Markets

• Bitfury Co-Founder Secures $100 Million in Cipher Digital Share-Backed Deal

Financial News

• MARA Moves to Amend $600M Long Ridge Notes Ahead of Power Asset Acquisition

• IREN Shares Jump 16% as Bitcoin Mining Retreat Fuels AI Expansion

• TeraWulf Reports Q1 2026 Results and New Revolving Credit Facility

• IREN Shares Sink After Unveiling $2 Billion Convertible Offering for AI Buildout

• Nscale Secures $790M Financing for Microsoft-Backed Norway AI Campus

• MARA Holdings Reports $1.26 Billion Net Loss for Q1 2026

• NVIDIA Reports $215.9 Billion in FY2026 Revenue as Data Center Networking Surges 142%

• Nebius Q1 Revenue Jumps 7x Amid ‘Unprecedented Demand’ for AI Infrastructure

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Today’s featured EIF speaker: Lisa Hough, who sits at the intersection of U.S. energy infrastructure, Bitcoin, and AI/HPC data center deployment. She brings institutional energy markets experience from Enron Capital & Trade, Phibro Energy, and PG&E National Energy Group, plus digital asset and regulatory expertise from Unchained and Custodia Bank, and is currently involved in structuring large-scale AI infrastructure initiatives including a roughly 2 GW campus in West Texas.

EIF Dallas (July 23-24) is a high-signal, curated conference convening leaders across energy, compute infrastructure, and capital to map the next decade of power and data center buildout.

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For much of the past halving cycles, bitcoin miners paid a steep premium to access debt markets—from high single-digit to high double-digit interest rates tied to volatile mining cash flows.

That premium appears to be now compressing.

A wave of project-backed financings tied to AI and high-performance computing (HPC) shows borrowing costs moving decisively lower. Deals that cleared above 9% in 2025 are now landing closer to the 6%–7% range in 2026, according to recent bond offerings across Core Scientific, Cipher Digital, Applied Digital, Hut 8 and more.

At the same time, bitcoin-backed financing is repricing lower too, with Riot Platforms recently cutting its effective borrowing cost to ~6% and Hut 8 refinancing its Coinbase credit with a new deal from FalconX to slash the cost from 9% to 7%.

This isn’t just better market conditions. It’s a repricing of the underlying collateral.

Then: ASICs, Volatility—and Double-Digit Risk Premiums

To see how far the market has moved, it helps to look back at the last cycle.

In 2021–2022, most mining debt was backed by Bitcoin ASIC machines—a collateral base that was highly cyclical, sensitive to bitcoin price and network difficulty, and prone to rapid depreciation.

The result: borrowing costs that routinely sat in the 12%–16% range, with some deals even higher depending on lender and structure. Lenders like Genesis, BlockFi and Celsius dominated the space, extending credit against rigs and bitcoin holdings in what was effectively a crypto-native shadow banking system. It worked—until it didn’t, and dragged big lenders underwater altogether when bitcoin prices fell and liquidity tightened in 2022.

Now: Contracted Compute Is Replacing Machine Collateral

Fast forward to today, and the collateral has fundamentally changed.

Instead of ASICs, lenders are underwriting long-term AI compute contracts, colocation leases with escalators and power-secured data center infrastructure.

That shift moves the credit profile away from commodity exposure and toward infrastructure-style cash flows.

CoreWeave’s trajectory is emblematic—moving from ~9% financing in 2025 to the low-6% range, supported by contracted revenue and investment-grade positioning.

Miners making the AI pivot are now being evaluated less like speculative operators—and more like emerging data center credits.

Miner Weekly

From MinerFi to ComputeFi: CoreWeave’s $8.5B Loan Rewrites the Playbook

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3 months ago · 7 likes · BlocksBridge Consulting

The Spread Tells an Interesting Story

Even as headline rates fall, dispersion remains notably—and increasingly informative.

From TheEnergyMag’s chart above:

• CoreWeave: low-6% range

• Hut 8: low-6%

• Cipher Digital: down from low-7% to low-6%

• Applied Digital: down from low-9% to high-6%

• Core Scientific: still pricing at high-7%

One of the key developments over the past year is the emergence of hyperscaler-linked credit support.

Hut 8, Cipher and TeraWulf have disclosed that Google provides financial backstop mechanisms tied to Fluidstack’s lease obligations—effectively anchoring those projects to hyperscaler demand.

That support matters and has helped pull borrowing costs into the mid- to high-single-digit range, tighter than what miners would achieve on a standalone basis.

This dynamic is clearest in the spread between Core Scientific and Hut 8. Both raised capital against AI infrastructure at roughly the same time with credible counterparties (Core Scientific with CoreWeave and Hut 8 with Fluidstack backed by Google). Yet Core Scientific continues to pay more.

AI Is Doing What Bitcoin Couldn’t

For years, miners argued they were infrastructure businesses. Markets didn’t buy it—because the collateral didn’t support the claim.

AI changed that.

With hyperscalers expected to spend roughly $700 billion on AI infrastructure this year, compute capacity has become a strategic asset. Power, land and interconnection—long the domain of bitcoin miners—are now in short supply.

Miners—who spent a decade building in exactly those constraints—are now being re-rated accordingly.

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Today’s featured EIF speaker: Mike Alfred, Founder and Managing Partner of Alpine Fox LP, a value-equities and bitcoin investment partnership, and a board director at IREN and Bakkt. He previously co-founded Digital Assets Data and led it through its acquisition by NYDIG, bringing deep experience across bitcoin markets, public-company governance, and the energy plus compute investment landscape.

EIF is a high-signal, curated conference convening leaders across energy, compute infrastructure, and capital to map the next decade of power and data center buildout.

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The AI boom is rapidly redrawing the map of U.S. data center infrastructure — but the most important signal may lie not just in where facilities exist today, but where power is being requested next.

A dataset compiled from public records by Datacenter.fyi shows there are 3,995 existing data centers across the United States, with roughly 2,900 operational. Virginia and Texas dominate that footprint, with 575 and 410 sites respectively, forming the backbone of the country’s digital infrastructure.

But the next phase of growth is already taking shape.

Texas leads the nation with 336 planned data center projects, outpacing every other state and signaling its emergence as the primary expansion frontier. Virginia follows with 203 projects, while secondary markets such as Ohio (68 planned) and Indiana (37 planned) are gaining traction as developers look beyond traditional hubs. In total, the dataset counts 932 data centers that have been planned and proposed.

At the same time, historically dense markets like California show a more limited pipeline, with just 21 projects planned — a reflection of tightening power availability and permitting constraints in legacy tech corridors.

The geographic spread points to a clear shift: proximity to users is no longer the defining factor. Power is.

That shift becomes even more apparent when looking beyond physical sites to the grid itself.

Data from Interconnect.fyi further shows active interconnection requests surged to 1,687 projects in 2025, representing a record 442 gigawatts of active requested capacity. Just five years earlier, that figure stood at roughly 100 gigawatts.

The growth has been nonlinear. From fewer than 1 gigawatt in 2012, interconnection demand has scaled into the hundreds of gigawatts, with a sharp acceleration beginning around 2021 and intensifying through 2024 and 2025.

Together, the two datasets — one mapping physical infrastructure, the other mapping power demand — reveal the full scope of the AI buildout. What is visible on the ground is only a fraction of what is queued at the grid level.

Meanwhile, the capital behind this expansion is increasingly concentrated among a handful of technology giants.

Companies including Amazon, Google, Microsoft and Meta are not only among the largest spenders on AI infrastructure, but also rank among the most prolific data center operators in the U.S., according to Datacenter.fyi’s breakdown of facility ownership.

Amazon alone accounts for 479 data centers, making it the largest operator by count, followed by CyrusOne (221), QTS (186) and Digital Realty (170). Microsoft (153), Equinix (129) and Google (79) also rank prominently, underscoring how hyperscalers and large colocation providers dominate the physical footprint of compute.

That ownership concentration is being reinforced by an unprecedented surge in capital spending.

In the first quarter alone, Amazon, Google, Microsoft and Meta collectively spent more than $130 billion on capital expenditures, largely directed toward AI data centers and supporting infrastructure. The figure marked another record and represented a sharp increase from a year earlier.

The spending trajectory shows little sign of slowing. Combined outlays from the four companies are expected to approach $700 billion this year, as each races to secure capacity for increasingly compute-intensive AI workloads.

Taken together, the data center map, the interconnection queue, and the capex surge point to the same conclusion: the current buildout is not just broad-based, but highly capital-intensive and led by a small group of firms with the balance sheets to sustain multi-year infrastructure investments.

That dynamic also helps explain the pressure building in interconnection queues. As hyperscalers commit to gigawatt-scale deployments, their demand is translating directly into large-load requests that now dominate grid pipelines across multiple regions.

The pattern feels familiar

Long before AI drove hyperscale demand, Bitcoin miners were already optimizing for the same constraint. Following the China’s Bitcoin mining ban, mining infrastructure rapidly migrated to the U.S., with Texas emerging as a global hub that effectively replaced regions like Sichuan and Xinjiang.

That migration triggered an earlier wave of power and infrastructure development — from substations to large-load interconnections — built around energy-intensive compute. In hindsight, it offered a preview of the dynamics now playing out at a much larger scale.

