What Is ERC-7007? The Token Standard for Verifiable AI-Generated Content

The line between human-made and machine-made digital content is getting blurrier by the month. AI image generators, music composers, and text tools are producing work that looks, sounds, and reads like it came from a human hand. That raises a practical question for anyone building or collecting digital assets: how do you prove that a specific piece of content was generated by a specific AI model, using a specific prompt?

That is the problem ERC-7007 sets out to solve. Proposed in May 2023, ERC-7007 is an Ethereum token standard purpose-built for verifiable AI-generated content. It extends the familiar ERC-721 NFT framework with new interfaces for cryptographic verification, ensuring that every minted token carries a provable link between a prompt, a model, and an output.

For developers building across multiple chains and token types, understanding standards like ERC-7007 matters because they shape how digital assets behave, what metadata they carry, and how they interact with wallets, marketplaces, and cross-chain infrastructure. This guide walks through how ERC-7007 works, why it exists, and where it fits in the broader Ethereum token landscape.

To understand what ERC-7007 adds, it helps to start with what ERC-721 already does. The ERC-721 standard defines the interface for non-fungible tokens on Ethereum. Each token is unique, identified by a token ID, and can be owned, transferred, and approved for third-party management. It is the backbone of nearly every NFT marketplace and collection in existence.

ERC-7007 builds directly on top of ERC-721. Any ERC-7007 token is also a valid ERC-721 token, which means it works with existing wallets, marketplaces, and tooling out of the box. But it introduces several additions that matter specifically for AI-generated content:

Prompt-indexed token IDs. In a standard ERC-721 collection, token IDs are arbitrary numbers. In ERC-7007, the token ID is derived from the prompt used to generate the content. This creates a deterministic link between what was asked and what was produced, meaning that each unique prompt maps to one unique token.

Onchain verification interfaces. ERC-7007 introduces an addAigcData function and a verify function. Together, these let a smart contract store and check whether a given output was genuinely produced by a specific AI model using a specific input. This is not just metadata stored in a JSON file somewhere. It is a verification mechanism baked into the contract logic.

Standardized AIGC metadata schema. The standard defines a JSON schema for AI-generated content metadata that goes beyond the typical NFT name-description-image triplet. It includes fields for the model used, the prompt submitted, and the verification proof, giving collectors and platforms structured data to work with.

These additions mean that an ERC-7007 token does not just represent ownership of a digital asset. It represents a verifiable claim about how that asset was created.

The verification layer is where ERC-7007 gets technically interesting. The standard supports two approaches to proving that AI-generated content is authentic: zero-knowledge machine learning (zkML) and optimistic machine learning (opML).

In the zkML flow, the process works roughly like this: an AI model is published onchain along with a verifier contract. When a user submits a prompt, the model produces an output. Simultaneously, a zero-knowledge proof is generated that attests the output was correctly derived from the model and the input, without revealing the model's internal weights or architecture.

This proof is then submitted to the verifier contract onchain. If the proof checks out, the content is minted as an ERC-7007 NFT. The benefit here is that the model owner's intellectual property stays protected, yet anyone can independently verify the output's authenticity.

The opML approach takes a different tack. Instead of generating a cryptographic proof upfront, the system operates on a trust-but-verify basis. The AI-generated output is published, and there is a challenge period during which anyone can dispute the correctness of the inference. If no successful challenge occurs within the window, the output is considered valid.

This is conceptually similar to how optimistic rollups handle transaction finality on Ethereum, where results are assumed correct unless someone proves otherwise. The trade-off is that opML is cheaper and faster to produce than a full zero-knowledge proof, but it requires a challenge period before the content can be considered fully verified.

ERC-7007 accommodates both methods through its modular verifier interface, letting developers choose the approach that best fits their use case.

Under the hood, an ERC-7007 implementation involves a few key components working together.

The AIGC-NFT smart contract is the core contract, compliant with both ERC-721 and ERC-7007 interfaces. It handles minting, ownership, transfers, and the AIGC-specific data storage.

The verifier smart contract implements a verify function. When given an inference task and its corresponding proof (either a ZK proof or an opML finalization), it returns a boolean result. This contract is separate from the NFT contract itself, which means different collections can plug in different verification mechanisms.

Optional extensions include an enumerable interface that maps token IDs to prompts (and vice versa), making it possible to look up the full prompt history of a collection. There is also an updatable extension for opML scenarios, where the AIGC data might change during the challenge period if a dispute succeeds.

