Bitcoin mining difficulty jumps second time as miners settle offshore

The mining difficulty of Bitcoin (BTC) took a dive after China announced a crackdown on mining operations, which at its peak, contributed to three-quarters of the global hashrate. 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 geographies, the Bitcoin ecosystem witnessed a 13.77% increase in mining difficulty in two consecutive jumps, exceeding 15 terahash (T) for the first time since the 2nd week of June. The next adjustment is expected to commence on August 27, estimated to surge the difficulty to 15.63 terahash.

Before China’s crackdown on local miners, Bitcoin’s mining difficulty peaked at 25 terahash. 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 towards Bitcoin mining has reduced to nearly 46% while the United States picked up the slack, hosting almost 17% of the global mining hashrate.

In a CNBC coverage on this 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 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.”

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 United States came forward as the best options for migrating Bitcoin miners. As Cointelegraph reported, Bitcoin’s rising hash rate would eventually translate into higher computational costs.

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