Performances
RD Popularity Index
RD Growth Index
| 1h | 24h | 7d | 30d | 60d | 90d |
|---|---|---|---|---|---|
| 0.34% | 1.45% | 12.67% | 29.59% | 37.77% | -- |
Comparison
Sub Organizations
Tokenomics
Unlock Progress
Unlock Event
| Date | Unlocked Token Amount | Unlocked M.Cap | M.Cap (%) | Allocation |
|---|---|---|---|---|
| Oct 21, 2026 | 9.12M OPG | $1.21M | 3.97% | 3 Allocation |
| Nov 21, 2026 | 9.12M OPG | $1.21M | 3.97% | 3 Allocation |
| Dec 21, 2026 | 9.12M OPG | $1.21M | 3.97% | 3 Allocation |
Top Holders
| Address | Token | Quantity | Percentage | Value |
|---|---|---|---|---|
| 0x3c73...25ef |   OPG | 13,000,000 | 1.3% | $1.73M |
| 0x323a...03aa | OPG | 9,390,600 | 0.94% | $1.25M |
| 0x238a...e6c4 | OPG | 5,450,741.82 | 0.55% | $726.54K |
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About OpenGradient
OpenGradient is a decentralized AI inference network that addresses the opacity, single points of failure, and privacy risks of centralized AI providers. Its core narrative is verifiable AI: every inference can be cryptographically proven, ensuring which model ran, what inputs were processed, and that outputs were not tampered with. The Hybrid AI Compute Architecture separates execution from verification, supporting TEE, ZKML, and Vanilla modes to balance latency, cost, and trust. Key products include OpenGradient Chat (a privacy-first assistant routing to frontier models with local encryption, Oblivious HTTP, and TEE isolation), the x402 payment-gated inference protocol, a decentralized Model Hub, and MemSync for persistent memory. Market pain points include users' inability to verify model behavior, provider lock-in, and data leakage. In the past six months, OpenGradient launched OpenGradient Chat, expanded its network to over 2,000 models, 260,000+ wallet addresses, and processed 2 million+ inferences. Known limitations include ZKML's high computational overhead, TEE's reliance on hardware trust, and the trust gap during asynchronous settlement.
OpenGradient, an AI-focused decentralized infrastructure, was publicly launched in October 2024 alongside its Model Hub and SDK, marking its entry as an a16z CSX-incubated project. In the same month, it secured an $8.5 million seed round backed by a16z CSX, Coinbase Ventures, and angel investors including Balaji Srinivasan, establishing early institutional validation.
A significant technical milestone came in September 2025 with the launch of MemSync, a memory layer addressing context loss in AI assistants. This innovation enabled persistent, user-controlled memory across platforms, laying groundwork for digital twin applications and reinforcing OpenGradient’s positioning beyond simple compute markets.
The project achieved major market milestones in April 2026: Binance opened OPG trading with a HODLer airdrop and a $200,000 trading competition, while Upbit simultaneously listed OPG for KRW trading. These events marked the token’s transition from testnet to mainstream exchange availability, broadening access and liquidity. Earlier, the testnet had processed over 2 million verifiable inferences with 4,400+ models deployed, demonstrating real usage. Collectively, these milestones trace a path from research incubation to technical innovation and global market integration.
OpenGradient co-founders and core executives:
Matthew Wang (Co-founder & CEO): Former Quantitative Research at Two Sigma, SWE at Google, Facebook, and NASA. B.S. in Electrical and Computer Engineering from Northwestern University.
Adam Balogh (Co-founder & CTO): Former Tech Lead at Palantir AI Platform, SWE at Google and Amazon. M.S. in Advanced Computing from Imperial College London.
Advait Jayant (CSO): Founder of SuperSight (AI analytics, raised $1.27M) and Peri Labs (edge AI). Previously Head of Research at Fabric Ventures, Lecturer at UCL, MakerDAO Delegate, and O'Reilly author with 50+ AI publications. PhD from LBS.