AI's been handling our loan approvals, diagnosing health conditions, and managing assets, but there's one question nobody's really tackled — how do you know the results it provides haven't been tampered with?

OpenGradient offers a verifiable solution to this dilemma. Born from the a16z Crypto accelerator, having raised $9.5 million in funding, the team hails from Palantir and Two Sigma. But what really caught my eye is their HACA architecture — it separates AI model execution and on-chain verification into two independent paths. The inference nodes run models on GPUs while generating cryptographic proofs, and full nodes asynchronously verify, allowing users to get results without waiting, yet each inference can be independently audited. This isn’t just a concept — the mainnet has processed over 2 million verifiable inferences and generated more than 500,000 cryptographic proofs to date.

$OPG is the core fuel in this value loop. Inference payments, node staking, model monetization, app access, governance voting — all settle with it. The total supply is 1 billion tokens, with only about 190 million in circulation, 40% allocated for ecosystem development.

Last week, Binance and Upbit listed $OPG for spot trading, and privacy-focused AI products like OpenGradient Chat have launched. No matter how attractive the narrative, on-chain data is what really counts. In this AI infrastructure race, only the protocols that are actually used will remain standing.

#opg $OPG