Quantus launched its mainnet on September 9 with post-quantum cryptography designed to protect against future attacks from sufficiently powerful quantum computers. The network uses ML-DSA, the digital-signature standard finalized by the U.S. National Institute of Standards and Technology in 2024, specifically relying on ML-DSA-65 and ML-DSA-87 to authenticate transactions.
Most cryptocurrency networks still rely heavily on elliptic-curve cryptography, which could theoretically be undermined by a sufficiently capable quantum computer. Quantus estimates that approximately $2.7 trillion of crypto market value remains exposed to this long-term risk. NEAR and Algorand have introduced post-quantum transaction security, but neither has completed a protocol-wide transition.
Quantus co-founder and CEO Christopher Smith stated: "We have known for over 30 years that if anyone builds a sufficiently large quantum computer, then elliptic curves will fail." The network features privacy-preserving transactions through Wormhole, a 21 million coin supply cap, and open proof-of-work mining from launch with no built-in mining advantage for Quantus Labs.
The mainnet targets 12-second blocks and achieved testing throughput of up to 430 transactions per second. However, post-quantum security comes with trade-offs: a Quantus ML-DSA transaction is approximately 7 kilobytes compared with about 100 bytes for a typical Bitcoin transaction. The network addresses this through aggregating activity and posting succinct proofs onchain.
Key institutional players, including Grayscale, Fidelity Investments, and Bitmine's Tom Lee, have previously warned that cryptocurrencies face future quantum risks due to lack of planning. Before launch, Neodyme, Eiger, Hashcloak, and V12 reviewed the Quantus network, while Immunefi hosted a public audit competition.
The timing reflects broader concerns about cryptographic security. In July, Anthropic reported that Claude Mythos Preview improved the best-known attack on HAWK, a post-quantum signature candidate, after approximately 60 hours of work, demonstrating how artificial intelligence can accelerate the discovery of cryptographic weaknesses.
