On January 19, in the UTC+8 time zone, the Bitcoin network's hash rate fell approximately 15% from its previous high, with its 7-day moving average dropping to about 993 EH/s. This change has brought the competition for electricity, which was originally buried deep in data centers, to the forefront. As the load on the same power line within the same park begins to swing between Bitcoin mining and AI training and inference, miners, hash rate service providers, and investors are all reassessing who should receive every kilowatt-hour of electricity they have. This round of hash rate adjustment is not merely a backdrop of price fluctuations; rather, it is a collective re-evaluation of "which form of hash rate should be prioritized for electricity supply" under the combined pressures of electricity prices, regulation, and AI demand, leaving many open questions regarding the long-term security of Bitcoin and miners' survival strategies.
Hash Rate Slips from High: Miners Begin…
Looking back from the peak in October last year, the Bitcoin network's hash rate rose steadily before starting to decline. By January 19, the 7-day moving average had slipped to about 993 EH/s, corresponding to a nearly 15% drop. This pullback from the peak has not been accompanied by extreme price crashes but resembles a slow release of structural pressure over several months: mining machines in high-cost areas have been shutting down, some older models have been permanently retired, and others have been pushed into a "waiting for transformation" gray area. Behind the hash rate curve is the reality that miners are beginning to use electricity meters rather than just Bitcoin spot prices to gauge their next decisions: when the same electricity can be directed to AI clusters, sold as hash rate contracts, or used to fulfill cloud service orders, the mining model that solely relies on block subsidies and transaction fees is increasingly unable to secure all racks and substation facilities. As the hash rate declines, voices in the market regarding "AI computing services siphoning electricity from miners" have begun to increase, examining the decline in hash rate and the migration of electricity under the same narrative.
The Battle for Electricity: How AI Hash Rate…
If we break down the assets of a mature mining site, we find that they overlap significantly with the key elements of AI computing infrastructure: large-scale, stable industrial electricity access, data center spaces equipped with cooling and fire safety capabilities, and well-established operation and maintenance teams along with distribution systems. These assets, once seen as "tailored for Bitcoin," are now also the essential foundation urgently needed by AI training clusters and inference nodes. For this reason, the view that "AI computing services are forming a siphon effect on miners' electricity" has begun to gain traction within the community—if the same electricity and space can be directed towards AI hash rate leasing, model training, or inference services, miners see a more imaginative revenue curve, which also implies more complex risk exposures. For some miners with low electricity prices and early infrastructure, switching part of their racks or electricity metrics to AI business can provide external cash flow during periods of Bitcoin price volatility and compressed mining profits, even enjoying premiums brought by increased AI demand; however, at the same time, issues such as hardware depreciation cycles, AI client stability, and operational capability migration remind them that this is not a trial path that can be "turned back at any time," and any excessive bets may expose a situation where both businesses struggle to sustain themselves when market conditions reverse.
Whale Betting Direction: From ZEC Blood…
On the infrastructure side, miners are entangled in the direction of electricity; meanwhile, on the trading floor, a whale known for aggressive shorting has expressed his judgment on the flow of hash rate and capital through his positions. Public addresses show that this whale once faced an unrealized loss of about $21 million while shorting ZEC, enduring paper pressure for a long time before finally waiting for the price drop to turn a profit. This experience has earned him the label of "the largest ZEC short" in the market, prompting greater attention to each of his subsequent directional choices. Currently, the address 0xd475… holds a short position of about $1.8853 million in MON, with an unrealized profit of about $685,500. On social media, "the largest ZEC short's successful operation on MON" has become a frequently referenced topic. Compared to betting on a single cryptocurrency, this whale has chosen to migrate short positions across multiple targets, which many analysts interpret as a bet on broader trends in hash rate and capital—when miners, electricity, and infrastructure begin to tilt towards AI, some crypto assets traditionally tied to the "mining narrative" may face repricing pressure.
Interwoven Narratives: From Mining Sites to Trading Floors…
Connecting the timeline of Bitcoin's hash rate decline from its peak with this whale's short positioning in ZEC and MON reveals a more dynamic story of resource and price competition: on one side are the real-time power readings in data centers, and on the other, the constantly adjusting margin curves in the derivatives market. When the underlying revenue expectations of electricity and hardware are rewritten by AI business, the valuation anchors of related crypto assets are also being subtly adjusted. The repricing of infrastructure resources first manifests as changes in the thresholds for turning mining machines on and off and the bargaining chips in electricity price negotiations, which then transmit to the spot market through miners' sell-offs or reductions, and are amplified in futures and perpetual contracts by whales holding long-term short positions and market-making institutions. Thus, during the same period, there has been a rhythmic downward adjustment of network hash rate, as well as systematic shorting of specific "old mining narrative" assets, but whether there is a necessary causal relationship between the two remains unsupported by sufficient data and long-term samples. The view on whether "AI hash rate will lead to a long-term decline in mining business" currently remains at the debate level, with optimists believing that miners will eventually transition en masse to AI hash rate service providers, while conservatives emphasize the irreplaceability of mining in decentralized security, with both sides lacking definitive evidence.
The Overlooked Cost Reality: Electricity Prices…
Regardless of which side one stands on, the unavoidable reality is that electricity prices and regulation are reshaping miners' cost curves. In some regions, rising electricity costs, increased energy consumption scrutiny, and higher compliance requirements have continuously compressed the profit margins of the "electricity solely from mining" model, prompting miners to actively seek external revenue sources such as AI hash rate to find a second cash flow channel for their data centers and electricity. From the miners' perspective, the opportunity window for transitioning to AI services mainly appears in several scenarios: first, utilizing idle or marginal hash rate to undertake small-scale AI inference tasks; second, under the demand of large clients, specifically modifying parts of data centers for AI training; third, in regions with compliant electricity and relatively friendly policies, directly investing new capital into hybrid clusters compatible with both AI and mining. However, once this transformation begins, it can easily lead to path dependence—operation and maintenance teams become familiar with AI cluster management, business departments become more accustomed to signing contracts with tech companies, and capital focuses on the growth potential of AI-related orders, disrupting the decision-making framework that originally relied solely on Bitcoin prices as a compass. Meanwhile, due to the lack of publicly available and transparent quantitative data, it is challenging to determine how much hash rate has "flowed out" of the mining sector and in what manner, making it impossible to accurately assess the specific impact of hash rate decline on network security. These gaps force market participants to make decisions under incomplete information and remind observers to remain sufficiently cautious when interpreting trends.
New Balance of Bitcoin Hash Rate: Miners and…
In the short term, Bitcoin's hash rate has fallen 15% from its peak, with the 7-day average dropping to about 993 EH/s. At the same time, discussions around "AI computing services siphoning electricity from miners" have rapidly heated up, forming a temporary pattern of electricity resource redistribution: Bitcoin is no longer the "sole buyer" of all electricity but is merely one of the participants competing alongside new forms of hash rate demand such as AI. In the future, miners are more likely to continue dynamically rebalance between Bitcoin mining and AI services: when coin prices and transaction fees strengthen, they will increase hash rate back to the network to obtain higher block rewards; when AI orders and hash rate leasing prices rise, they will tilt marginal electricity and machines towards AI clusters, using external cash flow to hedge against the cyclical fluctuations of mining business. The key variables determining the position of this balance line will not only be the price of Bitcoin but also the level and volatility of electricity prices, the length of hardware return cycles, the tightness of the regulatory environment, and whether AI demand can maintain high prosperity over a longer time dimension. Until these variables are firmly established, the electricity competition between Bitcoin and AI will remain an open drama, with miners, power grids, and capital all seeking their own safety boundaries and profit peaks.
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