PLETHORA
Every trading fee
becomes GPU time
Fees are routed through vast.ai, JarvisLabs, Lambda and RunPod.
The more fees, the more processing power available.
A fee is not a fee. It is an hour of an H100.
Most tokens burn fees or park them in a treasury. Plethora spends them on the one thing the market is short of, and the receipt is compute that exists.
- 01Trade feesEvery buy and sell on the Pons market produces fee revenue.
- 02Plethora routerFees are pooled, then split across the connected marketplaces.
- 03GPU providers vast.aiJarvisLabsLambdaRunPod The allocation is spent on real hardware at the going hourly rate.
- 04GPU timeProcessing power sitting behind the token instead of an idle treasury.
Trading generates fees
Every buy and sell on the Pons market produces fee revenue.
The router splits it
Fees are pooled and allocated across the connected compute marketplaces.
GPUs get rented
The allocation is spent on real hardware, priced at whatever the market charges that hour.
Capacity comes back
The result is processing power sitting behind the token instead of an idle treasury.
Four marketplaces, one demand center.
Routing across providers instead of picking one means capacity keeps flowing when a single marketplace runs dry or prices spike.
The more fees, the more processing power.
Move the volume and watch what it buys. This is arithmetic, not a promise, and the rate it uses is stated underneath.
Calculated at $2.20 per GPU hour, roughly the going rate for an H100 class card across these marketplaces. Real cost moves with the market, so treat this as a sense of scale.
Why this beats a treasury
A treasury holds a number on a screen. Compute is a thing that runs. It gets consumed, which means demand keeps returning, and it is priced in a market that has been short of supply for three years.
Plethora is a token with a spending policy. It is not an investment product and it does not promise a return.