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OGONG

Decentralized AI inference you don't have to trust. You can check it.

Run a node → How it works

The idea in one paragraph

The world has far more capable GPUs than any one company runs. The reason inference still piles up inside a few big providers isn’t a shortage of compute. It’s trust. You can’t safely pay a stranger’s GPU for an answer you have no way to check. It could quietly swap in a cheaper model, hand back a stale cached reply, or just run the model badly, and you would never know.

OGONG removes that problem. Providers prove their work, independent validators re-check a sample of it, and payment stays in escrow until the check passes. Because checking an answer is roughly 100x cheaper than producing it, the network can verify nearly everything. So anyone’s GPU becomes safe to pay, and inference spreads back out.

What is OGONGThe problem, the pieces, and how an answer gets verified end to end. Trust tiersPrivate vs. verified, and the difference between them stated plainly. How verification worksCommitments, audits, and why cheap checking replaces a cash bond. Split inferenceA cohort of ordinary GPUs serves a frontier model no single one could hold. TokenomicsFixed supply, 80% earned by verified work on a 4-year halving. QuickstartFrom an empty machine to a live local network, all command line. Run a providerServe a model from your GPU and earn. Headless, no GUI required.

CLI-first, no GUI required

Every role in OGONG runs headless from the command line, with no dependency on any hosted or branded stack, and no GUI to install. The command line is the real thing.

ogong-validatord   # validator / audit node
ogong-verifierd    # re-runs committed work to score an audit
ogong-routerd      # provider marketplace match engine
ogong-gatewayd     # OpenAI-compatible consumer endpoint
ogong-provider     # provider daemon, also a zero-signup local model server

Every piece above is real software you run from the command line. The sections that follow link straight into it.