Industry executives have increasingly drawn that connection. At a recent panel discussion at Bitcoin 2026, featuring MARA and CleanSpark, participants described Bitcoin miners as having “plowed the road” for AI, establishing the operational and infrastructure blueprint that data center developers are now expanding upon.

The implications are becoming clearer as interconnection queues swell.

Grid access — not land or hardware — is emerging as the primary bottleneck. Projects are measured not just by capital invested, but by their position in increasingly crowded queues, where timelines can stretch years.

For the mining sector, the convergence is both validating and competitive. The same regions that once attracted hashpower are now being targeted by AI developers with deeper balance sheets and longer-term contracts, intensifying the race for power.

In that sense, mapping the U.S. data center landscape today is less about counting facilities and more about understanding the underlying energy dynamics.

The physical footprint — nearly 4,000 sites — tells the story of where computing has been. The 442 gigawatts sitting in interconnection queues tells the story of where it’s going.

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• NRG Energy Issues $2.6 Billion in Senior Notes and Secures $900 Million Term Loan

Feature

• For AI and Bitcoin Investors: The Grid’s ‘Secret Sauce’ Just Got Even Sweeter

• ‘We Plow the Road’: Miners Pitch Role in AI Buildout at Bitcoin 2026

• Who Owns the Stack: From Bitcoin to AI, the Race for Power Is Going Off-Grid

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EIF is a high-signal, curated conference convening leaders across energy, compute infrastructure, and capital to map the next decade of power and data center buildout.

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Core Scientific grabbed headlines this week with its proposed $3.3 billion senior secured notes priced at 7.75%, the latest in a wave of high-yield debt offerings tied to the AI infrastructure boom.

While the financing itself has been widely covered, a lesser-noticed supplemental filing tied to the deal offers something more revealing: a detailed look at the actual infrastructure assets being pledged to back the debt — and, more importantly, the cash flow profile expected to service it.

At the center of the deal is Core Scientific’s long-term hosting relationship with CoreWeave. The document shows that the two parties have already funded roughly 80% of the estimated $5.5 billion in total capex for the projects, underscoring how far along the buildout is.

It also lays out how Core Scientific is packaging the CoreWeave-related data center assets into a financing vehicle with the underlying sites — and their future revenues — forming the backbone of the credit story. In doing so, it provides one of the clearest disclosures yet into how a Bitcoin miner’s AI pivot is being translated into a project-financed, debt-backed business.

A Site-by-Site Look at the Buildout

Based on the document, Core Scientific is developing six data center facilities across five campuses, having secured roughly 900 MW of grid capacity to support about 590 MW of contracted critical IT load exclusively for CoreWeave.

As of mid-March, around 350 MW has been energized, with more than 185 MW already billing — a notable milestone, as it marks the transition from construction to cash-generating operations.

The buildout, however, is not yet complete, and the timeline stretches into the second half of 2027.

The filing breaks down progress by campus, offering rare visibility into how much capacity is coming online and when revenue is expected to fully ramp up.

• Austin, TX: Fully completed in 2024, with 16.5 MW of IT capacity. This site is already generating base license fees and serves as the earliest proof point of the model.

• Denton, TX: The largest project in the portfolio at 262 MW. As of March 2026, about 132 MW — roughly half — is already billable. Full completion is expected in the second half of 2026.

• Marble, NC: A 65 MW campus that is about 57% complete, with 37 MW currently billing. It is expected to reach full completion in the first half of 2026.

• Muskogee, OK: A 70 MW campus where construction began in early 2025, with both delivery and completion expected in the first half of 2026.

• Dalton 1, GA: A smaller 30 MW site scheduled to begin delivery and reach completion in the first half of 2026.

• Dalton 4, GA: A larger 145 MW expansion that will come later in the cycle, with delivery starting in the second half of 2026 and full completion targeted for the first half of 2027.

Taken together, the portfolio shows a staggered ramp, where a meaningful portion of capacity is generating revenue even as the bulk of megawatts are still under construction.

The $10B Headline — and What Actually Drives Revenue

Core Scientific frames the exclusive long-term contract as generating roughly $10 billion in total revenue over the life of its agreements with CoreWeave, net of rent repayments tied to the upfront construction funding contributed by CoreWeave.

Notably, that headline figure includes power passthrough, which materially inflates the top line without contributing to economic margin. Under this structure, CoreWeave reimburses electricity costs paid by Core Scientific, with those payments recorded as both revenue and operating expense on Core Scientific’s balance sheet.

A more grounded way to think about the underlying revenue engine is the base license fee.

Across the portfolio, CoreWeave pays a fixed rate of $100 per kW per month for most sites and $115 per kW per month for the Austin campus, with built-in annual rent escalators of 3.5% (and 3.0% for Austin). Applying those rates to the full 588.5 MW of contracted capacity translates into approximately $59 million per month in base license fees once all sites are fully built and operational, or roughly $700 million annually. This figure is a closer proxy for the net revenue generated by the infrastructure itself, before operating costs and financing effects.

Revenue vs. Levered Free Cash Flow

The illustrative financials included in the filing further underscore that distinction.

For 2026, Core Scientific projects:

• $737 million in total revenue, including power passthrough

• $418 million in operating expenses, also including power passthrough

• That works out $319 million in net operating income

• But just $6 million in levered free cash flow

Stripping the power passthrough from both revenue and operating expenses, the net operating income reflects the actual value of the hosting agreements rather than grossed-up utility flows.

The more meaningful drop occurs below that line.

The sharp compression from net operating income to levered free cash flow is largely driven by what the filing categorizes as “Other Cash Flow Items.” While this includes maintenance capital expenditures, a substantial portion relates to CoreWeave repayment mechanics — specifically, the revenue credits that reduce the cash Core Scientific receives as reimbursement for upfront construction costs. Under the agreements, CoreWeave is entitled to credits equal to 50% of the base license fee, capped at $1.5 million per MW of deployed capacity, effectively allowing it to recoup a certain portion of the buildout costs over time through reduced cash payments.

In effect, what appears as strong contracted revenue is partially being recycled back to the customer in the early years, delaying cash realization. When combined with interest expense on the $3.3 billion debt stack, the result is a business that generates significant accounting income but very limited near-term free cash flow.

Why This Matters for the Bitcoin-to-AI Pivot

This supplemental filing may not have made headlines, but it offers a critical window into how the industry’s AI pivot is being financed.

The takeaway is nuanced. Core Scientific’s deal with CoreWeave delivers long-term, contracted revenue with built-in escalation — a stark contrast to the volatility of Bitcoin mining. But it also introduces a capital-heavy structure where cash flow is constrained in the early years and heavily shaped by financing terms.

In many ways, this mirrors what has already been seen on the other side of the relationship. Just weeks ago, CoreWeave was tapping debt markets with GPU-backed financing structures, effectively using contracted compute demand as collateral to raise capital. Here, Core Scientific is doing something similar — but with powered land and data center infrastructure instead of chips.

Both cases point to the same underlying shift: AI infrastructure is increasingly being built not just with equity and operating cash flow, but through structured, asset-backed financing models where future contracted revenue is pulled forward to fund present-day capex.

That makes this more than just a Bitcoin miner diversifying into AI. It is another example of how the entire stack — from GPUs to data centers — is converging toward a project finance model, where assets are ring-fenced, cash flows are pre-allocated, and returns are shaped as much by capital structure as by demand.

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Today’s featured EIF speaker: Matthew Roszak, chairman and co-founder of Bloq and Hemi, and founding partner of Tally Capital, a globally recognized investor who has backed category-defining companies across the bitcoin and digital asset ecosystem, including Binance, Coinbase, Blockstream, and BitGo.
EIF is a high-signal, curated conference convening leaders across energy, compute infrastructure, and capital to map the next decade of power and data center buildout.
Register to attend today or explore sponsorships for private meeting rooms, branding & more.

Public bitcoin miners have liquidated their BTC reserves at a pace not seen since the depths of the last crypto bear market, as a prolonged slump in mining economics pushes operators into survival mode.

Several major public miners, including MARA, CleanSpark, Riot, Cango, Core Scientific, and Bitdeer, have already sold more than 32,000 BTC in the first quarter of 2026, according to data analyzed by TheEnergyMag. The dataset remains incomplete, as first-quarter earnings reports are still pending.

Even so, the figure already exceeds total net sales across all four quarters of 2025 and sets a new industry record, surpassing the roughly 20,000 BTC that public miners liquidated in the second quarter of 2022 during the market turmoil triggered by the Terra-Luna collapse.

The reversal is striking. Just over a year ago, miners were accumulating aggressively, ending 2024 with a net addition of 17,593 BTC and pushing combined reserves above 100,000 BTC.

The shift comes as hashprice — a key industry metric measuring expected mining revenue per unit of computing power — hovers in the low $30/PH/s range, near all-time lows. At those levels, margins are either compressed or outright negative, especially for operators running older, less efficient fleets or paying higher power costs.

The root of today’s pressure can be traced to the industry’s aggressive hashrate expansion following China’s mining ban in 2021 — a period that, in hindsight, fueled exponential growth at each company’s own expense.

For context, bitcoin’s current price — despite retreating from its all-time high above $120,000 — remains higher than the previous cycle peak. Yet network difficulty is now roughly 10 times higher than in 2021, and block rewards were cut in half in 2024. In effect, mining profitability has compressed by an order of magnitude, helping explain the wave of recent selling.