The standard also addresses security concerns like frontrunning. Because prompts are submitted onchain during the minting process, an attacker could theoretically observe a pending transaction and submit the same prompt first. The specification recommends that implementers use commit-reveal schemes or time-locks to prevent this.

For developers working with EVM-compatible chains and cross-chain token standards, ERC-7007's backward compatibility with ERC-721 means these tokens can move through existing infrastructure, including bridges and marketplaces, without requiring custom integration work.

The standard is designed to be flexible enough for several distinct applications.

An artist deploys an AI model onchain. Collectors submit prompts during the minting process, generating unique pieces. Each artwork is verified to confirm it was produced by that specific model with that specific prompt, and the proceeds flow back to the artist. This creates a new model for digital content ownership where the artist monetizes the model itself, not just individual outputs.

A musician tokenizes an AI model that generates music tracks. Fans submit prompts or themes, receive personalized compositions, and own the resulting NFTs. The verification layer ensures that each track genuinely came from the artist's model, not a copycat.

ERC-7007 enables structures where the original model creator receives ongoing compensation as their model generates content. Because the link between model, prompt, and output is verifiable onchain, revenue-sharing can be automated through smart contract logic rather than relying on honor systems.

Beyond creative applications, the standard has potential in any context where proving that a specific AI model produced a specific output matters, from scientific research to legal document generation.

Like any standard, ERC-7007 involves trade-offs worth understanding.

Ethereum's ecosystem includes a growing family of token standards, each designed for a specific purpose. ERC-20 handles fungible tokens. ERC-721 handles non-fungible tokens. ERC-1155 handles semi-fungible tokens. ERC-4626 standardizes yield-bearing vaults. ERC-7683 standardizes cross-chain intent-based transactions.

ERC-7007 carves out a niche specifically at the intersection of AI and NFTs. It does not compete with these other standards so much as it adds a verification layer that becomes increasingly relevant as AI-generated content floods digital markets.

The timing is notable. As AI tools become more accessible and AI-generated art becomes harder to distinguish from human-made work, the demand for provenance and authenticity verification is growing. Platforms, collectors, and creators all benefit from a standardized way to answer the question: "Was this actually made by the model the creator says it was?"

For the broader onchain ecosystem, standards like ERC-7007 also matter because they expand the types of assets that can be represented, verified, and traded onchain. As stablecoin infrastructure and cross-chain execution layers mature, the ability to move verified AI-generated content tokens across chains with the same ease as any other ERC-721 token becomes a practical reality.

Developers interested in building with ERC-7007 can start with the reference implementation on the EIP page, which includes sample contract code and unit tests. The ORA Network provides tooling for deploying AI models onchain with ERC-7007 verification, including support for both zkML and opML proving methods.

Key implementation steps include:

The ERC-7007 discussion thread on Ethereum Magicians is an active resource for implementation questions and technical discussion.

What is ERC-7007 in simple terms?

ERC-7007 is an Ethereum token standard that lets you create NFTs for AI-generated content with built-in proof that a specific AI model produced the content using a specific prompt. It extends the existing ERC-721 NFT standard.

How is ERC-7007 different from a regular ERC-721 NFT?

A regular ERC-721 NFT represents ownership of a digital asset but says nothing about how the asset was created. ERC-7007 adds verification interfaces that cryptographically prove the content was generated by a particular AI model with a particular input.

What are zkML and opML in the context of ERC-7007?

zkML (zero-knowledge machine learning) uses cryptographic proofs to verify AI outputs without revealing the model's internals. opML (optimistic machine learning) assumes outputs are correct unless someone successfully challenges them within a time window. Both are supported verification methods within ERC-7007.

Is ERC-7007 widely adopted?

The standard is still in the Review stage as of early 2026. Several projects, notably ORA Network, have built implementations, but it has not yet reached mainstream adoption. Interest is growing as AI-generated content becomes more prevalent.

Can ERC-7007 tokens be used on other blockchains?

Because ERC-7007 extends ERC-721, these tokens can be bridged to other EVM-compatible chains using standard cross-chain infrastructure. The verification data travels with the token metadata.

What types of AI content can ERC-7007 handle?

The standard is content-agnostic. It can handle images, music, text, video, or any other output that an AI model produces. The verification layer cares about the model-prompt-output relationship, not the content type itself.