Nillion’s NIL Down 12% After Debut; Analyst Claims Network’s ‘Blind Computing’ Ensures Data Privacy, AI
Omkar Godbole | Edited by Parikshit Mishra , Mar 25, 2025 6:38 AM UTC
Private computing and storage network Nillion, known as the “blind computer,” launched its mainnet and native token NIL on Monday.
However, the token’s market cap has fallen 12% in the first 24 hours amid ongoing listings on major exchanges such as South Korea’s Bithumb and analyst optimism about the project’s long-term prospects.
NIL debuted with a total supply of 1 billion, of which 19.52% or 195.15 million NIL were distributed to the community on the first day, resulting in an initial market cap of just over $165 million.
Since then, its market value has fallen 12% to $144.93 million, according to Coingecko data, with the token trading for 74 cents on major exchanges like Binance, Gate.io, MEXC, Bitget, and others.
On Tuesday, Bithumb, one of the largest cryptocurrency exchanges in South Korea where there is high interest in altcoins, announced the listing of the NIL-Korean won pair on its platform.
Nillion is a decentralized platform designed to provide private storage and processing of valuable data. It operates on the same principle as blockchains that decentralize transactions.
There is one caveat, however. Unlike blockchains that focus on transparent ledgers, Nillion uses Nil Message Compute (NMC), which allows computations to be performed on encrypted data without revealing (decrypting) it, ensuring that no node or party has access to sensitive information.
The network architecture combines the nilChain coordination layer and Petnet, with the latter using privacy-enhancing technologies such as multi-party computation, fully homomorphic encryption, and trusted computing environments to protect data.
These so-called blind calculations are in stark contrast to traditional methods that require decryption before processing, which exposes sensitive data such as personal health or financial information to security risks and abuse.
Nillion solves the persistent problem of data privacy and trust in areas such as artificial intelligence (AI), personal assistants and AI in healthcare, private order books in decentralized finance, and many more.
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