Fee Model
Transaction fee structure, distribution, and dynamic pricing.
Fee Schedule
| Transaction Type | Base Fee | Use Case |
|---|---|---|
| Standard transfer | $0.0035 | Wallet-to-wallet payments |
| Smart contract call | $0.0175 | dApp interactions, DAO proposals |
| IoT data packet | $0.000125 | High-frequency sensor data |
| AI inference query | $0.0025 | Decentralized ML services |
Dynamic Fee Multiplier
Fees adjust dynamically during network congestion, up to 100x the base fee.
Congestion thresholds:
| Metric | Threshold | Effect |
|---|---|---|
| Mempool size | > 1,000 pending TX | Fee multiplier increases |
| Block time deviation | > 5,000ms | Fee multiplier increases |
| Throughput | < 100 TPS | Fee multiplier increases |
| Gas utilization | > 80% | Fee multiplier increases |
Fee Distribution
Every transaction fee is split into four streams:
50% burned permanently → reduces circulating supply
10% network treasury → perpetual ecosystem funding
20% block proposer → direct validator incentive
20% staking reward pool → distributed to active validators
Treasury Revenue Projections
The 10% treasury fee creates a self-sustaining funding mechanism:
| Year | Est. Daily TX | Annual Treasury Revenue |
|---|---|---|
| Y1 | 10,000 | ~51,000 SAVI |
| Y3 | 200,000 | ~876,000 SAVI |
| Y5 | 1,000,000 | ~3,650,000 SAVI |
| Y10 | 20,000,000 | ~43,800,000 SAVI |
At scale (20M+ daily transactions), the treasury generates more annual funding than any pre-allocated ecosystem grant pool.
IoT Micro-Fee Design
IoT transactions use a dedicated transaction type with fees 28x lower than standard transfers. This enables:
- Continuous sensor data streams at minimal cost
- Batch certification of IoT device data
- Mesh network revenue tracking
AI/IoT service fees include an additional 50% micro-burn applied directly to the service fee, accelerating deflation as AI/IoT adoption grows.