OpenGradient Raises $9.5 Million to Scale Verifiable AI Compute Network

New updates have been reported about OpenGradient.

OpenGradient has secured a total of $9.5 million in funding to expand its decentralized compute network for verifiable AI, positioning the company as a core infrastructure provider for open, auditable model execution. The round is led by a16z crypto, with participation from Coinbase Ventures, SV Angel, Foresight Ventures, Pragma, SALT, Symbolic Capital, Canonical Crypto, Black Dragon, NEAR, Celestia, Thanefield Capital, and several prominent angel investors, giving OpenGradient both capital and strategic backing across AI and crypto ecosystems.

The company is targeting a growing systemic risk in AI deployment: today, most AI workloads run on opaque, centralized infrastructure that offers limited transparency or verification, which becomes critical as AI agents increasingly make financial and operational decisions. OpenGradient’s network functions as an AI coprocessor rather than a standalone blockchain, allowing applications, blockchains, and autonomous agents to offload intensive inference tasks to a distributed set of GPU and Trusted Execution Environment nodes while attaching cryptographic proofs to every output.

OpenGradient’s stack centers on three components: a verifiable inference network that records what model ran on which input and what it returned, a decentralized on-chain model hub hosting more than 2,000 models from over 100 developers, and developer tooling, including SDKs and APIs, that exposes these capabilities without requiring teams to understand underlying proof systems. This architecture is designed to let enterprises and protocol developers run workloads such as fraud and sybil detection, content generation, or decision support with auditable execution and traceable model provenance, potentially reducing compliance and governance risks.

The company reports early traction ahead of a broader ecosystem rollout, including more than 2 million users across the network and adjacent products, over 2 million verifiable inferences processed, 500,000 cryptographic proofs generated, and six active revenue streams. CEO and co-founder Matthew Wang frames OpenGradient as an open alternative to the consolidation of AI under a few closed providers, emphasizing that the new capital will be used to scale infrastructure, expand the model hub, and deepen tooling so developers can own and verify the intelligence their products depend on, with implications for financial services, on-chain applications, and AI-native platforms that require trustworthy automation.