The coprocessor sector has experienced remarkable growth since 2024, with several key developments reshaping the landscape:
Significant advancements have emerged in the core technologies powering coprocessors:
Axiom has maintained market leadership by introducing AxiomOS, an operating system for data availability that integrates with major L2 solutions. Their enterprise-grade coprocessing suite now supports real-time data streaming with ZK validity proofs.
Following their successful integration with EigenLayer, Brevis has deployed Brevis Nexus, connecting coprocessor functionalities across 9 major blockchain networks. Their parallel processing architecture can now handle 5,000+ simultaneous verification requests.
Herodotus has leveraged its Starknet integration to create Temporal Bridges, allowing smart contracts to access cross-chain historical data with 97% lower fees than traditional methods. Their partnership program now includes 40+ major DeFi protocols.
New entrants have focused on specialized vertical applications:
Coprocessors are increasingly becoming a fundamental layer of Web3 infrastructure:
The coprocessor landscape has matured significantly through 2025, transforming from experimental technology to essential Web3 infrastructure. Technical improvements have dramatically reduced costs while expanding capabilities, making historical data access practical for mainstream applications. As standardization efforts continue and cross-chain functionality expands, coprocessors are establishing themselves as the critical link between blockchain’s present state and its historical record, enabling a new generation of intelligent, context-aware decentralized applications.
This article provides a comprehensive review of the development and origins of coprocessors, analyzes the technical stacks and competitive advantages of various competitors in the current track, and explains how coprocessors work using Axiom as an example.
Mo Dong, the co-founder of Celer Network and Brevis, believes that, in simple terms, a coprocessor is a tool that “gives smart contracts the ability of Dune Analytics.”
In simple terms, current general smart contracts cannot access historical data. For instance, while working on a Liquidity Management Protocol, I needed historical price data to calculate how often and at what cost liquidity providers exceeded the price range in an AMM. We had to depend on a chain-hosted index service like The Graph’s GraphQL API, because aggregation, searching, and filtering tasks cannot be performed through contract interaction alone. Indeed, even indexing standard blockchain transaction data is challenging, let alone reading more complex data than basic information.
Regarding liquidity management protocols, evaluating the historical performance of existing test pools or user pools still requires using a chain-hosted index service’s API. This data is then manually calculated in Excel. Is there a service capable of simplifying this process, providing dapp smart contracts with the ability to aggregate, filter, and analyze this data directly? Coprocessors are designed to solve the problem.
In early computer systems, the CPU processor could often only perform basic operations. It needed to be paired with a dedicated “coprocessor” to perform specific types of computing tasks, such as floating-point operations, to improve performance.
Now, we can think of Ethereum as a giant supercomputer. Smart contracts all over the world can only access on-chain data from the current block, not historical data including transaction records and account balance changes. This is because Ethereum’s design does not provide a way for smart contracts to access this historical data.
Accessing historical data to ensure its trustworthiness requires a cryptographic method that links historical records to the current block. However, calculating and verifying this proof in a smart contract directly can be time-consuming and costly. Alternatively, queries through storage nodes can be made, but smart contracts cannot interact directly with them, and there is a trust issue. So, how can we solve this trust problem and enable verifiable computation? In other words, how can we allow a third party to directly verify the results of the computation for correctness, without needing to re-execute the computation itself? The solution may lie in coprocessors, which are similar to early computer systems. They can extend the computing power of smart contracts on Ethereum, giving them the new ability to access historical data and perform complex calculations.
In general, the main workflow of a coprocessor that verifies Ethereum data is as follows:
This section mainly analyzes the key technical stacks and competitive advantages of leading players in the coprocessor space.
A pioneer in the coprocessor space, Axiom is building on-chain data infrastructure to simplify smart contract interaction with on-chain data. Axiom is also credited with introducing the concept of coprocessors. We’ll delve deeper into how their coprocessor works later in this article using Axiom as an example.
Lagrange focuses on cross-chain state proofs and parallel processing techniques. Their proofs can achieve cross-chain verification without relying on cross-chain messaging protocols like zkBridge or IBC. Lagrange’s Parallel Prover is well-suited for products involving re-staking, solidifying their position in the RaaS (Rollup as a Service) ecosystem.
Unlike sequential proofs, parallel proofs can distribute their workload across thousands of threads simultaneously. Additionally, re-staking on EigenLayer can secure them. In other words, this approach of parallel computing and parallel proving allows for better horizontal scalability.
