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Yuga Labs’ Highly-Anticipated Twelvefold Bitcoin NFT Auction Bidders Spent Huge $16.5M



Reports said that Yuga Labs’ highly-anticipated Twelvefold Bitcoin nonfungible token (NFT) auction has come to a close. 288 successful bidders spent a huge $16.5 million worth of BTC to acquire pieces from the limited collection.


It has been reported that the collection, featuring 300 unique generative art pieces, generated significant buzz and received over 3,000 bids within 24 hours. TwelveFold generated 3,246 total bids during its 24-hour auction on Monday.


However, the highest bid was 7.1159 BTC, approximately $159,500, while the lowest successful bid was 2.2501 BTC, or slightly over $50,000. The top 288 bidders will receive their inscriptions within the week. The company has previously released NFTs only on the Ethereum blockchain, with collections featuring at least 10,000 NFTs. TwelveFold is a 300-count limited series.


The report said that Yuga Labs has taken a bold step away from its previous work with the generative art pieces in TwelveFold NFTs. These unique pieces are inscribed on the Bitcoin blockchain via Ordinals, a new method of committing art to Bitcoin. Each piece is a 12×12 grid, combining 3D graphics and hand-drawn features. Unlike other NFT collections, the code will generate each of the 288 pieces won at auction, ensuring that each piece is unique.


Likewise, the higher bidding price does not influence the quality of the piece, but the pieces are numbered and generated based on their rank in the bidding process. Not everybody was happy with the bidding process for Yuga Labs’ TwelveFold collection. In order to participate, bidders had to deposit the full amount of their bids directly with Yuga.


Thus, Casey Rodarmor, creator of Bitcoin Ordinals quickly condemned the process. Rodarmor berated Yuga for creating a system that could be easily manipulated by project creators to steal funds from bidders. Yuga promised to return rejected bids within 24 hours of the auction’s end.


Source: NFT Evening


 

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