Peer Cycles

The inference network where workers can't fake results and can't read your prompts. Powered by hardware guarantees.

0x33de3f2630b07bd5277a50bc4ae1acef172b7777

[Peer Cycles @PeerCycles]

$PEER Is Live

CA: 0x33de3f2630b07bd5277a50bc4ae1acef172b7777

Decentralized AI inference. You send a prompt, a real GPU runs it, the network proves the right model ran and keeps it private.

Live now: OpenAI-compatible API, USDG credits, workers earning, staking and burn. Confidential TEE tier next.

Site: https://t.co/Dpt5Czk6Pn

[Peer Cycles @PeerCycles]

Giving away 100 000 000 $PEER drop your wallets under this post

[Robinhood @RobinhoodApp]

We announced a lot yesterday. Here's everything we introduced, in one place. 🧵

[Peer Cycles @PeerCycles]

Peer Cycles turns idle hardware into a network you can verify on-chain - real work, real settlement, real proof. The future is already running.

[Vlad Tenev @vladtenev]

The future of crypto is in real-world assets.

[Peer Cycles @PeerCycles]

Anyone can catch a cheater and get paid for it.

On the Verified tier, validators stake the token to re-run random jobs and check the output matches. Find a mismatch? You win the challenge.

The cheating worker's bond gets slashed. You, the challenger, collect the reward.

The network polices itself. Catching bad work is profitable.

[Peer Cycles @PeerCycles]

6/ Job done. Worker gets paid in USDC. Failed proofs burn supply.

[Peer Cycles @PeerCycles]

How a job actually works on Peer Cycles. Simple version:

[Peer Cycles @PeerCycles]

5/ If you paid for the top tier, the enclave signs a cryptographic proof of which model ran. That proof ships with your response.

[Peer Cycles @PeerCycles]

AI inference is a commodity. Privacy and verifiable correctness are not.

That's the gap Peer Cycles fills.

[Peer Cycles @PeerCycles]

Live Network Stats are up on https://t.co/Yl5d2SjUQN.
Real numbers from the node, updating in real time. No fake counters - every figure is pulled straight from the network.
What you can see now in the Live section:

- Requests served, tokens generated, USD settled on-chain
- GPU worker status - live online/offline plus current model
- Inference speed in tok/s from the last job

Auto-refreshes every 5s. All real data, zero placeholders.
Watch the network work: https://t.co/Dpt5Czk6Pn

[Peer Cycles @PeerCycles]

Where does the value go? Into the token. No fake flywheel.

Network margin flows into one treasury in USDC. Every day it splits:

Half buys the token on the open market and burns it
Half pays stakers in USDC

On top of that, every slashed bond burns more supply. Bad actors shrink the float for everyone else.

Real revenue, real burns, real yield.

[Peer Cycles @PeerCycles]

6/ The browser tier brings in casual users. The confidential tier captures enterprise and high-sensitivity use. One network, three trust levels.

[Peer Cycles @PeerCycles]

Why this is different from every other "decentralized AI" project. A quick breakdown:

[Peer Cycles @PeerCycles]

5/ OpenAI-compatible API means the demand side is already there. Any app or agent framework plugs in with one URL change. No new SDK. No migration work.