One real-world use case is Lagrange’s application on AltLayer. AltLayer offers active verification services for Restaked Rollup, helping developers implement decentralized sequencing and verify the correctness of Rollup state efficiently. In March 2024, Lagrange partnered with AltLayer to utilize parallel provers for Rollup co-processing. This ensures verifiable and trustless on-chain data and computation results for AltLayer’s RaaS customers.
Closely tied to the Starkware/Starknet ecosystem, Herodotus partners with projects like Snapshot. They call their coprocessor system “Storage Proof,” which can be combined with ZK proofs to enable cross-layer data access between different Ethereum layers.
Source: Herodotus Website
The storage proof system consists of three components:
Any on-chain data in an Ethereum archive node can be proven using the storage-proof system.
Like other coprocessors, the storage proof system is generated off-chain and verified on-chain, minimizing on-chain resource consumption. It also reduces data transferred between Ethereum layers by only sending the block hash or accumulator root for verification.
Developed by Celer Network, Brevis is an infrastructure for building various on-chain data services, including ZK coprocessors. Celer Network, an interoperability protocol founded by Mo Dong and Qingkai Liang, raised \$4 million in an IEO (Initial Exchange Offering) in 2019.
Celer Network has deployed a Brevis contract on-chain. This contract verifies proofs from coprocessor requests and relays the results back to the dapp’s contract through a callback function. Developers can leverage the Brevis SDK to enable dapps to access on-chain historical data with ease. The SDK abstracts away complex circuits, eliminating the need for developers to have prior knowledge of ZK proofs. The Brevis SDK is built on the gnark framework developed by the Consensys Linea team. Additionally, Brevis supports Ethereum’s ZK light client, allowing it to work with on-chain data from any Ethereum EVM-compatible blockchain.
Source: Brevis Documentation
Celer Network is currently developing coChain, a blockchain focused on the RaaS ecosystem, using Brevis as the foundation. coChain is a blockchain based on the Proof-of-Stake (PoS) consensus algorithm and can provide Ethereum staking and slashing services.
Slashing refers to the process of penalizing validators who violate the rules in the Ethereum PoS ecosystem, including fines and state changes. Historically, the slashing rate in the Ethereum staking ecosystem has been very low, with data suggesting that only around 0.04% of validators have been slashed.
coChain’s unique feature is linking the generation of coprocessor results to the rewards and punishments of Ethereum staking. Here’s the process:
Overall, coChain’s approach combines coprocessors’ trust/verification incentives with the Ethereum staking ecosystem. In the future, it will integrate with EigenLayer to reduce the proof cost of ZK coprocessors.
Nexus zkVM allows verification of any on-chain computation result. Its unique feature is the ability to verify ZK proofs based on folding techniques. Founded in 2022, Nexus is another player in the zkVM space. While details haven’t been widely disclosed yet, the founder, Daniel Marin (Stanford graduate with prior experience at Google), published early research papers through the Stanford Blockchain Club.
ZK folding technology is considered a promising branch within zkVM solutions. Nexus zkVM supports the verification of both folding proofs and accumulation schemes. It aims to be a scalable, modular, and open-source zkVM. Their technical stack includes large-scale parallelized proof aggregation mechanisms based on Incremental Verifiable Computation (IVC) and various folding schemes like Nova, CycleFold, SuperNova, and HyperNova. They’re also developing the Nexus Network, a large-scale parallelized proof mining network built on Nexus zkVM.
Source: Nexus Documentation, Nexus zkVM Architecture
As you can see, different projects have chosen different technical stacks based on different ecosystems (Ethereum EVM, RaaS, cross-chain, Ethereum cross-layer), different proof methods (Rollup vs ZK), or different solutions within ZK proofs (zk-SNARK, folding proofs, accumulation schemes, etc.). They each have their strengths and weaknesses regarding competitive advantages and ultimately present different product forms: interactive on-chain contracts, SDKs, and networks designed for various purposes, such as staking verification networks and large-scale verification networks.
Source: By Author
Axiom is a ZK proof coprocessor built for Ethereum. It allows smart contracts to access historical on-chain data and ensures the trustlessness of off-chain computation through ZK proof technology. Axiom was founded by Jonathan Wang and Yi Sun in 2022. On January 25, 2024, Axiom announced on Twitter that it had raised \$20 million in Series A funding led by Paradigm and Standard Crypto. It is the first project to propose the concept of “coprocessor” and is also one of the most venture capital-backed projects in the space.
