EZKL — Zero-Knowledge Proofs for ML Models

EZKL converts any ONNX-formatted ML model into a ZK-SNARK circuit, enabling cryptographic verification that a model ran correctly on specific inputs without revealing private data. Written in Rust with Python, JavaScript/TypeScript (WASM), and CLI interfaces. Generates EVM-compatible Solidity verifier contracts for on-chain verification.

When to Use This Skill

• Converting ML models to ZK circuits
• Generating and verifying proofs of ML inference
• Deploying on-chain verifiers for model outputs
• Working with @ezkljs/engine (JS/TS SDK) or ezkl (Python/CLI)
• Integrating zkML into applications (Node.js, Bun, browser, EVM chains)

Core Workflow — 9 Steps

Every EZKL pipeline follows this sequence regardless of interface (CLI, Python, JS):