Every dollar burns CR8 — and now you can simulate it

Most token whitepapers read like marketing brochures. Vague claims about "deflationary mechanics" and "value accrual" and "aligned incentives." No numbers. No simulations. No way to verify whether the model actually works under stress.

We think that is unacceptable. So we built something different.

The Create Protocol V4 tokenomics model introduces a burn toll — a simple, deterministic mechanism where every dollar of CR8 mint or redeem volume destroys a fraction of supply. We modelled it completely. Then we built a public simulator so anyone can poke holes in it. It is live at kcolbchain.com/token-simulator/.

How the burn toll works

The V4 model replaces the previous yield-buyback mechanism with something far simpler. When a user mints CR8 against USD collateral, 1% of the CR8 equivalent is burned from the protocol's reserve. When a user redeems CR8 for USD, the same 1% burn applies.

That is the entire mechanism. No staking. No rebasing. No governance vote to adjust parameters. Every interaction with the protocol reduces supply by a fixed, predictable amount.

Why 1%? Because it is large enough to create meaningful deflation at moderate volumes, and small enough that it does not create prohibitive friction for users. At $5 million per month in mint/redeem volume — a conservative estimate for a mid-cap stablecoin protocol — the burn toll destroys approximately 5.4% of circulating supply annually.

That number is not hand-waved. It falls out of the simulator.

The simulator

The token simulator at kcolbchain.com/token-simulator/ is a full macro-level model of the CR8 economy. You can adjust every parameter and watch the supply, price, and burn rate evolve over simulated months.

Here is what you can configure:

• Initial supply and distribution. Set the genesis supply, team allocation, investor allocation, community treasury, and liquidity bootstrap amount.
• Vesting schedules. Configure cliff periods and linear vesting for each allocation bucket. The simulator tracks unlocked vs. circulating supply separately — because a token is not "circulating" just because it has been minted.
• Mint/redeem volume. Set monthly volume with a growth rate and a tapering function. Volume starts at your specified base, grows at your specified rate, and tapers as the protocol matures. This prevents the classic mistake of modelling with constant exponential growth forever.
• Burn toll rate. The default is 1%, but you can crank it to 5% and watch what happens. (Spoiler: above 3%, the friction deters usage and total burn actually decreases. There is an optimal point, and the simulator helps you find it.)
• AMM pool parameters. The simulator includes an endogenous price model via a constant-product AMM. You set the initial pool depth (CR8 and USDC sides), and the price emerges from supply/demand dynamics as burns reduce the CR8 side of the pool.
• Operating costs. The protocol has real costs — infrastructure, audits, contributor compensation. These are modelled as monthly outflows from the treasury. If operating costs exceed revenue, the treasury drawdown is visible in the charts.

What the default scenario shows

With the V4 preset loaded (100M initial supply, 1% burn toll, $5M/month starting volume growing at 8% monthly with tapering, $200K/month operating costs), here is what the simulator produces:

After 12 months, circulating supply drops from 100M to approximately 94.6M. The burn toll has destroyed 5.4M tokens. But because supply reduction concentrates the AMM pool, the endogenous price rises from $0.10 to approximately $0.118 — an 18% increase driven purely by supply mechanics, not speculation.

After 24 months, the growth tapering kicks in. Volume stabilises around $12M/month. Annual burn rate settles to approximately 4.8% (slightly lower because the base supply is smaller). Cumulative supply is down to roughly 89.5M. Price sits around $0.134.

After 36 months, the model reaches a quasi-steady state. Volume growth has fully tapered. Burns continue at a predictable rate. The treasury is self-sustaining from protocol fees (separate from the burn toll). Price appreciation slows but remains positive because supply continues to contract.

None of these numbers are promises. They are outputs of a model with explicit assumptions. Change the assumptions, and the outputs change. That is the point.

Breaking the model

We encourage you to try to break it. Here are some stress tests we ran:

Volume collapse. Set monthly volume to zero after month 6. Result: burns stop, price stabilises, treasury runs out of runway by month 14. The model does not pretend to work without usage. Honest.

Extreme burn rate. Set the toll to 10%. Result: per-transaction cost is so high that the volume growth rate cannot overcome the friction. Total burned supply actually peaks lower than the 1% scenario because there are fewer transactions. The Laffer curve applies to token burns too.

Whale dump. Simulate a large holder selling 10% of supply into the AMM in month 3. Result: price drops sharply, but the burn toll on the redeem partially offsets it by reducing supply simultaneously. Recovery takes about 4 months at baseline volume. The burn toll acts as an automatic stabiliser — not perfect, but meaningful.

Hyperinflation of operating costs. Triple the operating costs to $600K/month. Result: treasury is depleted by month 18. The model makes this failure mode visible and quantifiable, so governance can set cost guardrails with real numbers.

The Python library

The web simulator is great for exploration, but for rigorous analysis you want something you can put in a CI pipeline. The Python library kcolbchain-token-sim implements the same model with the same parameters. Install it, write a test that asserts "at $5M/month volume, annual burn rate exceeds 5%," and run it on every commit. Tokenomics should be as testable as smart contracts.

The library and the web simulator share the same core logic, transpiled from a single source of truth. If you find a discrepancy, it is a bug — please file an issue.

Source code: github.com/kcolbchain/token-simulator.

Why this matters beyond CR8

We built this simulator for the CR8 V4 model, but the architecture is general. Any token with supply sinks, vesting, AMM pricing, and treasury dynamics can be modelled by swapping out the preset. We are already working on presets for three other protocols that asked us to run the same kind of analysis.

The deeper point: the token design space is huge, and most of it is unexplored because the tooling does not exist. You cannot A/B test tokenomics on mainnet. But you can simulate a thousand scenarios in a browser tab before deploying a single contract. That is what responsible token design looks like.