But the record liquidation does not tell a uniform story. Instead, it reveals an industry beginning to diverge — with some operators forced to sell into weakness, while others lean on structural advantages or capital discipline to ride out the downturn.

For many, the immediate priority is liquidity. Selling bitcoin remains the fastest way to shore up balance sheets, fund operations, and meet debt obligations in a financing environment that is both selective and expensive.

Others are taking a more measured approach. American Bitcoin (ABTC), the proprietary mining carve-out of Hut 8, has doubled down on accumulating bitcoin through both mining and market purchases. As of early April, it had built reserves of more than 7,000 BTC, up from zero a year earlier, while ramping its proprietary hashrate to 28 EH/s.

But the company is not repeating the hashrate-at-all-costs playbook of the previous cycle. Matt Prusak, president and interim CFO of ABTC, told TheEnergyMag that its focus is on quality growth under current market conditions.

“We won’t do deals that we don’t think will win. … When you see people chasing hashrate and chasing big exahash numbers, that’s never been our style,” Prusak said. “Having the biggest fleet doesn’t make a difference to me.”

Unlike many publicly traded peers, ABTC expanded its hardware fleet when demand for ASICs had already cooled. In the summer of 2025, it acquired roughly 15 EH/s of Antminer S21 series from Bitmain by pledging about 3,000 BTC — redeemable within 24 months — rather than paying cash. Such a structure would have been unlikely in prior market conditions. The value of the pledged bitcoin has since declined by about 40%, and Bitmain cannot liquidate the collateral unless ABTC chooses not to redeem it.

Based on Q4 2025 data analyzed by TheEnergyMag, ABTC’s all-in cash cost of production was around $55,000 per bitcoin, or roughly $25/PH/s — among the lowest in the public mining cohort. That allows it to accumulate newly mined bitcoin at a discount to prevailing market prices.

Even if bitcoin falls below that level, Prusak said the company retains the flexibility to allocate capital dynamically. ABTC raised $240 million through at-the-market offerings in 2025 and another $110 million in the first quarter of this year.

“We don’t have to flip into AI. We are a bitcoin allocator. If bitcoin’s expensive relative to the cost to mine, we mine. If bitcoin’s cheap relative to mining, then we buy.” he said, adding: “ At this time, we have no intent ot sell. … We are accumulating.”

But for private operators without comparable access to capital, the divergence in strategy is increasingly shaped by one of the industry’s oldest variables: power costs.

Sean McDonough, president and CEO of New West Data, a Canadian oil producer that mines bitcoin using off-grid power generated by flared natural gas from its own oil sites, said the company’s effective power cost is below $0.02 per kilowatt-hour. That is, in some cases, roughly one-third of what large-scale public miners pay.

At that level, even less efficient machines remain profitable. With hashprice around $30/PH/s, a miner paying $0.02/kWh can sustain fleet efficiencies of roughly 60 J/TH. McDonough said this enables the company to acquire older-generation equipment at lower upfront costs while maintaining margins, especially as ASIC prices have fallen alongside hashprice.

That cost advantage has allowed New West Data to expand despite the downturn. The company tripled both its oil production and bitcoin compute capacity in 2025 and expects to triple again this year. It currently operates about 15 MW of computing capacity, all powered by flared gas from its own sites.

Still, flared gas represents a niche model, requiring expertise in upstream oil production rather than traditional power procurement through utilities or long-term power purchase agreements.

Absent ultra-low-cost power, miner operators are also turning to operational optimization to preserve margins.

Luxor, a bitcoin mining pool operator, ASIC broker, and software provider, launched a fleet management tool called Commander earlier this month. The platform uses automated algorithms to evaluate hashrate and power market conditions every five minutes, dynamically adjusting power settings across a fleet based on real-time economics.

The goal is to optimize output from existing infrastructure. Luxor says internal benchmarks show an 8% to 14% improvement in profitability compared with traditional on/off curtailment strategies.

The shift toward software reflects a broader recalibration across the industry. With hashprice under pressure, upgrading to the latest generation of machines often requires capital outlays that are difficult to justify on a standalone return basis.

Instead, operators are focusing on extracting better margins from existing fleets — gaining incremental efficiency wherever possible.

Ethan Vera, Luxor’s chief operating officer, said the Commander platform has already scaled to about 5 EH/s of customer hashrate since launch. It complements LuxorOS, the company’s firmware solution introduced in 2022, which now supports roughly 45 EH/s, or about 5% of the global network.

In one recent case study, Luxor claimed that Soluna, a publicly traded bitcoin miner with colocation and proprietary mining in Texas, was able to speed up the recovery time via LuxorOS for its 1.1 EH/s fleet by 50% after curtailment events, improving uptime without additional operational expenditure.

All told, the industry is no longer moving in lockstep. What was once a relatively uniform business model defined by scale and hashrate growth is fragmenting into a range of survival and quality growth strategies shaped by power economics, balance sheet flexibility, and operational sophistication.

Regulation News

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Corporate News

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• Riot Data Center Chief Departs Less Than a Year After Bitcoin Miner’s AI Push

• CoreWeave Lands $6B AI Deal With Jane Street, Secures $1B Equity Investment

Financial News

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• TeraWulf raises $900 million through stock sale for Kentucky infrastructure and debt settlement

• HIVE secures $75 million through private bond issuance and seeks to list on TSX

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Today’s featured EIF speaker: Congressman Earl “Buddy” Carter (R-GA), a member of the House Energy and Commerce Committee and the House Budget Committee, where energy reliability, infrastructure investment, and technology policy collide.
EIF is a high-signal, curated conference convening leaders across energy, compute infrastructure, and capital to map the next decade of power and data center buildout.
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If 2021 was the year of ASIC-backed loans, 2026 may go down as the moment compute financing grew up.

CoreWeave’s $8.5 billion delayed draw term loan—secured primarily by GPU infrastructure—has already made headlines as the first and largest deal of its kind. The headline numbers alone are notable: the facility allows CoreWeave to draw capital through June 2027, with final maturity in March 2032. It is split between floating-rate debt priced at roughly SOFR + 2.25% and fixed-rate tranches around the high-5% range, putting the overall cost of capital in the mid-single digits—remarkably low for an asset class that didn’t meaningfully exist a few years ago.

But buried inside the credit agreement is something far more intricate: a blueprint for how Wall Street now wants to finance compute. This isn’t just “GPU-backed debt.” It’s compute treated as infrastructure.

And in many ways, it’s what MinerFi tried—and failed—to become.

The lesson from 2021: hardware alone isn’t enough

Back in 2021, bitcoin miners tapped a wave of ASIC-backed loans to expand aggressively. The premise was simple: machines generate bitcoin, bitcoin repays debt.

What that model underestimated was how volatile and fragile both sides of the equation were.

When bitcoin’s price fell in 2022, the hashrate went up relentlessly as a result of the MinerFi boom, deteriorating the hashprice even further. At the same time, the resale value of ASIC machines declined. So lenders were left with collateral that was worth less and generating less cash.

That double exposure—asset value risk and cash flow risk—was fatal.

The real collateral isn’t GPUs

CoreWeave’s credit agreement emphasizes the Data Center (DC) Funding Conditions, which are really the spine of the whole deal.

Simply put, CoreWeave cannot simply point to a purchase order for GPUs and borrow against it. The financing is tied to whether those machines are actually becoming usable compute inside a functioning data center, for a customer contract with the customer’s acceptance and satisfaction.

That matters even more because the advance rate is high.

The agreement defines the borrowing base for a funding date as the “Funding Date GPU Amount,” which equals 90% of Funding Date Capital Expenditures, plus certain fees and expenses tied to the transaction. Those capital expenditures include the cost of the infrastructure itself and installation costs.

In practical terms, lenders are saying they are willing to fund almost the entire build cost of the GPU deployment. But they only do that because the deal does not treat a GPU as collateral the moment it is bought.

Instead, the agreement requires the financed infrastructure to satisfy the DC Funding Conditions. Those conditions tie funding to real-world deployment: the equipment has to be physically associated with the relevant data center site, prior loans must already have been used properly, and for the applicable infrastructure, the DC Funding Conditions must be satisfied at the time of the borrowing. The contract also includes language elsewhere that accepted GPU clusters count toward Funding Date Capital Expenditures only when the customer has accepted them in writing and the borrower certifies testing has been completed for the relevant data halls.

So the key idea is this:

CoreWeave is getting very high leverage — roughly 90 cents of debt for every dollar of qualifying deployment cost — but only after proving that the machines are not just purchased, but installed, tested, accepted, and on the path to generating contracted revenue.

That is a notable difference from the MinerFi era.

In 2021, ASIC-backed lenders often financed miners largely on the assumption that once the machines were delivered, the economics would take care of themselves. Here, the lenders are willing to go bigger precisely because they are financing not a box of chips, but a controlled, trackable, revenue-linked compute system. That is what makes this feel less like equipment lending and more like infrastructure finance.

Following the machines down to the rack level

Once you start from that premise—only funding “ready-to-earn” assets—the rest of the structure builds around visibility and control.

