Earn Points & Rewards

Points are the heartbeat of Zusama’s reward engine.

Earn Points & Rewards Architecture

1. Point Accrual Mechanism

Within the Zusama ecosystem, Points function as a non-transferable performance metric representing measurable on-chain and off-chain contribution.

Participants accumulate Points through verifiable protocol-aligned activities:

A. Infrastructure Contribution

• Operating active nodes (Browser, VPS, Partner)

• Maintaining validated uptime (PoU)

• Submitting high-quality model updates (PoT)

• Sustaining peer network connectivity (PoC)

B. Data & AI Contribution

• Participating in dataset validation workflows

• Providing structured model feedback

• Contributing to training accuracy improvements

C. Network Growth

• Referring new contributors who successfully activate nodes

• Supporting verified onboarding cycles

D. Ecosystem Engagement

• Completing governance quests

• Participating in protocol campaigns

• Executing community-aligned tasks

All Point generation events are:

• Cryptographically verifiable

• Tracked via smart contracts

• Time-bound within a defined Reward Round

2. Reward Conversion to $ZUS

At the conclusion of each Reward Round:

1. The protocol aggregates the Total Network Points

2. The round’s allocated Reward Pool ($ZUS) is finalized

3. Each participant receives a proportional distribution

Reward Allocation Formula

User Reward=User PointsTotal Network Points×Reward Pool(Round)User\ Reward = \frac{User\ Points}{Total\ Network\ Points} \times Reward\ Pool_{(Round)}User Reward=Total Network PointsUser Points​×Reward Pool(Round)​

This ensures:

• Fair proportional distribution

• No fixed emission per user

• Reward scaling aligned with real network contribution

Lucky Bonus Allocation

To stimulate continuous participation:

• 1–3% of each Reward Pool is reserved as a Randomized Lucky Bonus

• Distributed among active contributors within the round

• Eligibility requires minimum activity thresholds (anti-sybil safeguard)

This mechanism increases retention without distorting proportional fairness.

Dynamic Conversion Logic

The conversion ratio between Points and $ZUS is not static.

It is dynamically calibrated based on:

• Network-wide participation volume

• AI training output performance

• Token velocity metrics

• Market liquidity conditions

• Emission sustainability thresholds

This adaptive model prevents:

• Over-inflation

• Reward dilution during high participation spikes

• Unsustainable token emissions

All rewards are:

• Automatically distributed

• Sent directly to the connected wallet

• Settled before the next Reward Round begins

3. Reward Boost Level System

Zusama integrates a Level-Based Reward Multiplier Framework designed to incentivize long-term protocol alignment.

Level Progression Criteria

Users advance through Levels by:

• Maintaining consistent node uptime over multiple rounds

• Achieving high PoT validation scores

• Completing verified ecosystem tasks

• Successfully onboarding active referrals

• Sustaining non-malicious behavior history

Level Multiplier Logic

Each Level applies a multiplier to the user’s base reward:

Final Reward=Base Reward×Level MultiplierFinal\ Reward = Base\ Reward \times Level\ MultiplierFinal Reward=Base Reward×Level Multiplier

Where:

• Base Reward is calculated via proportional formula

• Multiplier reflects long-term commitment

• Higher Levels unlock increased reward efficiency

Level	EXP Required	Reward Boost
Iron	0 EXP	0%
Bronze	500 EXP	+2%
Silver	1,000 EXP	+4%
Gold	2,000 EXP	+6%
Platinum	3,500 EXP	+8%
Diamond	5,000 EXP	+10%
Legend	10,000 EXP	+12% (max)

Level progression is achieved by consistent node uptime, completed tasks, and successful referrals.