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Crypto miners are pivoting to AI workloads as profitability drops, while rising chip prices from TSMC threaten hardware costs for both sectors.
Cryptocurrency mining firms are increasingly repurposing their graphics processing units (GPUs) for artificial intelligence workloads as the profitability of traditional mining declines. Companies such as IREN are aggressively expanding their GPU fleets to capture AI cloud demand, while rising semiconductor manufacturing costs pose new challenges for the sector [1, 2].
Key takeaways
Bitcoin mining firm IREN is actively transitioning its business model, announcing the procurement of 4,200 Nvidia Blackwell B200 GPUs for its facility in Prince George, Canada [1]. This acquisition brings the site's total GPU count to 8,500, comprising a mix of H100, H200, B200, and B300 models [1]. While the company continues to mine Bitcoin, it is winding down those operations to divert cash flow toward its AI cloud business, a strategic shift that contributed to a 304% surge in its stock price since April [1].
Similarly, other crypto miners are exploring AI to recoup heavy hardware investments. Hut 8 and Hive Blockchain have revamped operations to support AI workloads after spending millions on GPUs during the crypto boom [2]. Hive Blockchain, which spent $66 million on Nvidia GPUs in 2021, reportedly aims to generate $20 million from AI work by 2025, up from $1 million in 2022 [2]. This pivot leverages the parallel computing power required for both crypto mining and AI model training, though not all mining GPUs are considered suitable for high-end AI tasks [2].
The financial landscape for GPU mining is also being shaped by changes in the semiconductor supply chain. TSMC, the world's largest chipmaker, is preparing to implement price increases for its most advanced processors due to rising component costs and AI demand [3]. The company forecasts a potential 15% increase on 3nm wafers in the second half of 2026, with additional hikes of 5-10% anticipated for 2027 [3].
These price increases are expected to ripple through the market, affecting both AI servers and crypto mining rigs [3]. TSMC fabricates the custom ASICs used for Bitcoin mining and the high-end GPUs used for AI training [3]. Consequently, manufacturers like Bitmain, MicroBT, Nvidia, and AMD may face higher production costs, which could eventually be passed on to buyers of mining hardware [3].
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GPUs contain thousands of smaller cores optimized for simultaneous, repetitive operations, allowing them to process hashing workloads much faster than the sequential processing strengths of CPUs.
Ethereum's switch to a proof-of-stake algorithm made GPU mining for that network economically infeasible, leading many miners to sell their equipment or attempt to pivot to other, often less profitable, proof-of-work coins.
The migration from crypto mining to AI represents a critical adaptation for firms holding depreciating GPU assets following Ethereum's shift to proof-of-stake and a drop in crypto values [2, 4]. However, this strategy faces hurdles, including the need for greater maintenance, bandwidth, and competition with established cloud giants like Google and Microsoft [2]. Meanwhile, the rising cost of chip fabrication threatens to increase the barrier to entry for both new miners and AI infrastructure providers, potentially squeezing margins across the industry [3]. Despite these shifts, GPU mining remains a relevant method for specific altcoins such as Kaspa and Ergo, which rely on algorithms different from Bitcoin [4].
AI-assisted synthesis by the TrendWatcher Editorial Desk · sourced from 4 outlets · Jun 12, 2026 · How we report
Profitability is impacted by the amount of cryptocurrency rewards earned, which for Bitcoin are pre-programmed to halve every four years or after every 210,000 blocks.
Yes, GPU mining consumes significant amounts of electricity, and reports have noted that a large percentage of the energy used for mining has been generated by fossil fuels, contributing to carbon dioxide emissions.