Every GPU financed under the facility is tracked:

• It must be located at an approved site

• It must be tied to a specific deployment

• Lenders must have contractual access to the facility

This is very different from early ASIC lending, where collateral could be loosely defined and, in some cases, difficult to locate or control in distress scenarios.

Here, lenders know not just what they are financing, but where it is and how it is being used.

Cash doesn’t flow freely—it follows a strict order

Once those GPU clusters start generating revenue, the cash doesn’t simply go to CoreWeave.

It flows through a controlled system—known as a cash waterfall.

Here’s the idea:

Every dollar that comes in is a pre-assigned job.

1. First, pay the costs to keep the system running (power, operations)

2. Then, pay lenders (interest and principal)

3. Only after that can any remaining cash go back to the company

Why it matters: it ensures that debt repayment is prioritized automatically, rather than relying on management discretion.

In MinerFi, that level of control was often opaque.

And the agreement goes one step further with what’s called a cash trap.

If the project starts underperforming—for example, if it’s not generating enough cushion above its debt obligations—then excess cash stops flowing back to the company.

Instead, it stays within the system to prevent situations where value leaks out of the structure just as risks are rising.

Even the electric bill is part of the credit story

One of the more telling details is how seriously the agreement treats power costs.

Running GPUs at scale is energy-intensive, just like running bitcoin miners, and electricity is one of the largest—and most volatile—expenses.

The structure requires mechanisms to manage that risk, including hedging or other arrangements to stabilize power pricing.

In simple terms: the loan isn’t just underwriting compute—it’s underwriting the cost of the electricity that makes that compute possible. And that variable is actively controlled rather than left exposed.

Borrowing only happens when the math works

All of this feeds into a final layer of discipline: the project must prove it can pay for itself.

That’s where the debt service coverage ratio (DSCR) comes in. DSCR compares how much cash a project brings in versus how much it needs to pay lenders (principal+interest).

• If a project generates $120 and owes $100 in debt payments, its DSCR is 1.2x

• That extra $20 is the cushion—it allows for things to go slightly wrong without immediately causing stress

In CoreWeave’s case:

• To take on new debt, the projected DSCR needs to be around 1.20x

• To stay in compliance, it needs to maintain roughly 1.15x

That buffer is what gives lenders confidence that even if things don’t go perfectly, the system can still hold.

The bigger shift: from machines to systems

Put all of this together, and the contrast with 2021 becomes clear.

MinerFi was built around machines: Finance the hardware and expect the revenue to follow.

This deal is built around systems:

• Verify the infrastructure is live

• Confirm the cash flow is real with customer contracts

• Control how that cash is used

It’s a fundamentally different way of risk management.

At $8.5 billion, backed by major banks and structured to investment-grade standards, this isn’t just a large deal. It’s a signal.

Compute—specifically AI compute—is being redefined as infrastructure that can be financed with the same discipline as power plants or toll roads.

Bitcoin mining showed that energy can be turned into digital output at scale.

CoreWeave’s financing shows how that output can be turned into something lenders are willing to underwrite at massive scale.

Of course, structure can’t eliminate risk. Both MinerFi and this new wave of compute financing ultimately depend on demand holding up.

The difference is where the risk sits.

• In mining, it was concentrated in network and market-driven revenue (hashprice)

• Here, it’s embedded in contract durability and utilization

Whether that shift makes the system more resilient—or simply changes how stress emerges—remains to be seen.

But one thing is already clear: Compute financing has entered a new phase—and this time, it looks a lot more like Wall Street than crypto.

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Introducing EIF: A new conference in Dallas (July 23-24, 2026) for executives, investors, and operators across mining, AI/HPC, power, and infrastructure. Full details in today's press release.

The AI infrastructure boom has no shortage of capital.

It has a shortage of conversion.

Across the industry, billions of dollars are being raised, allocated, and announced at a pace that would have been unthinkable just a few years ago. But turning that capital into functioning data centers, energized megawatts, and ultimately revenue-generating compute is proving far more complex — and far slower — than the headlines suggest.

That gap is beginning to define the next phase of the AI supercycle.

Capital is flooding in

By TheEnergyMag’s analysis, nine publicly listed bitcoin mining data center operators with HPC/AI initiatives collectively raised $17 billion in net financing inflows in 2025, up from $10.9 billion in 2024. Over the same period, their net spending on property, plant, and equipment reached $6.3 billion, compared with $4.5 billion a year earlier.

The direction is clear: more capital is entering the system, and more is being deployed.

But the gap between capital raised and capital converted into productive infrastructure remains wide.

Zooming out, the same pattern is now playing out across the broader AI ecosystem.

Major technology companies, including Microsoft, Amazon, Alphabet and Meta Platforms, are expected to spend as much as $635 billion on AI infrastructure in 2026, up sharply from $383 billion in 2025.

The capital is there.

The question is how quickly — and how efficiently — it can be turned into revenue.

The conversion problem

At NVIDIA’s GTC 2026, the tone from infrastructure investors and operators was less about fundraising and more about execution. The Luxor team summarized their key takeaways from attending the event in a recent newsletter post.

One point stood out: money is no longer the scarcest input.

Instead, the constraints are increasingly physical and operational.

A single gigawatt-scale AI campus can require more than 9,000 workers across dozens of states. Equipment supply chains — from transformers to cooling systems — remain tight. Interconnection queues are clogged with projects that may never materialize. And rapidly evolving compute architectures are forcing redesigns even after construction has begun.

In other words, the bottlenecks are no longer just about securing capital or even power in isolation.

They sit at the intersection of:

• labor availability

• grid access and transmission

• equipment manufacturing

• site design and cooling architecture

• tenant readiness and utilization

Each layer introduces friction between capex committed and cash flow realized.

The grid is no longer a passive input

Nowhere is this friction more visible than in power markets.

In the Electric Reliability Council of Texas (ERCOT), as of February 2026, the Large Load Interconnection queue contained approximately 400 individual requests totaling 239,000 MW. This volume is roughly 2.8 times the current ERCOT record for system peak demand.

The headline number suggests overwhelming demand.

But it also highlights a deeper issue: not all megawatts are equally real.

In PJM Interconnection, regulators and grid operators are already moving to separate speculative load from bankable demand. PJM’s latest long-term forecast places greater emphasis on “firm” commitments — projects backed by actual construction progress or binding service obligations — rather than early-stage requests.

Meanwhile, the Federal Energy Regulatory Commission has stepped in to push for clearer rules governing co-located large loads such as data centers, reflecting mounting concern over how these facilities interact with existing grid infrastructure.

The shift is subtle but important.

The market is moving from who can secure power on paper to who can actually deliver power in practice.

From gigawatts to monetization

Even once a site is financed and energized, the conversion process is not complete.

Revenue depends on:

• securing long-term customers

• achieving high utilization rates

• aligning infrastructure with evolving compute requirements

• maintaining uptime and service guarantees

This is particularly relevant for bitcoin miners pivoting into HPC and AI colocation.

Their advantage lies in power sourcing, site development, and operational expertise. But participating in the AI infrastructure stack requires adapting to a different economic model — one that is contract-driven, utilization-sensitive, and increasingly dependent on creditworthy counterparties.

The result is a growing divergence between announced capacity and monetized capacity

The deeper story is that the AI boom is no longer confined to software or semiconductors.

It is now fully entangled with the physical economy.

Grid operators are rewriting interconnection frameworks. Utilities are reassessing cost allocation. Local communities are pushing back against large-scale developments. Labor markets are tightening around specialized construction and engineering roles.

Taken together, these dynamics point to a broader conclusion: The AI infrastructure cycle has shifted from capital scarcity to execution complexity.

Raising billions is no longer the defining challenge. Aligning capital, power, infrastructure, labor, and demand into a functioning, revenue-generating system is.

That alignment does not happen automatically. It requires coordination across stakeholders that have historically operated in silos — investors, developers, utilities, grid operators, equipment suppliers, and end users.

Where mining, AI/HPC, energy, and capital markets converge

As the gap between capital raised and revenue realized becomes more visible, the industry is entering a phase where execution, not ambition, will separate winners from the rest.

That is why we are launching the Energy Investor Forum (EIF).

EIF will bring together the companies and investors shaping the next phase of AI and power-intensive infrastructure, not just for on-stage discussion but for curated meetings and real business development across power, sites, interconnection, financing, customer relationships, and the partnerships needed to convert announced capacity into operating, monetized infrastructure. To get involved, readers can explore sponsorship opportunities, apply to speak, or request an investor attendee pass.

Because the next phase of the AI boom will not be defined by who can raise the most money. It will be defined by who can put it to work.

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Across rural America, the AI infrastructure boom is increasingly taking shape behind closed doors.

For much of the past year, some of the biggest names in AI infrastructure have been hunting for land in rural America the same way they hunt for power: quietly, quickly and often before the public knows what is happening.

The playbook has become increasingly familiar. Developers approach local officials under nondisclosure agreements (NDAs), use intermediaries or shell entities to mask the ultimate buyer, and begin assembling hundreds of acres before residents can organize around what a project might mean for farmland, water use, noise and electricity demand. That secrecy may help companies lock up strategic sites in a fiercely competitive market for AI infrastructure, but it is also becoming a political liability.

Now the backlash is getting harder to ignore.

