As blockchain has evolved from simple transaction systems into complex programmable networks, more and more computation is moving from on-chain to off-chain execution. Scenarios such as Rollup scaling, cross-chain bridges, AI inference, oracles, and off-chain data processing all need a technical solution that can prove "computational results are true and trustworthy."
Zero-Knowledge Proof (ZK Proof) has become a key technology in the Web3 infrastructure to address this need. They allow a system to prove that a program has been correctly executed without revealing the original data. However, traditional ZK development has long suffered from high barriers to entry. Developers often must learn complex cryptographic constraint systems, specialized DSLs, and low-level circuit logic, making it hard for ZK technology to achieve widespread adoption.
The SP1 zkVM attempts to solve this problem.
What Is the SP1 zkVM?
As a general-purpose zero-knowledge virtual machine (zkVM) launched by Succinct, the SP1 zkVM lets developers write programs directly in Rust and automatically generate verifiable ZK Proof without needing to manually write cryptographic circuits.
Traditional ZK systems typically rely on specialized languages like Circom, Halo2, Cairo, or Noir. While powerful, these systems are difficult to develop with, requiring deep understanding of underlying cryptographic logic.
The SP1 zkVM takes a completely different design approach.
Developers only need to write programs just like normal software development, and the system automatically handles the remaining proof generation process. Succinct calls this concept "Code as Proof." This means any runnable program can theoretically be transformed into a verifiable computation.
How Does the SP1 zkVM Differ From Traditional Virtual Machines?
Ordinary virtual machines (VMs) — such as EVM, WASM, and JVM — primarily handle program execution. They focus on execution efficiency, memory management, and state updates. A zkVM, on the other hand, not only runs the program but also proves that the program was correctly executed.
Therefore, in addition to executing the program, a zkVM must also: record the complete execution process, build mathematical constraints, generate a proof, and provide verifiability to external systems.
At its core, a zkVM is more like a "provable execution environment." It not only runs the program but also convinces others that the program's execution results are true and trustworthy.
Why Did SP1 Choose RISC-V?
The SP1 zkVM's underlying execution architecture is based on the RISC-V instruction set.
RISC-V is an open-source, reduced instruction set architecture known for its simple structure, clear logic, and ease of formal verification. This is critical for a zkVM because the more complex the CPU instructions, the harder it becomes to generate proofs.
Compared to complex CPU architectures, RISC-V is much easier to convert into a system of mathematical constraints.
SP1's complete workflow does not generate proofs directly from Rust programs. Instead, it follows:
Rust → RISC-V → zkVM Execution → Proof
Thus, RISC-V acts as the "intermediate execution layer" in the whole system.
Why Is Rust Suitable for a zkVM?
Succinct chose Rust mainly because it is well-suited for verifiable computation.
First, Rust offers extremely high performance. Since proof generation itself demands significant computational resources, system-level language performance is crucial.
Second, Rust has excellent memory safety features. Its ownership model reduces runtime errors, helping the system produce more stable execution traces.
Additionally, Rust's determinism is very important.
In a zkVM, the same input must always produce the same output. Otherwise, different nodes could generate different proofs.
Rust naturally excels in determinism, making it an excellent choice for zkVM development.
More importantly, Rust is already widely used in Solana, Cosmos, Rollup, and system development, so the developer ecosystem is mature and migration costs are low.
How Does a Rust Program Become a ZK Proof?
The core flow of the SP1 zkVM includes:
Write Rust program → Compile to RISC-V → zkVM execution → Generate Execution Trace → Convert to STARK Proof → Compress to SNARK → On-chain verification.
The central goal of this entire flow is to prove: "The program was correctly executed according to the rules."
Step 1: Write a Rust Program
Developers first write business logic in Rust.
These programs can be used for Rollup state transitions, AI model inference, cross-chain verification, hash computation, data processing, and Oracle systems.
In traditional ZK development, developers often have to manually write complex circuits. But in SP1, they only need to write ordinary Rust programs.
For example:
fn main() {
let x = 10;
let y = 20;
let z = x + y;
assert_eq!(z, 30);
}
SP1 automatically converts this program into a verifiable proof.
This dramatically reduces the ZK development barrier.
Step 2: Compile to RISC-V Instructions
The Rust program is then compiled to RISC-V instructions.
Since the proof system cannot directly verify high-level languages, it can only verify the underlying machine execution process.
The compiler translates Rust into a low-level instruction stream, such as:
ADD x1, x2, x3
LOAD x4, 0(x5)
STORE x6, 4(x7)
These instructions are then executed by the zkVM.
The most important goal at this stage is to ensure the program is deterministic and verifiable.
Why Is Determinism So Important?
In ordinary programs, timing, random numbers, and system state can all affect execution results.
But in a zkVM, the same input must always yield the same output.
Otherwise, different nodes might generate different traces, eventually making the proof unverifiable.
Therefore, zkVMs typically strictly limit access to external state and ensure the entire execution process is completely deterministic.
This is one of the biggest differences between a zkVM and a regular virtual machine.
Step 3: zkVM Execution Generates an Execution Trace
The SP1 zkVM executes the RISC-V instructions and records the complete execution process.
This process is called:
Execution Trace.
Think of it as:
A "video recording of the program execution."
