Most AI crypto projects tokenize compute. @OpenGradient tokenizes the model itself — and that flips the economics.

Their Model Hub lets developers deploy open-source AI and earn $OPG every time someone runs inference on it. Think of it like YouTube's creator monetization, but for machine learning models. The 2000+ models already hosted aren't just a vanity metric — they're early supply-side infrastructure for a marketplace where usage directly drives token demand.

With 2M+ verifiable inferences already processed through their HACA stack (GPU nodes + zkML + TEEs), the network is proving that on-chain AI can be both transparent and functional. Built on Base, backed by a16z crypto and Coinbase Ventures, the thesis is that verifiable inference becomes a commodity layer — and the Model Hub is where supply meets demand.

The 1B fixed supply and April 2026 TGE give the ecosystem time to mature before full token velocity kicks in. Staking, node rewards, and governance round out the utility, but the real unlock is developer incentives: if model creators earn meaningfully, the flywheel spins.

What would it take for you to trust an AI model's output if you could cryptographically verify every inference on-chain?

$OPG #OPG

We post every algo signal's REAL result openly and the full live track record + a free preview channel are in our bio/profile.