In Wisconsin, at least five communities have now been linked to NDAs tied to proposed data center developments, according to Wisconsin Watch, which found secrecy arrangements in Beaver Dam, Kenosha, Janesville, Menomonie and most recently Beloit. In Beaver Dam, Meta used shell companies in the early stages of a 520-acre, roughly $1 billion campus. Across the state, seven major data center projects are pending with a combined value of more than $57 billion, making Wisconsin one of the clearest examples of how the AI buildout is colliding with demands for public disclosure.

The pushback has become forceful enough that Microsoft — one of the most aggressive builders of AI data center capacity globally — said this month it would stop using NDAs with local governments for data center development. The company said the old practice had been meant to protect commercially sensitive information, but that transparency with communities had become "paramount." Microsoft added that it is working to identify and terminate active NDAs with local governments, even as it reserved the right to keep using confidentiality protections for certain trade secrets and land acquisitions.

That policy shift says as much about politics as it does about process. Microsoft President Brad Smith said this week that winning over local communities has become essential as towns across the U.S. increasingly protest data center projects. Reuters reported that opposition in parts of the Midwest and Northeast has already contributed to canceled developments over concerns ranging from power prices and water usage to pollution from related energy infrastructure.

What is changing is not just the scale of the projects, but the scale of what communities feel they are being asked to absorb before anyone has had an honest public debate.

In Mason County, Kentucky, for instance, officials have backed a proposed hyperscale campus that would span about 2,080 acres of agricultural land outside Maysville. The plan envisions six data center buildings, multiple substations, stormwater ponds and phased construction beginning in summer 2027 if approvals move forward. County officials have pitched the project as an economic engine that could bring 400 full-time jobs and thousands of construction jobs, while also keeping the identity of the company behind it undisclosed unless the development is ultimately approved.

That secrecy has helped turn the project into a local flashpoint. Realtor.com and local broadcaster WKRC reported that several farming families have rejected lucrative offers to sell. One mother and daughter turned down more than $26 million for part of their land, while another family previously refused nearly $8 million. Officials say at least 20 residents were approached and 18 signed conditional sale agreements, but the holdouts have become symbols of a broader resistance: not necessarily to data centers as such, but to the idea that farmland can be quietly assembled for an unnamed AI customer and only debated in earnest after the map is largely drawn.

A similar drama is playing out in Pennsylvania, where 86-year-old farmer Mervin Raudabaugh rejected more than $15 million from a data center developer for his 261 acres in Cumberland County. Instead, he sold the development rights for about $2 million to preserve the land for agriculture. Realtor.com reported that the developer’s outreach had been persistent, while local preservation advocates said deep-pocketed data center buyers are increasingly targeting large tracts of open farmland that conservation groups cannot match on price.

Taken together, the cases point to a deeper tension in the AI infrastructure boom. For hyperscalers and their development partners, secrecy is often treated as a practical necessity. Land is scarce, power is scarcer, and once word gets out, prices can jump, competitors can swoop in and local opposition can organize before a project is mature enough to present in full. Microsoft said as much in explaining why NDAs became common in the first place.

But the communities being targeted are increasingly viewing that same secrecy as a warning sign.

In Wisconsin, backlash over confidential negotiations has fueled legislative efforts to restrict local governments from signing NDAs with data center developers. Critics say the issue is bigger than whether companies are entitled to protect trade secrets. It is about whether elected officials should be negotiating projects that can reshape land use, tax policy, infrastructure planning and local utility systems without telling the people who will live next to them.

That tension is likely to intensify as the AI buildout moves beyond established data center corridors into rural counties with abundant acreage and relatively easier paths to large-scale development. The industry still has money, urgency and political support on its side. But the farmers turning down eight-figure offers in Kentucky and Pennsylvania are a reminder that not every acre is just another site-control exercise.

In the AI race, land is becoming as strategic as chips and megawatts. The more quietly developers try to secure it, the more likely rural communities are to ask what else they are not being told.

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The most important power market for U.S. data centers is rewriting the rules.

PJM Interconnection — the grid operator spanning from Illinois to Virginia — sits at the epicenter of the global AI infrastructure buildout. The region hosts Northern Virginia, the world’s largest data center hub, and already accounts for roughly 40% of U.S. data center capacity.

Late last month, PJM filed a proposal with federal regulators to overhaul how large electricity users — particularly data centers colocated with power generation — connect to and pay for the grid. The filing was made in response to a December directive from the Federal Energy Regulatory Commission (FERC), which concluded that PJM’s existing framework no longer reflects the realities of large-scale AI-driven demand.

The timing is not accidental. The proposal comes as the White House recently emphasized a “Ratepayer Protection” stance, signaling that households and traditional businesses should not bear the cost of infrastructure built to serve energy-intensive AI and data center growth. That message closely aligns with regulators’ concerns that some large users are benefiting from the grid without paying a proportional share.

The initial public comment period on that proposal closed on March 16, drawing formal objections from industrial power users and setting the stage for a regulatory decision in the months ahead.

PJM’s filing is more than a procedural update. It represents a structural shift in how the grid treats the fastest-growing source of electricity demand in the U.S.

At stake is not just a tariff adjustment, but the economics of where — and how — the next generation of AI compute gets built.

To understand why this matters, it helps to simplify how things used to work.

From “Self-Powered” to Grid-Dependent

For years, PJM allowed something called “behind-the-meter” generation.

In simple terms, this means a company produces electricity right next to where it uses it — for example, a factory with its own gas turbine, or more recently, a data center built next to a power plant.

Under the old rules, these users could “net” their electricity usage. Think of it like this:

• If a data center uses 100 MW of power

• And produces 70 MW on-site

• The grid only counts it as using 30 MW

That accounting matters because many of the biggest grid charges are based on how much demand you place on the system.

In PJM, large customers typically pay for several things tied to their load:

• Transmission costs (paying for high-voltage lines that deliver power across the region)

• Capacity costs (paying for the grid to have enough generation available during peak demand)

• Certain system and reliability charges

If your load is counted as 30 instead of 100, those charges are calculated on the smaller number.

That made sense when onsite generation truly reduced dependence on the system.

But the problem is that large facilities — especially data centers — still rely heavily on the grid in ways that aren’t captured by that simple math:

• They need backup power when onsite generation fails

• They rely on the grid for stability and frequency control

• The grid must still be sized to serve them at full demand

In other words, even if they “self-generate” most of their power, the grid still has to be there — fully built — just in case.

That’s where regulators see a mismatch.

The 50 MW Line

PJM’s proposal introduces a clear dividing line:

• Below 50 MW → treated like traditional, smaller onsite users

• Above 50 MW → treated as large grid users, regardless of onsite generation

In practical terms, this means large data centers can no longer use accounting to significantly reduce their grid costs.

Instead, they must choose:

• Pay for firm access to the grid (guaranteed power, higher cost)

• Or take non-firm service (cheaper, but can be curtailed)

The key shift is conceptual: You are no longer “off-grid” just because you have power next door.

Why This Is Happening Now

The rule shift only makes sense when you look at what PJM is seeing internally.

The operator is facing a surge in demand unlike anything in its history — driven almost entirely by data centers.

• PJM estimates up to ~30 GW of new data center demand by 2030

• It already represents ~40% of U.S. data center capacity

Even more striking:

• Total proposed large-load requests can exceed 100 GW before filtering

To put that in perspective, that’s comparable to adding multiple large states’ worth of electricity demand onto the grid.

PJM has had to heavily discount speculative projects and apply conservative assumptions just to make the numbers usable.

Still, the conclusion is unavoidable: this is not incremental growth — it’s a structural demand shock.

The Hidden Constraint: The Grid Can’t Keep Up

Another key issue is timing.

• Data centers can be built in 1–2 years

• Grid infrastructure often takes 3–7 years

PJM’s proposed new service options reflect this mismatch. They effectively say:

• You can start operating early

• But you may be interrupted until the grid is fully upgraded

This introduces a tradeoff the industry hasn’t had to face at scale before: speed versus certainty.

The Pushback: Not From Big Tech (Yet)

Interestingly, though, the strongest opposition so far appears to be coming from industrial users, not hyperscalers just yet.

Manufacturers and combined heat & power operators argue:

• The 50 MW threshold is too low

• The rules are being rewritten for data centers

• But applied to everyone

Their concern is that longstanding onsite generation models — which genuinely reduce grid demand — could be penalized alongside large AI facilities.

Why This Matters for Bitcoin Miners

At its core, this is about cost allocation.

FERC’s position is increasingly clear:

If the grid must be built to serve you, you should pay for it — even if you don’t use it all the time.

That challenges a key strategy used by data centers: colocating with power to minimize grid costs while still relying on it as a safety net.

For Bitcoin miners, this dynamic is familiar because mining has long operated on a different model:

• Flexible demand

• Willingness to curtail

• Optimization around power pricing

In many ways, PJM’s framework formalizes that distinction:

• Firm power → expensive but reliable

• Flexible power → cheaper but interruptible

The difference is that AI workloads are far less tolerant of disruption. You can shut down ASIC miners any time – bitcoin doesn’t care. But you can’t turn off AI compute hardware without jeopardizing long-term service revenues from customers.

The Bottom Line

PJM is not just tweaking rules — it is redefining what it means to be a large power user and implementing a regulator-driven reset of how large loads interact with the grid.

