# ONNX ONNX is an open format built to represent machine learning models. ONNX defines a common set of operators - the building blocks of machine learning and deep learning models - and a common file format. While most zkVMs run their proofs over a RISC-V trace, JOLT Atlas computes proofs over an ONNX trace. That is, a proof in JOLT Atlas convinces a verifier that the ONNX trace is the result of running a neural network model for some inputs parameters. Neural networks have a different computational model (they are a DAG) and a different set of opcodes. We'll dive into the ONNX runtime next. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://devs.novanet.xyz/jolt-atlas-zkml/onnx.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.