Full Tokenomics Model · $CX · CC · CU

CarbonX Token Architecture

Three-layer proof-of-activity model. Real-world compute and carbon contribution backs every token. No inflation without activity.

Mirror ratio
1 : 1
1 CC/CU = 1 $CX
Buyback range
20–40%
Revenue → buy & burn
Net supply (10k devices)
40k
100k minted · 60% burned
Supply model
Activity-gated
No max · grows with use
Treasury allocation
Users 60% Treasury 20% Ecosystem 10% Team 10%
60% Users, 20% Treasury, 10% Ecosystem, 10% Team.
Burn mechanics
Usage burn
100%
Launchpad
50%
Marketplace
30%
Transactions
1–2%
Soft supply caps
50M
Phase 1
200M
Phase 2
1B
Phase 3
Reward issuance curve — gross vs net supply over network growth
Gross rewards Net (after 60% burn)
Issuance curve: gross rewards decline over network growth; net follows with 60% burn applied.
Economic flywheel
Devices
& activity
→
Credits
minted
→
$CX
token
→
Burn
events
→
Supply ↓
Price ↑
→
More
devices

Each loop reduces circulating supply · drives scarcity · incentivises new hardware onboarding

Architecture layers
Layer A — EU frontend
Compute Credits (CC) · Carbon Units (CU)
Non-transferable · non-tradable · platform-only
⇅
Bridge: controlled redemption · geo-fenced export
Layer B — global token layer
$CX · Tradable outside EU
Used across IOBIT ecosystem
Demand engine
⚡
Compute marketplace
AI bots · nodes · launchpad
🌱
Carbon buyers
EUR → token → burn path
🔗
IOBIT integration
Cross-ecosystem utility layer
🖥
AI compute boosts
Better hardware → higher yield
ROI Simulator below
$CX Token · Proof-of-Activity Model · v1.0

Edge Miner ROI
Revenue Model

Dynamic, market-dependent returns from compute rental, carbon credits, and token rewards. Adjust every variable to model real-world device economics.

Daily Profit = Compute Rev + Carbon Rev + Token Rewards − Operating Cost ROI = Daily Profit / Device Cost

Model inputs — adjust to simulate

Hardware & device
$1,200
100 TOPS
60 W
Market inputs
70%
$0.008
$12
Token & emissions
$0.25
200
1.5 CU
Operating costs
$0.12
2%
Burn rates (fixed)
Usage burn
100%
Launchpad
50%
Marketplace
30%
Transactions
1-2%

Live output — per device per day

Investment metrics

Revenue streams (daily $)

Compute Carbon Token rewards Op cost
Daily revenue breakdown.
Token price sensitivity — net profit per day by utilization rate
Utilization 40% Utilization 70% Utilization 100%
Sensitivity analysis.
Network scaling simulation — from 1 to 100,000 devices (log scale)
Total daily revenue ($) Tokens minted/day Net tokens (after 60% burn)
Network scaling simulation.
Economic flywheel — value loop
Devices
& activity
→
Credits
minted
→
$CX
token
→
Burn
events
→
Supply ↓
Price ↑
→
More
devices

Each cycle reduces circulating supply · drives scarcity · incentivises new hardware onboarding

Scenario comparison — Bear / Base / Bull / Moon

Scenario Token $Util Compute/dCarbon/dToken/d Op cost/dNet profit/d PaybackAnnual ROI

System architecture — three-layer model

Layer A — EU frontend

Compute Credits (CC) and Carbon Units (CU) issued on-platform. Non-transferable, non-tradable. EU-compliant utility layer with no speculative classification at entry.

CC Credits CU Units
BRIDGE
Bridge mechanism

Controlled redemption via periodic events, service settlement (credits → vendor tokens), and geo-fenced export. No instant conversion — legal separation maintained.

Redemption events Geo-fenced
Layer B — global token

$CX token tradable outside EU. Used across IOBIT ecosystem for compute marketplace, AI bots, launchpad, and nodes. Market price determined externally.

$CX Global IOBIT