The old idea was:

“If I generate my own power, I pay less for the grid.”

The new reality is:

“If the grid needs to exist for you, you pay for it.”

The first round of public comments has already been filed, and FERC is now deciding whether PJM’s proposal meets the mandate it laid out in December. Even if approved, the rule would be phased in over several years, with legacy users getting some protection and newer large-load projects facing a much stricter framework almost immediately.

That means the fight is no longer about whether the old model survives. It is now about how quickly the new one takes hold — and how expensive it becomes for the next wave of AI infrastructure to secure reliable power.

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Before we dig in: Our team has advised mining and data center companies since 2014, from ASIC launches on Bitcointalk.org and the great scaling wars to public-market debuts in 2020, environmental opposition in blue states, and today’s pivot from mining to AI/HPC. We bring that hard-won context to crisis communications, rebrands, product launches, and investor-facing messaging. If your organization could benefit from strategic communications or PR support, email us.

For years, nuclear power in the United States was widely seen as a sunset industry. Aging reactors were closing, utilities struggled to justify operating costs, and cheap natural gas combined with subsidized renewables eroded the economics of baseload generation.

Now the trend is reversing — and the catalyst isn’t government policy alone. It’s the explosive electricity demand from AI data centers.

Across recent annual filings, major utilities and power producers describe what amounts to a nuclear renaissance, fueled by long-term power contracts with hyperscalers such as Microsoft, Amazon and Meta. These companies are no longer simply purchasing renewable energy credits to offset emissions. They are underwriting entire nuclear facilities to secure carbon-free power that runs around the clock.

The reason is simple: AI infrastructure doesn’t sleep. Training clusters and high-performance computing facilities operate continuously, requiring massive quantities of reliable electricity that intermittent sources like wind and solar cannot guarantee on their own.

Nuclear plants, once considered uneconomic relics, suddenly look like strategic infrastructure.

Hyperscalers Step In as Nuclear Backers

The clearest signal of the shift is the emergence of long-term nuclear power purchase agreements (PPAs) with technology companies acting as anchor customers.

Microsoft signed a 20-year deal with Constellation Energy to support the restart of the former Three Mile Island Unit 1 reactor in Pennsylvania. The plant, retired in 2019 for economic reasons, is being revived as the Crane Clean Energy Center and will deliver roughly 835 megawatts of carbon-free power once operational.

Amazon’s cloud unit AWS struck a similar 20-year agreement with Vistra Corp for electricity from the Comanche Peak nuclear plant in Texas, securing about 1,200 megawatts of generation.

Meta has gone even further. The company signed a 20-year agreement with Vistra covering more than 2,600 megawatts of nuclear output across several plants in the PJM grid. It also reached a separate deal with Constellation Energy to purchase the output from the Clinton Clean Energy Center in Illinois.

These agreements effectively turn hyperscalers into long-term underwriters of nuclear generation — guaranteeing revenue streams that allow operators to maintain, upgrade or even restart reactors that might otherwise shut down.

An Early Signal From Bitcoin Mining

Before hyperscalers began underwriting nuclear plants for AI infrastructure, Bitcoin miners had already begun experimenting with colocating compute directly next to large power assets.

One of the clearest examples is in Pennsylvania, where Talen Energy operates the Susquehanna nuclear power plant. In 2021, Bitcoin miner TeraWulf formed a joint venture with Talen called Nautilus Cryptomine to build a large-scale mining facility directly adjacent to the plant.

The project allowed the mining operation to draw electricity directly from the nuclear facility behind the meter, bypassing the wholesale market and securing extremely low-cost power. TeraWulf described Nautilus as the first U.S. Bitcoin mining operation powered entirely by nuclear energy.

The arrangement demonstrated a concept that has since become central to the AI data-center buildout: colocating energy-intensive computing loads directly with large baseload generation assets.

That experiment later evolved into something much larger. In 2024, Talen repurchased TeraWulf’s stake in the Nautilus venture and shifted its strategy toward supplying power to hyperscale data centers. The company sold its adjacent Cumulus data center campus to Amazon Web Services for $650 million, enabling AWS to develop a large campus connected to the Susquehanna plant.

The progression illustrates how prime power-adjacent sites are being repriced in the AI era. Locations once used for Bitcoin mining are now becoming anchor points for hyperscaler data infrastructure.

Retired Reactors Return to the Grid

The new economics are already reversing retirement decisions.

Constellation’s restart of the Crane Clean Energy Center marks one of the most visible examples. The project is supported by a 20-year Microsoft contract and backed by a U.S. Department of Energy loan guarantee of up to $1 billion from the Federal Financing Bank. The loan carries a 30-year term maturing in 2055 with interest set just 37.5 basis points above U.S. Treasury rates.

Another example is the Duane Arnold Energy Center in Iowa. NextEra Energy Resources is pursuing the recommissioning of the plant, which shut down in 2020. The company has secured a 25-year power purchase agreement for the facility’s full capacity and submitted an application to the Nuclear Regulatory Commission to reinstate the operating license.

If approved, the reactor could return to service as early as 2029.

Even as companies pursue restarts, they are also extending the lifespan of existing facilities. Dominion Energy has received approvals to operate its Surry and North Anna reactors for up to 80 years, while Vistra secured a license extension for its Perry plant through 2046.

Turning Old Reactors Into Bigger Ones

Utilities are also squeezing more capacity out of existing reactors through what the industry calls “uprates.”

These are engineering upgrades that increase a plant’s electricity output without building an entirely new reactor.

Vistra plans to add about 433 megawatts of additional capacity across three plants — Perry, Davis-Besse and Beaver Valley — largely to meet commitments under its long-term agreement with Meta.

Constellation is pursuing a smaller expansion at the Clinton facility, adding about 30 megawatts of additional output as part of its supply arrangement with the social media company.

While incremental, these upgrades highlight a broader shift: existing nuclear assets are increasingly being treated as expandable infrastructure for the data economy.

The Grid Problem AI Created

The surge in nuclear investment ultimately reflects a deeper structural challenge facing power grids.

Utilities across the U.S. are reporting unprecedented electricity demand growth driven largely by data centers.

Dominion Energy, for example, disclosed that data centers now account for roughly 28% of electricity sales in its PJM Dominion zone. Similar demand spikes are emerging in markets such as Texas and the Midwest.

Because hyperscalers increasingly target hourly carbon-free energy — matching clean electricity supply with consumption every hour — nuclear power provides a uniquely valuable resource: reliable, emissions-free generation that operates continuously.

In other words, nuclear power is becoming the backbone of the AI era’s electricity system.

And if the current wave of data center development continues, the industry that once struggled to justify its survival may soon find itself at the center of the world’s fastest-growing energy market.

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It’s not news that public mining hodlers have been selling coins for months. Riot liquidated four times its production in December; Cango sold 4,451 BTC in February, or 60% of its reserves; and Bitdeer cleared out its bitcoin reserves last month.

But the latest round of annual filings this week suggests the pace may be accelerating — and could get even more turbulent ahead.

Fresh disclosures from several mining companies indicate that treasury liquidations picked up sharply after Bitcoin’s post-October slide squeezed margins and pushed mining economics below breakeven. Together, they sold more than 15,000 BTC in five months.

Over the past week, Core Scientific revealed in its latest annual report that it plans to sell all of its roughly 2,500 BTC holdings in the first quarter, with 1,900 BTC already sold in January.

Riot noted that bitcoin’s downward trend "may necessitate the sale of a greater volume" of its bitcoin than previously anticipated, to maintain the liquidity required for ongoing operations and working capital

Even MARA — historically one of the industry’s most aggressive Bitcoin accumulators — has softened its stance. While the company still held more than 53,000 BTC at the end of 2025, it has adjusted its treasury policy to allow sales beyond just newly mined coins.

In other words: the HODL era is quietly loosening.

Miners Are Selling Into a Profit Squeeze

The selling pressure shouldn’t come as a surprise.

Since October, Bitcoin’s average price has slid steadily, pushing mining economics into uncomfortable territory.

Hashprice — the key profitability metric for miners — recently fell below $30/PH/s, a level below the total cash-based hashcost for most public miners, according to TheEnergyMag’s analysis of the latest quarterly filings.

In simple terms: many miners are currently operating at or below breakeven.

The gap between hashprice and hashcost has historically been one of the strongest triggers for treasury liquidation.

And the numbers are starting to show it.

Debt Is Rising — and Bitcoin Is the Collateral

Unlike previous downturns, many public miners entered 2025 with significantly more leverage.

Across the industry, companies tapped credit facilities, Bitcoin-backed loans, and senior secured bonds to fund both operating costs and the massive buildout of AI and high-performance computing (HPC) data centers.

That leverage often comes with Bitcoin collateral requirements.

As of Dec. 31, three major miners — Hut 8, MARA and Riot Platforms — had pledged more than 14,500 BTC combined against loans.

The catch: as Bitcoin prices fall, loan-to-value ratios rise.

With Bitcoin dropping sharply after the new year, these collateral ratios likely increased — meaning additional Bitcoin may already have been pledged to maintain lending thresholds, which are typically set at around 60%.

A Classic Miner Capitulation Signal?

Historically, large-scale miner selling has often coincided with late-stage bear market conditions.