The trace records every state change during program execution, including:
Instruction execution process, CPU state changes, memory changes, register states, and input/output relationships.
For example:
Step 1: LOAD
Step 2: ADD
Step 3: STORE
Step 4: ASSERT
The proof system then proves that these steps actually occurred correctly.
Why Is the Trace the Core of the Entire System?
Because a ZK Proof isn't fundamentally about proving that a "result exists."
What it truly proves is:
"The program was correctly executed according to the rules."
Therefore, the Execution Trace determines the credibility of the entire proof.
If the trace contains errors, the final generated proof will also be invalid.
Step 4: Trace Is Converted Into a STARK Proof
After the Execution Trace is generated, the system converts it into mathematical constraints.
This stage typically uses techniques such as AIR (Algebraic Intermediate Representation), polynomial constraint systems, and hash commitments.
The system then generates a STARK Proof.
The advantages of STARK are:
No trusted setup, high security, quantum resistance, and excellent scalability.
That's why many modern zkVMs adopt STARK as the underlying proof system.
However, STARK has a notable drawback:
Proofs are relatively large.
So further optimization is needed.
Step 5: STARK Compressed Into a SNARK
To reduce on-chain verification costs, SP1 typically further compresses the STARK into a SNARK.
This design combines the strengths of both proof systems:
STARKs are fast to generate, while SNARKs have low on-chain verification costs.
Thus, SP1 can balance:
Proof generation efficiency, on-chain Gas costs, and overall network scalability.
The final SNARK proof is submitted to blockchains like Ethereum for verification.
What Is a Recursive Proof?
Recursive proofs are a key technology in modern zkVMs.
It allows:
One proof to verify another proof.
For example, multiple Rollup proofs can each be generated individually, then aggregated into a larger proof.
Finally, only a single verification is needed on-chain.
Recursive proofs can significantly reduce on-chain verification costs and network load, making them essential for large-scale verifiable computation.
How Does the SP1 zkVM Differ From zkEVM?
Many developers confuse zkVM and zkEVM.
But their goals are actually completely different.
zkEVM's core purpose is to be compatible with the Ethereum EVM, so it focuses primarily on Solidity and EVM bytecode.
The SP1 zkVM, by contrast, is oriented toward general-purpose verifiable computation.
It can not only execute Smart Contract logic, but also handle AI inference, data processing, cross-chain logic, and any Rust program.
Therefore:
zkEVM is more of an Ethereum scaling solution.
SP1 zkVM is more like a general-purpose proof infrastructure.
Core Advantages of the SP1 zkVM
SP1's biggest advantage is that it dramatically lowers the barrier to ZK development.
Developers no longer need to manually write complex cryptographic circuits. Instead, they can directly build verifiable applications using Rust.
At the same time, SP1 offers strong generality, supporting recursive proofs, modular expansion, and low-cost on-chain verification.
These capabilities make it suitable not only for Rollups but also for broader scenarios like AI, cross-chain, and off-chain computation.
Typical Application Scenarios of the SP1 zkVM
The SP1 zkVM is already being adopted across multiple fields.
In Rollups, it generates state transition proofs; in cross-chain protocols, it verifies the authenticity of state between different chains; in AI, it validates model inference results; and in Oracle systems, it verifies complex off-chain data computations.
Long term, SP1's more important goal is to advance the "verifiable internet."
In the future:
APIs, web pages, database queries, and even AI content could all be verified for authenticity through proofs.
What Challenges Does the SP1 zkVM Face?
Despite the promising outlook, SP1 still faces practical challenges.
First, generating complex proofs remains costly, requiring significant GPU and hardware resources.
Second, a general-purpose zkVM must simultaneously balance performance, security, and generality, which makes it far more technically complex than dedicated circuit systems.
Additionally, the zkVM landscape is highly competitive, with projects like RISC Zero, zkSync, Starknet, Valida, and Jolt all pushing in different directions.
Meanwhile, the verifiable computation market is still in its early stages, and large-scale demand has yet to fully materialize.
Conclusion
The SP1 zkVM is redefining how zero-knowledge proofs are developed.
Through Rust programming, RISC-V execution, Execution Traces, STARK/SNARK compression, and recursive proofs, Succinct has built a general-purpose verifiable computation infrastructure.
Developers no longer need to understand complex ZK circuits; they can build verifiable applications just like normal software development.
FAQs
Why Did SP1 Choose RISC-V?
Because RISC-V instructions are simple, open-source, and easy to formally verify, making them more suitable for building a zkVM.
Why Is Rust Suitable for a zkVM?
Rust offers high performance, determinism, and memory safety — all ideal for a verifiable computing environment.
What Are the Steps in Generating a ZK Proof?
The main steps include: writing a Rust program, compiling to RISC-V, executing in the zkVM to generate a trace, producing a STARK/SNARK proof, and on-chain verification.
How Is the SP1 zkVM Different From Traditional ZK Systems?
Traditional systems require dedicated DSLs and manual circuit writing, whereas SP1 supports general-purpose languages and automatically generates proofs.
What Are the Application Scenarios of the SP1 zkVM?
They include Rollup scaling, cross-chain verification, AI verifiable computation, oracles, and off-chain computation.