Source: Axiom Official X Account
In 2017, Yi Sun received a PhD in mathematics from MIT and also worked for a high-frequency trading company for a period of time. He began to delve into the field of cryptocurrencies and realized that ZK proof is the key to blockchain scalability. However, at the time, he believed that ZK technology was still in its early stages, so he chose to continue observing the space. It wasn’t until the end of 2021 that ZK technology began to take off, with infrastructure and development tools gradually maturing. In addition, Yi Sun encountered problems accessing historical data in smart contracts he wrote when building DeFi protocols. All of these factors led to the birth of Axiom.
Axiom currently uses the SNARK proof system based on Halo2 and KZG backends and ZK proof tools such as lookup tables (LUTs). In the past, ZK proofs were complex and difficult to audit. Lookup tables are a set of pre-computed values that allow the prover to more efficiently prove to the verifier that the value exists.
In January 2024, Axiom V2 went live on the Ethereum mainnet, supporting access to transactions, receipts, contract storage, block headers, and other data from smart contracts. This means it now supports access to all historical data on the Ethereum mainnet.
Using the SDK tools developed by Axiom, developers can write Axiom circuits in Typescript to issue data requests and customize computations. Axiom is ahead of the curve because it makes it very easy for smart contracts to access on-chain data:
However, unlike Herodotus, Axiom currently does not support querying historical data from other Ethereum EVM networks or L2 networks and only focuses on the Ethereum mainnet. Future support for related features is not ruled out.
At the application layer, Axiom can assist dapps in implementing the following functions:
The current leader in the coprocessor space, Axiom, has a complementary relationship with light node projects such as Succinct. Succinct attempts to prove the Ethereum consensus itself, while Axiom proves any on-chain historical data based on the consensus, assuming the consensus result is accepted.
The field of ZK proof is rapidly developing with innovative inventions like folding proofs, accumulation schemes, and large lookup tables. This growth has drawn attention to projects like Nexus, which support the latest advancements in ZK proof technology. While ZK proofs are becoming mainstream, other projects like Lagrange are also gaining notice for providing proofs for Rollup through parallel provers, thereby filling a market gap.
Ongoing tech advancements have boosted the performance of various knowledge proofs, shrinking their size and verification costs. And this broadens their potential usage. In this context, the flexibility provided by modularization is gaining recognition, particularly within the coprocessor space.”
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The coprocessor sector has experienced remarkable growth since 2024, with several key developments reshaping the landscape:
Significant advancements have emerged in the core technologies powering coprocessors:
Axiom has maintained market leadership by introducing AxiomOS, an operating system for data availability that integrates with major L2 solutions. Their enterprise-grade coprocessing suite now supports real-time data streaming with ZK validity proofs.
Following their successful integration with EigenLayer, Brevis has deployed Brevis Nexus, connecting coprocessor functionalities across 9 major blockchain networks. Their parallel processing architecture can now handle 5,000+ simultaneous verification requests.
Herodotus has leveraged its Starknet integration to create Temporal Bridges, allowing smart contracts to access cross-chain historical data with 97% lower fees than traditional methods. Their partnership program now includes 40+ major DeFi protocols.
New entrants have focused on specialized vertical applications:
Coprocessors are increasingly becoming a fundamental layer of Web3 infrastructure:
The coprocessor landscape has matured significantly through 2025, transforming from experimental technology to essential Web3 infrastructure. Technical improvements have dramatically reduced costs while expanding capabilities, making historical data access practical for mainstream applications. As standardization efforts continue and cross-chain functionality expands, coprocessors are establishing themselves as the critical link between blockchain’s present state and its historical record, enabling a new generation of intelligent, context-aware decentralized applications.
This article provides a comprehensive review of the development and origins of coprocessors, analyzes the technical stacks and competitive advantages of various competitors in the current track, and explains how coprocessors work using Axiom as an example.
Mo Dong, the co-founder of Celer Network and Brevis, believes that, in simple terms, a coprocessor is a tool that “gives smart contracts the ability of Dune Analytics.”
In simple terms, current general smart contracts cannot access historical data. For instance, while working on a Liquidity Management Protocol, I needed historical price data to calculate how often and at what cost liquidity providers exceeded the price range in an AMM. We had to depend on a chain-hosted index service like The Graph’s GraphQL API, because aggregation, searching, and filtering tasks cannot be performed through contract interaction alone. Indeed, even indexing standard blockchain transaction data is challenging, let alone reading more complex data than basic information.
