🪙SOGNI Token vs Spark Points

Learn the difference between Spark Points and SOGNI Tokens

SOGNI Token

SOGNI is a fully transferable ERC-20 utility token on the Base blockchain, with availability extended to Etherlink. It powers the decentralized economy behind the Sogni protocol, supporting compute providers, developers, and the community. Some of the utilities of the SOGNI token are the following:

• Artists can use SOGNI to pay for rendering and creative services on the Supernet. ‍ • Workers earn SOGNI by sharing compute and powering generation jobs. Earnings can be claimed and withdrawn at any time. ‍ • You can stake SOGNI to boost your priority in queues, visibility, rewards, and unlock future perks. ‍ • SOGNI holders also help shape the future of the network through community votes and decisions.

Spark Points

Spark Points are part of a prepaid system designed for artists who just want to create, no wallets or crypto experience needed.

• Pay for rendering with either Spark Points or SOGNI. ‍ • One Spark Point = one base job. The value stays stable.

Base Job = SDXL Stable Diffusion Model at 20 steps.

• Recharge your creativity, instantly. Buy them right inside the Sogni apps with Apple Pay, credit cards, and other traditional methods. ‍ • You can also earn Spark Points through onboarding tasks, daily boosts, and community quests. ‍ • While ownership is recorded on-chain, Spark Points are not transferable between users and can only be spent through approved platform contracts.

Unified rewards, seamless experience.

No matter how a job is paid for, with SOGNI or Spark Points, workers always earn rewards in SOGNI. This design makes Sogni accessible to everyone, while preserving a unified, decentralized reward system that powers the network behind the scenes.

How are Spark Point payments calculated vs Sogni Token?

Behind the scenes the cost of jobs on the Supernet are measured in units of GPU-time with the amount of GPU-time required to do one standard HQ render being pegged to an industry competitive rate of $0.005. If a job takes 2x the GPU-time to complete, as configured, than as a standard render then it would cost $0.005 * 2 = $0.01. When paying this rate via SOGNI token the amount of tokens required may fluctuate as the USD value of each SOGNI token will reflects the real-time average market price across exchanges. Spark Points are introduced to avoid this exposure to price fluctuations and keep things simple for Artists. One Spark Point is always pegged to the cost of a base render job—and that never changes. If the job is 2x the GPU-time cost, it reliably costs 2 Spark Points for example.

Benefits of using Spark Points:

• Allows Sogni to give a fixed number of free daily render and other credits to users without the amount of jobs those credits can do changing based on SOGNI market price. (50 free render tokens a day always equal 50 renders)

• Allows users to conveniently buy render credits in "Spark Packs" via friendly in-app payment methods

• Securing the economy: Unlike with SOGNI, Spark is "Soulbound" and can’t be transferred or sold once earned, only used to pay for Supernet generations by the account receiving them. This means Sogni can give more generous rewards, Developer & Creator Grants, etc, knowing these tokens must be used on the network and can’t be farmed and dumped.

Benefits of using SOGNI Tokens:

• SOGNI tokens will continue to be the main utility token on the protocol, used for many purposes beyond Supernet inference payments to workers, including future DAO voting

• SOGNI will be required to stake for worker reward boosts and participating in the staking leaderboard

• Paying for jobs with SOGNI gives a 10x multiplier to leaderboard points. Paid-for Spark Points will give a 7x multiplier, and free Spark will give a 1x multiplier.

Using Spark Points

You can toggle betwen paying for Sogni Supernet jobs in Spark Points or in SOGNI tokens by clicking the job cost text area and then clicking on the "SOGNI Token" or "Spark Points" button bar.

Keep in mind that the cost of your jobs can still vary based on the gpu-time increase or decrease as you change parameters that can make jobs take more or less time:

• The number of steps.

• The type of model you are using (SDXL, Standard, etc.).

• The number of requested previews.

• The use of an additional ControlNet model.

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