When margins compress and treasuries shrink, weaker miners exit and stronger operators consolidate — setting the stage for the next recovery.

Whether this cycle follows the same pattern remains uncertain.

Bitcoin has already rebounded to around $73,000, lifting hashprice back above $30/PH/s.

But that recovery hasn’t fully restored mining profitability. For most public operators, cashflow remains tight.

Which leaves the industry in an unusual position:

Miners are almost simultaneously selling Bitcoin to survive the present while borrowing aggressively to build AI infrastructure for the future.

If history is any guide, miner capitulation has often marked the end of painful market phases.

But for now, the industry is still very much in the middle of the squeeze.

Regulation News

• Russian Draft Notices Issued to Chinese Digital Asset Workers

• U.S. Nuclear Regulatory Commission Publishes Proposed Rule and Guidance for Fusion Regulatory Framework

Hardware and Infrastructure News

• American Bitcoin to Add 3 EH/s With New S21XP Purchase, Reactivating Drumheller Site

• IREN Expands AI Cloud Capacity to 150,000 GPUs

Corporate News

• MARA and Starwood Form Strategic Partnership to Develop 2.5 GW AI Infrastructure Platform

• TeraWulf CEO Sets Plan to Sell 1.65M Shares Amid $3.2B AI Pivot

• Core Scientific Sold 1,900 BTC in January; to Sell Remaining Bitcoin in Q1

• MARA Expands BTC Sales Flexibility After Mixed 2025 Bitcoin Treasury Results

• Canaan Announces Open Market Share Purchases by CEO NG Zhang and CFO

Financial News

• OpenAI Secures $110 Billion in New Funding to Fuel Global AI Scaling

• Blackstone to Launch Public Entity for AI Data Center Investments

• Applied Digital Targets $2.15B Bond Sale for North Dakota AI Data Center

• Core Scientific Lands $500M Loan at ~7.8% as AI Data Center Financing Boom Continues

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If you want to understand the AI and data center boom in 2026, don’t just look at GPUs, megawatts, or backlog announcements.

Look at the bond market.

Over the past 12 months, more than $33 billion of long-term senior notes have been issued by just a short list of bitcoin mining/AI infrastructure companies, utilities and power producers — and that’s excluding convertible notes. This isn’t equity dilution. It’s hard debt: Fixed coupons; Real maturities; Real interest expense.

And the spread between who pays 4% and who pays 9% tells you almost everything about how the market is underwriting the data center arms race.

The 9% Club: AI and Bitcoin Infrastructure

At the high-yield end of the spectrum, the capital isn’t cheap.

CoreWeave printed:

• $2.0B at 9.25% (May 2025)

• $1.75B at 9.00% (July 2025)

Applied Digital:

• $2.35B at 9.25% (Nov 2025)

TeraWulf:

• $3.2B at 7.75% (Oct 2025)

Cipher Mining:

• $1.4B at 7.125% (Nov 2025)

• $2.0B at 6.125% (Feb 2026)

Cipher’s February deal is interesting. In just three months, its pricing improved by a full percentage point even as it doubled down with a $2 billion issuance. That suggests there’s still appetite for “compute-backed” credit, especially when colocation leases and power contracts are in place.

But zoom out and compare this to regulated utilities and power producers.

The 4–5% World: Incumbent Energy Giants

Now look at the other side of the ledger.

Dominion Energy:

• Multiple tranches between 4.6% and 5.65%

NRG Energy:

• Mostly 4.7%–6.0%

Vistra Corp.:

• January 2026: $2.25B at 4.70% and 5.35%

The Southern Company:

• Several issuances clustered around 4%–5.5%

Constellation Energy:

• $2.75B in January 2026, multi-tranche, largely sub-5% depending on maturity

Same macro environment. Same Treasury curve. Different credit pricing.

The message from lenders is clear: regulated load and contracted generation still get treated as infrastructure. AI and bitcoin, even when attached to long-term offtake agreements, are still treated as growth credit.

The Spread Story is a Credit-Rating Story

If you line these issuers up by coupon, you get a rough risk ladder:

• 4%–5%: Regulated utilities and diversified power producers

• 5%–6%: Stronger independent generators

• 6%–9%: Bitcoin miners and AI infrastructure builders

Regulated utilities and established power producers tend to sit in the investment-grade universe, with long operating histories, predictable (often regulated) cash flows, and deep institutional demand for their paper.

On the other side, the newer “compute” names — especially the ones still scaling, still building, or still proving the durability of their customer base — are typically borrowing as high-yield / speculative-grade credits. Even when they have real contracts, the market still prices in execution risk, refinancing risk, and the reality that capex eats cash before it creates cash.

Why So Much Debt, So Fast?

The common thread isn’t crypto cycles. It’s data center demand.

Utilities are openly revising capital plans upward. Southern now expects a $78.1 billion investment plan through 2030, with $15.9 billion in 2026 alone — explicitly citing projected load growth from data centers. Dominion similarly flagged billions in anticipated long-term debt issuance (between $6B and $9.5B in 2026) to support infrastructure expansion driven by large new data center customers.

On the AI side, the logic is simpler: secure power first, figure out monetization later.

For miners transitioning into HPC, the debt stack is becoming the bridge between legacy bitcoin cash flows and future AI tenancy – assuming there’s still cash flow from bitcoin mining. For AI players like CoreWeave, it’s about scaling ahead of revenue realization under hyperscaler contracts.

Is This a Bubble — or Just a Capex Supercycle?

There’s a bigger question hanging over all of this.

If AI demand holds, these coupons may look entirely rational. Debt gets refinanced lower. Assets appreciate. Power scarcity becomes the bottleneck.

But if AI demand cools — or hyperscaler buildouts lose momentum — the 7%–9% debt stack tied to merchant-exposed compute assets could become burdensome fast, particularly with bitcoin mining economics providing little buffer.

Remember: most of these maturities cluster around 2030–2036. That’s not far away in infrastructure time. This isn’t just a power story anymore. It’s a balance sheet story.

Regulation News

• Trump says he will raise US global tariff rate from 10% to 15%

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Hardware and Infrastructure News

• Bitcoin Difficulty Jumps 15% to Push Hashprice Below $30/PH/s

• Canaan Acquires Cipher’s Stake in Texas Bitcoin Mines in $40M Stock Deal

• Bitfarms Wins Local Approval to Advance Pennsylvania AI Data Center Project

• Fire in Wenatchee, Washington Tied to Bitcoin Mining Activity

Corporate News

• Blue Owl Struggles to Line Up Debt for $4B CoreWeave AI Data Center

• Bitdeer Clears Out Bitcoin Reserves While Refinancing Higher-Cost Convertibles

• Cipher Mining Rebrands as Cipher Digital to Double Down on AI Data Center Leases

• Cipher CEO Sets New 10b5-1 Plan Covering Up to 1.5M CIFR Shares

• NextEra Energy to Raise $2 Billion in Equity Units to Fund Power Projects

Financial News

• Tether Reloads on Bitdeer in $42M Buys After Selling Near 2025 Peak

• CoreWeave Seeks $8.5B Loan as AI Infrastructure Debt Piles Up

• Nvidia Revenue Tops $216B as Blackwell Ramp Lifts AI Data Center Sales

• Hut 8 Pledges 4,533 Bitcoin for $200M Coinbase Loan as BTC Slides

• American Bitcoin Tops 6,000 BTC Holdings After Q4 Production, ATM Buys

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On paper, 14 public bitcoin miners are about to build a small country’s worth of power infrastructure.

In reality, they have roughly 11 gigawatts online today — and about 30 gigawatts more sitting in “pipeline” decks, interconnection queues, and early-stage development plans, according to the chart compiled by TheEnergyMag.

That three-to-one gap is the clearest signal yet that the mining industry’s next cycle won’t be fought only with cheaper or more efficient ASICs or higher uptime, but with something far more contested: who can secure power, finance it, and deliver data-center-grade capacity fast enough to matter.

This is the megawatt arms race of the AI boom—assuming the boom lasts long enough, and demand stays deep enough, for these companies to actually monetize the power they deliver in the first place.

But before we get carried away, it’s worth acknowledging why the bubble question is unavoidable. Every bull market comes with a new narrative that promises to lift the whole sector. In 2017, it was blockchain. In 2021, it was the hashrate arms race. In 2025, it became “AI data centers.” The story changes, the capital follows, and the industry relabels itself — often faster than the underlying business model actually changes.

Riot is a good example of that identity churn. Before 2017, it was a biotech play; then it became Riot Blockchain, rebranded again as Riot Platforms, and now faces pressure from an activist investor to accelerate its pivot away from bitcoin mining toward AI data center colocation. The names and narratives have evolved with the market cycle. The harder part is whether the assets and execution can keep up.

From GPU to ASIC and back to GPU!

The AI boom has turned “pipeline megawatts” into a valuation talking point. But “pipeline” can mean everything from a signed lease and an active construction site to a project in feasibility studies, a grid application, or simply a target a company is marketing. Some of those megawatts will become energized, revenue-generating capacity. Some will slip by years. Some will never materialize, especially if AI demand cools or financing conditions change.

Even if power delivery does catch up, there’s a second issue that doesn’t get enough attention: it’s genuinely difficult to transition from monetizing ASIC hashrate to monetizing data center infrastructure. It’s also striking to watch the industry’s arc—from GPUs to ASICs, and now back to GPUs again, but this time in a completely different business.