Regarding liquidity management protocols, evaluating the historical performance of existing test pools or user pools still requires using a chain-hosted index service’s API. This data is then manually calculated in Excel. Is there a service capable of simplifying this process, providing dapp smart contracts with the ability to aggregate, filter, and analyze this data directly? Coprocessors are designed to solve the problem.
In early computer systems, the CPU processor could often only perform basic operations. It needed to be paired with a dedicated “coprocessor” to perform specific types of computing tasks, such as floating-point operations, to improve performance.
Now, we can think of Ethereum as a giant supercomputer. Smart contracts all over the world can only access on-chain data from the current block, not historical data including transaction records and account balance changes. This is because Ethereum’s design does not provide a way for smart contracts to access this historical data.
Accessing historical data to ensure its trustworthiness requires a cryptographic method that links historical records to the current block. However, calculating and verifying this proof in a smart contract directly can be time-consuming and costly. Alternatively, queries through storage nodes can be made, but smart contracts cannot interact directly with them, and there is a trust issue. So, how can we solve this trust problem and enable verifiable computation? In other words, how can we allow a third party to directly verify the results of the computation for correctness, without needing to re-execute the computation itself? The solution may lie in coprocessors, which are similar to early computer systems. They can extend the computing power of smart contracts on Ethereum, giving them the new ability to access historical data and perform complex calculations.
In general, the main workflow of a coprocessor that verifies Ethereum data is as follows:
This section mainly analyzes the key technical stacks and competitive advantages of leading players in the coprocessor space.
A pioneer in the coprocessor space, Axiom is building on-chain data infrastructure to simplify smart contract interaction with on-chain data. Axiom is also credited with introducing the concept of coprocessors. We’ll delve deeper into how their coprocessor works later in this article using Axiom as an example.
Lagrange focuses on cross-chain state proofs and parallel processing techniques. Their proofs can achieve cross-chain verification without relying on cross-chain messaging protocols like zkBridge or IBC. Lagrange’s Parallel Prover is well-suited for products involving re-staking, solidifying their position in the RaaS (Rollup as a Service) ecosystem.
Unlike sequential proofs, parallel proofs can distribute their workload across thousands of threads simultaneously. Additionally, re-staking on EigenLayer can secure them. In other words, this approach of parallel computing and parallel proving allows for better horizontal scalability.
One real-world use case is Lagrange’s application on AltLayer. AltLayer offers active verification services for Restaked Rollup, helping developers implement decentralized sequencing and verify the correctness of Rollup state efficiently. In March 2024, Lagrange partnered with AltLayer to utilize parallel provers for Rollup co-processing. This ensures verifiable and trustless on-chain data and computation results for AltLayer’s RaaS customers.
Closely tied to the Starkware/Starknet ecosystem, Herodotus partners with projects like Snapshot. They call their coprocessor system “Storage Proof,” which can be combined with ZK proofs to enable cross-layer data access between different Ethereum layers.
Source: Herodotus Website
The storage proof system consists of three components:
Any on-chain data in an Ethereum archive node can be proven using the storage-proof system.
Like other coprocessors, the storage proof system is generated off-chain and verified on-chain, minimizing on-chain resource consumption. It also reduces data transferred between Ethereum layers by only sending the block hash or accumulator root for verification.
Developed by Celer Network, Brevis is an infrastructure for building various on-chain data services, including ZK coprocessors. Celer Network, an interoperability protocol founded by Mo Dong and Qingkai Liang, raised \$4 million in an IEO (Initial Exchange Offering) in 2019.
Celer Network has deployed a Brevis contract on-chain. This contract verifies proofs from coprocessor requests and relays the results back to the dapp’s contract through a callback function. Developers can leverage the Brevis SDK to enable dapps to access on-chain historical data with ease. The SDK abstracts away complex circuits, eliminating the need for developers to have prior knowledge of ZK proofs. The Brevis SDK is built on the gnark framework developed by the Consensys Linea team. Additionally, Brevis supports Ethereum’s ZK light client, allowing it to work with on-chain data from any Ethereum EVM-compatible blockchain.
Source: Brevis Documentation
Celer Network is currently developing coChain, a blockchain focused on the RaaS ecosystem, using Brevis as the foundation. coChain is a blockchain based on the Proof-of-Stake (PoS) consensus algorithm and can provide Ethereum staking and slashing services.
