Conversion ratio and circulating supply
4.24 bINT → INT conversion ratio
The conversion ratio that governs how much INT a user receives per bINT decreases over the 15-year emission horizon. Earlier contribution earns more INT per unit of bINT than later contribution.
| Year | Base conversion ratio |
|---|---|
| 1 | 1 bINT = 5 INT |
| 2 | 1 bINT = 4.56 INT |
| 3 | 1 bINT = 4.11 INT |
| 4 | 1 bINT = 3.67 INT |
| 5 | 1 bINT = 3.22 INT |
| 6 | 1 bINT = 2.78 INT |
| 7 | 1 bINT = 2.33 INT |
| 8 | 1 bINT = 1.89 INT |
| 9 | 1 bINT = 1.44 INT |
| 10 | 1 bINT = 1 INT |
| 11–15 | 1 bINT = 1 INT |
The ratio interpolates linearly between Year 1 (5:1) and Year 10 (1:1). From Year 10 onward the ratio stays at 1:1 for the remaining emission horizon. The year index is determined by the protocol's emission calendar, starting from the Token Generation Event.
4.25 Hold window and conversion controls
bINT enters a minimum holding period before conversion eligibility. The hold window makes farming uneconomic: an attacker would need to sustain accounts through the full window, during which the trust layer (03) has time to detect and respond to anomalous patterns.
A per-user conversion rate limit caps how much bINT can be converted to INT in a single period. A lifetime conversion ceiling exists to bound the total INT any single account can ever extract from the contribution layer. These parameters are managed in the operations layer and are calibrated to balance user experience with protocol safety.
4.26 Circulating supply model
Circulating INT grows from three primary inflows: User Rewards conversion, Liquidity unlocks, and Airdrop tranches. It shrinks through buy-back-and-burn (4.9) and staking locks.
The table below projects circulating supply under three MAU growth scenarios. These are modeling projections, not commitments.
| Year | Low MAU scenario | Base MAU scenario | High MAU scenario |
|---|---|---|---|
| TGE | 2,237,500,000 | 2,237,500,000 | 2,237,500,000 |
| 1 | 3,500,000,000 | 5,200,000,000 | 7,400,000,000 |
| 2 | 5,100,000,000 | 8,800,000,000 | 14,000,000,000 |
| 3 | 7,000,000,000 | 13,200,000,000 | 21,500,000,000 |
| 5 | 11,500,000,000 | 22,500,000,000 | 36,000,000,000 |
| 10 | 24,000,000,000 | 42,000,000,000 | 58,000,000,000 |
| 15 | 38,000,000,000 | 60,000,000,000 | 72,000,000,000 |
Assumptions
- Low MAU: MAU stays in the 0–10K band for the first two years, reaching 100K by year 5.
- Base MAU: MAU reaches 100K in year 1, 1M by year 3, 5M by year 5.
- High MAU: MAU reaches 1M in year 1 and sustains 5M+ from year 3.
- All scenarios assume the buy-back-and-burn mechanism is active from year 2 onward, removing a percentage of circulating supply annually. The burn rate is a function of data-product revenue and treasury policy.
- Staking locks temporarily remove INT from circulation; the model counts locked INT as non-circulating.
These projections illustrate the relationship between adoption velocity and supply expansion. Actual circulating supply depends on conversion behavior, staking participation, burn execution, and user growth patterns that cannot be predicted with certainty.