Scale and cost-efficiency

Building the GNUS.ai marketplace as a Web3 protocol eliminates centralized overheads, allowing for unprecedented scalability and reduces barriers to entry for new supply participants. This enables GNUS.ai to connect potentially every computing device globally, creating a decentralized network that scales far beyond the limits of traditional providers. By forming a network from the available billions of worldwide consumer compute devices, GNUS.ai offers on-demand access to boundless compute supply at a transparent and minimal cost—often as low as $0.01 per hour or less.

GNUS.ai's pricing is driven by an automated supply and demand function, ensuring that costs remain at least 80% lower than other systems. This dynamic pricing structure allows GNUS.ai to stay highly competitive while offering users massive savings. Unlike traditional providers with centralized infrastructure and inflated costs, GNUS.ai operates with no CapEx and minimal OpEx, further driving down prices. Operational expenses are taken as a small percentage of the already low hourly cost, enabling the system to approach near-zero costs.

This approach completely redefines cost barriers associated with scaling machine learning workloads, as GNUS.ai guarantees users access to affordable compute without compromising on scalability. By efficiently utilizing global compute resources and capturing latent capacity, GNUS.ai offers a flexible, decentralized solution that meets the needs of both developers and end-users, all while maintaining cost advantages unmatched by other systems.

Provider

Approximate hourly cost for ML training work (V100-equivalent)

Scalability

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