The mining difficulty of the Bitcoin network took a dive after China had announced a crackdown on mining operations, which at its peak contributed to three-quarters of the global hash rate. The latest data from BTC.com shows an ongoing spike in Bitcoin’s mining difficulty starting from June 17, 2021.
As miners from China slowly settle down in crypto-friendly countries, the Bitcoin ecosystem witnessed a 13.77% increase in mining difficulty in two consecutive jumps, exceeding 15 terahashes (TH) for the first time since the second week of June. The next adjustment is expected to commence on Aug. 27, estimated to surge the difficulty to 15.63 TH.
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Before China’s crackdown on local miners, Bitcoin’s mining difficulty peaked at 25 TH. The sudden decline in the number of Chinese miners had lessened the competition in confirming blocks. This allowed the existing miners on the network to make higher profits. Data from Statista shows that China’s contribution toward Bitcoin (BTC) mining has reduced to nearly 46%, while the United States has been picking up the slack, hosting almost 17% of the global mining hash rate.
In a CNBC story on the matter, Quantum Economics crypto analyst Jason Deane highlighted that the network’s latest difficulty adjustment mechanism has made it 7.3% less profitable to mine Bitcoin.
Concluding the discussion, Mike Colyer, CEO of Foundry — a New York-based digital currency group — said:
“There is an enormous amount of machines coming out of China that need to find new homes.”
Colyer also believes that the new generation of mining rigs is more efficient and would “double the hash power for the same amount of electricity.”
Related: Bitcoin hash rate rebounds as major miners are coming back online
China’s move against Bitcoin mining was credited to energy concerns due to the electricity consumption of mining operations. Following the crackdown, Canada, Kazakhstan, Russia and the U.S. came forward as the best options for migrating Bitcoin miners. As Cointelegraph reported, Bitcoin’s rising hash rate will eventually translate into higher computational costs.
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