Why the Battle Between SNARKs and STARKs Is Just Beginning

Proof generation is the primary bottleneck, measured in dollars and seconds. The race is to build specialized hardware (ASICs, FPGAs) and optimized software stacks to make ZK proofs viable for high-frequency applications.

• Key Players: Ulvetanna (FPGA), Ingonyama (ASIC), Cysic (Accelerator).
• Target: Sub-$0.01 cost for a ~1M gas Ethereum transaction proof.
• Implication: The winning hardware stack will dictate the economic model of major L2s like zkSync, Starknet, and Polygon zkEVM.

A single proof verifying other proofs is the key to scaling. Recursion enables parallel proof generation and seamless interoperability, turning a blockchain into a verifiable compute platform.

• Mechanism: Starknet's SHARP and Polygon's Plonky2 use recursion to batch thousands of transactions.
• Endgame: A single proof for an entire day of L2 activity, settling to Ethereum in one transaction.
• Limit: Recursive depth is constrained by circuit complexity and prover memory, creating a direct link to the hardware race.

Trustlessness requires every user to verify state transitions. The fight is to make proof verification so lightweight it can run in browsers and mobile wallets, eliminating any trusted intermediary.

• SNARK Advantage: Smaller proof sizes (~1 KB) are inherently mobile-friendly.
• STARK Challenge: Larger proofs (~100 KB) but quantum-resistant; requires aggressive optimization for client-side WASM.
• Who Wins?: The system that achieves <100ms verification on a smartphone becomes the default for bridges, wallets, and on-chain games.

The dominant paradigm, built on recursive proof composition and trusted setups. Teams choose this for existing tooling and EVM compatibility, accepting the security and centralization risks of a ceremony.

• Key Benefit: Mature ecosystems (e.g., zkSync, Polygon zkEVM, Scroll) with ~100ms proof times for simple txs.
• Key Benefit: Plonk and Groth16 offer small proof sizes (~1KB), minimizing on-chain verification gas costs.

A bet on long-term scalability via cryptographic elegance. No trusted setup, quantum-resistant, and inherently parallelizable. The cost is a steeper learning curve and proprietary VMs.

• Key Benefit: StarkWare's Cairo VM enables ~1000 TPS on L2 with proofs that scale logarithmically.
• Key Benefit: RISC Zero brings general-purpose ZKMs to any chain, enabling verifiable off-chain computation for EigenLayer, Avail.

The emerging meta-strategy: abstract the proving layer entirely. These protocols act as proof co-processors, letting developers choose the best prover for each job and aggregate results.

• Key Benefit: Succinct's SP1 allows teams to write ZK-circuits in Rust, bypassing DSL lock-in.
• Key Benefit: =nil; Foundation's Proof Market creates a decentralized marketplace for proof generation, commoditizing the hardware layer.

The battle moves to silicon. SNARKs (Groth16, Plonk) are ASIC-friendly, leading to specialized hardware from Ingonyama, Cysic. STARKs are GPU-optimized, leveraging existing NVIDIA infrastructure.

• Key Benefit: ASICs can drive prover costs down 1000x, making ZK-Rollups viable for ~1 cent fees.
• Key Benefit: GPU ecosystems benefit from continuous performance gains and avoid single-supplier risk.

Winning ecosystems will be those that can verify foreign proofs. This is the next frontier for interoperability layers like LayerZero, Polymer, and Hyperlane.

• Key Benefit: A rollup using StarkEx could permissionlessly settle on an EVM chain via a SNARK-wrapped STARK proof.
• Key Benefit: Breaks vendor lock-in, allowing applications to migrate or compose across zkSync, Starknet, and Polygon without friction.

Why choose? Architectures like Polygon's zkEVM and Taiko use STARKs for execution proofs and a final SNARK for compression, optimizing for both prover speed and cheap on-chain verification.

• Key Benefit: Leverages STARK's parallel speed for the heavy lifting and SNARK's tiny proof size for final L1 settlement.
• Key Benefit: Creates a modular proving pipeline where each component can be upgraded independently as cryptography advances.

SNARKs (zk-SNARKs) rely on a one-time trusted ceremony but deliver compact proofs and fast verification. This is the go-to for high-frequency, cost-sensitive applications.

• Proof Size: ~200 bytes (tiny, cheap on L1)
• Verification Speed: ~10ms on Ethereum
• Dominant Use: Privacy apps (Zcash), scaling rollups (zkSync Era, Scroll).

STARKs (zk-STARKs) eliminate trusted setups and are post-quantum secure. Their computational overhead is higher, but they scale better for massive batches.

• Key Trade-off: Larger proofs (~45-200KB) but O(log n) scaling.
• Verification Cost: Higher on L1, but negligible per-tx in a batch.
• Dominant Use: High-throughput validity rollups (Starknet, Polygon zkEVM).

The endgame isn't SNARKs or STARKs—it's recursive proof systems that use one to prove the other. This enables layer-3 appchains and decentralized prover networks.

• Recursion: Starknet uses STARKs, then wraps in a SNARK for cheap L1 verification.
• Prover Markets: Projects like Risc Zero and Succinct are commoditizing proof generation.
• Implication: Your stack will consume proofs as a service, agnostic to the underlying cryptography.

Leading teams are adopting hybrid models, picking the optimal proof for each layer. This pragmatism maximizes performance and minimizes cost.

• Example: Polygon zkEVM uses SNARKs for execution proofs and STARKs for faster prover time, then recursively aggregates.
• Tooling: Plonky2 (SNARK-friendly STARKs) and Boogin (SNARK recursion) blur the lines.
• Action: Design your proving pipeline, don't just choose a family. The optimal stack is a multi-proof pipeline.