Slashing refers to the process of penalizing validators who violate the rules in the Ethereum PoS ecosystem, including fines and state changes. Historically, the slashing rate in the Ethereum staking ecosystem has been very low, with data suggesting that only around 0.04% of validators have been slashed.
coChain’s unique feature is linking the generation of coprocessor results to the rewards and punishments of Ethereum staking. Here’s the process:
Overall, coChain’s approach combines coprocessors’ trust/verification incentives with the Ethereum staking ecosystem. In the future, it will integrate with EigenLayer to reduce the proof cost of ZK coprocessors.
Nexus zkVM allows verification of any on-chain computation result. Its unique feature is the ability to verify ZK proofs based on folding techniques. Founded in 2022, Nexus is another player in the zkVM space. While details haven’t been widely disclosed yet, the founder, Daniel Marin (Stanford graduate with prior experience at Google), published early research papers through the Stanford Blockchain Club.
ZK folding technology is considered a promising branch within zkVM solutions. Nexus zkVM supports the verification of both folding proofs and accumulation schemes. It aims to be a scalable, modular, and open-source zkVM. Their technical stack includes large-scale parallelized proof aggregation mechanisms based on Incremental Verifiable Computation (IVC) and various folding schemes like Nova, CycleFold, SuperNova, and HyperNova. They’re also developing the Nexus Network, a large-scale parallelized proof mining network built on Nexus zkVM.
Source: Nexus Documentation, Nexus zkVM Architecture
As you can see, different projects have chosen different technical stacks based on different ecosystems (Ethereum EVM, RaaS, cross-chain, Ethereum cross-layer), different proof methods (Rollup vs ZK), or different solutions within ZK proofs (zk-SNARK, folding proofs, accumulation schemes, etc.). They each have their strengths and weaknesses regarding competitive advantages and ultimately present different product forms: interactive on-chain contracts, SDKs, and networks designed for various purposes, such as staking verification networks and large-scale verification networks.
Source: By Author
Axiom is a ZK proof coprocessor built for Ethereum. It allows smart contracts to access historical on-chain data and ensures the trustlessness of off-chain computation through ZK proof technology. Axiom was founded by Jonathan Wang and Yi Sun in 2022. On January 25, 2024, Axiom announced on Twitter that it had raised \$20 million in Series A funding led by Paradigm and Standard Crypto. It is the first project to propose the concept of “coprocessor” and is also one of the most venture capital-backed projects in the space.
Source: Axiom Official X Account
In 2017, Yi Sun received a PhD in mathematics from MIT and also worked for a high-frequency trading company for a period of time. He began to delve into the field of cryptocurrencies and realized that ZK proof is the key to blockchain scalability. However, at the time, he believed that ZK technology was still in its early stages, so he chose to continue observing the space. It wasn’t until the end of 2021 that ZK technology began to take off, with infrastructure and development tools gradually maturing. In addition, Yi Sun encountered problems accessing historical data in smart contracts he wrote when building DeFi protocols. All of these factors led to the birth of Axiom.
Axiom currently uses the SNARK proof system based on Halo2 and KZG backends and ZK proof tools such as lookup tables (LUTs). In the past, ZK proofs were complex and difficult to audit. Lookup tables are a set of pre-computed values that allow the prover to more efficiently prove to the verifier that the value exists.
In January 2024, Axiom V2 went live on the Ethereum mainnet, supporting access to transactions, receipts, contract storage, block headers, and other data from smart contracts. This means it now supports access to all historical data on the Ethereum mainnet.
Using the SDK tools developed by Axiom, developers can write Axiom circuits in Typescript to issue data requests and customize computations. Axiom is ahead of the curve because it makes it very easy for smart contracts to access on-chain data:
However, unlike Herodotus, Axiom currently does not support querying historical data from other Ethereum EVM networks or L2 networks and only focuses on the Ethereum mainnet. Future support for related features is not ruled out.
At the application layer, Axiom can assist dapps in implementing the following functions:
The current leader in the coprocessor space, Axiom, has a complementary relationship with light node projects such as Succinct. Succinct attempts to prove the Ethereum consensus itself, while Axiom proves any on-chain historical data based on the consensus, assuming the consensus result is accepted.
The field of ZK proof is rapidly developing with innovative inventions like folding proofs, accumulation schemes, and large lookup tables. This growth has drawn attention to projects like Nexus, which support the latest advancements in ZK proof technology. While ZK proofs are becoming mainstream, other projects like Lagrange are also gaining notice for providing proofs for Rollup through parallel provers, thereby filling a market gap.
Ongoing tech advancements have boosted the performance of various knowledge proofs, shrinking their size and verification costs. And this broadens their potential usage. In this context, the flexibility provided by modularization is gaining recognition, particularly within the coprocessor space.”