Capex aside, the operational and commercial risk is hard to ignore. Unlike bitcoin mining, monetizing GPUs for AI companies or enterprise customers depends heavily on product fit, sales execution, and service delivery. In bitcoin mining, the formula is simple: power plus ASICs produces bitcoin. In AI infrastructure, you can secure the power and still fail to deliver a marketable product—or fail to sell it on terms that meet customers’ expectations. That’s what makes “pipeline megawatts” a more fragile metric.

The 11 GW operational figure is part of the story that already exists. The 30 GW pipeline figure is the story miners are trying to make true. The AI pivot is a real strategic response to hashprice pressure and capital-market incentives, but it also carries the familiar scent of bull-market hype.

If the AI boom sustains, the winners won’t be the companies that announce the biggest pipelines. They’ll be the ones that can close the infrastructure gap—turning planned megawatts into energized capacity, energized capacity into critical IT load, and critical IT load into contracted revenue—without stretching their balance sheets or overpromising timelines. None of this makes the pivot impossible; it just makes it harder, and slower than the narrative often assumes.

Hardware and Infrastructure News

• HIVE Signs $30M GPU Cloud Contracts to Expand Canada AI Data Center - TheEnergyMag

• Caturus Secures 20-Year LNG Offtake Agreement with Aramco Trading for Louisiana Export Facility - TheEnergyMag

• Mon Power and Potomac Edison Announce New Natural Gas Power Plant in West Virginia - TheEnergyMag

• Transource Energy and FirstEnergy Transmission Joint Venture Approved for Major Electric Transmission Project in Central Ohio - TheEnergyMag

• Soluna Expands Blockware Partnership, Adding 6 MW Bitcoin Mining Capacity at Project Dorothy 1 - TheEnergyMag

• Meta to Deploy Millions of NVIDIA GPUs as AI Buildout Pushes CapEx Higher - TheEnergyMag

• Yotta to Build $2 Billion AI Hub in India Using Nvidia Blackwell Chips - TheEnergyMag

• Tata Group, OpenAI Plan AI Compute Hub in India - TheEnergyMag

Corporate News

• OpenClaw founder Steinberger joins OpenAI, open-source bot becomes foundation - Reuters

• IREN Appoints John Gross as Chief Innovation Officer to Enhance Data Center Engineering - TheEnergyMag

• Portland General Electric Acquires Washington Utility Operations from PacifiCorp - TheEnergyMag

• 1606 Corp. Signs Term Sheet to Acquire 55 MW Texas Power Generation Facility and 50,000 Sq. Ft. Data Center-Ready Infrastructure Site - TheEnergyMag

• Activist Starboard Pushes Riot to Speed Up Shift From Bitcoin Mining to AI Data Centers - TheEnergyMag

• Core Scientific Board Set for Overhaul Under Two Seas Pact - TheEnergyMag

Financial News

• Constellation Energy Surges 10% This Week on Data Center Deals and Analyst Upgrades - TheEnergyMag

• Blackstone Commits Up to $1.2 Billion to Neysa for India’s Domestic AI Infrastructure Build-Out - TheEnergyMag

• HIVE Digital Technologies Reports Record Q3 Revenue Driven by Bitcoin Hashrate Growth - TheEnergyMag

• Bitdeer Plans New $300M Convertible Bonds Aimed at Deleveraging - TheEnergyMag

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A quick note before we dive in: TheMinerMag is now TheEnergyMag.

What began as focused coverage of Bitcoin mining has expanded into something broader. AI-driven data center demand is reshaping utilities, capital markets and long-term infrastructure investment. The center of gravity has shifted from pure hashrate to power.

TheEnergyMag reflects that evolution. Read more here.

The scale of capital now flowing into AI infrastructure is starting to look less like a typical tech upcycle and more like a generational buildout — one that stretches from Bitcoin miners to regulated utilities to Big Tech itself.

Over the past few weeks alone, we’ve seen a rare 100-year bond, a Bitcoin mining giant deploy more capital in one year than it spent in the three years after its IPO — and two of the largest U.S. utilities line up tens of billions in regulated investment and fresh debt to support rising data center load.

This isn’t incremental expansion. It’s a balance-sheet shift.

IREN’s spending curve bends sharply upward

Start with IREN.

In its latest quarter, net spending on property, plant and equipment topped $800 million — significantly above prior quarters. But the annual view is even more telling: IREN’s total net PP&E spending in 2025 alone exceeded the combined total from 2022 through 2024.

In practical terms, the company deployed more capital in a single year, building AI data center infrastructure and procuring GPU hardware than it spent across three years expanding its Bitcoin mining fleet post-IPO, according to TheEnergyMag’s analysis.

That shift highlights how different the AI buildout looks from the last mining cycle. High-density GPU clusters, substation upgrades, advanced cooling and long-duration interconnections resemble utility-scale infrastructure more than modular ASIC deployments. The capex profile follows accordingly.

Duke’s $103B plan — and the load behind it

On the utility side, Duke Energy is openly framing this as a multi-year expansion cycle.

The company outlined a $103 billion five-year capital plan, which CEO Harry Sideris described during the earnings call as “the largest fully-regulated capital plan in the industry focused on critical energy infrastructure investments that strengthen the system and serve increasing load.”

That “increasing load” is tied in part to AI and advanced manufacturing demand.

Sideris also stressed that as investment needs accelerate, “the cost of energy has been and will remain a key focus for Duke Energy.” In a news release accompanying the results, he said the company is entering the year “with incredible momentum,” adding that the fundamentals of the business “have never been stronger” and pointing to operations in some of the most attractive jurisdictions in the country.

In 2025 alone, Duke broke ground on 5 gigawatts of new dispatchable generation. Management extended its long-term adjusted EPS growth target of 5% to 7% through 2030, supported in part by contracted demand.

The quarterly results also reflected the other side of heavy capital spending: higher depreciation and interest expense tied to a growing asset base.

NextEra Energy has been equally active in capital markets.

On Feb. 7, it announced raising $1.3 billion in new debt across two tranches. On Feb. 10, its subsidiary issued another €1.3 billion in euro-denominated debentures. The structure — blending intermediate and long-dated maturities — mirrors how large utilities fund long-lived generation and grid assets.

While proceeds were not specifically itemized, the activity comes as NextEra expands its partnership with Google Cloud to co-develop multiple gigawatt-scale data center campuses in the U.S., including land, interconnection and dedicated generation resources.

Google sells a century

At the other end of the stack, Alphabet Inc. — parent of Google — sold a rare 100-year bond as part of a $31.51 billion global debt raise.

The century tranche raised 1 billion pounds at a 6.125% coupon and reportedly drew demand nearly ten times the amount offered. The broader transaction included sterling, Swiss franc and U.S. dollar bonds, with maturities stretching from three years out to 2066.

Century bonds are typically associated with governments or regulated utilities. Analysts noted that ultra-long-term issuance of this kind signals a pivot from asset-light models toward long-term infrastructure.

Alphabet’s deal stands out not just for its maturity but for its scale. Alphabet, Microsoft, Amazon and Meta are collectively expected to spend at least $630 billion this year, with most of that directed toward data centers and AI chips.

In that context, a 100-year bond begins to look less like a novelty and more like a financing tool for infrastructure measured in decades.

Viewed together, the signals are clear. Compute operators are spending at levels that eclipse their prior mining cycles. Utilities are formalizing record capital plans and tapping debt markets to expand generation and grid infrastructure. Earnings calls now routinely reference AI-driven load growth alongside traditional drivers.

The AI boom is not just reshaping revenue mix — it is redefining the scale and duration of capital deployment across the energy-compute stack.

Hardware and Infrastructure News

• Bitcoin Miners Could Face Crisis After BTC Price Falls 50% From Peak - Decrypt

• Bitcoin Mining Difficulty Saw Biggest Drop Since 2021 China Ban - TheEnergyMag

• Soluna Begins Energization of Project Kati 1, adding 83 MWs to Total Capacity - Link

• Bell Canada Advances AI Fabric Expansion With Proposed 160-Acre Campus South of Regina - TheEnergyMag

Corporate News

• Bitfarms Deleverages, Unveils Keel Rebrand as Bitcoin Mining Margins Sink Below $30/PH/s - TheEnergyMag

• Bitcoin Miner NFN8 Files Chapter 11 After Fire, Lease Strain as Hashprice Hits Record Low - TheEnergyMag

• BlockFills Suspends Client Withdrawals Amid Market Volatility - TheEnergyMag

• Cipher Welcomes Thomas Duda to the Company’s Board of Directors - Link

• Anthropic says it will pay 100% of the grid upgrade costs tied to its AI data centers - Business Insider

Financial News

• NextEra Raises $1.3B in Debt as AI Data Center Power Demand Accelerates - TheEnergyMag

• Cango Sells 4,451 BTC, Cuts Bitcoin Reserves by 60% to Repay Loan - TheEnergyMag

• Canaan revenue more than doubles in Q4 as bitcoin miner grows treasury to record levels - The Block

• Cipher Mining and TeraWulf are buys, MARA a sell, as Morgan Stanley begins bitcoin miner coverage - CoinDesk

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