Solana vs Sui: Execution Latency

Optimized for raw speed: Leverages Proof of History (PoH) for a global clock, enabling deterministic transaction ordering and parallel execution via Sealevel. This architecture consistently achieves ~400ms block times and sub-second finality on mainnet. This matters for high-frequency trading (HFT), real-time gaming, and consumer applications where user experience is critical.

Massive parallelization: Solana's architecture allows thousands of smart contracts (programs) to execute simultaneously across GPU cores. This enables a theoretical peak of 65,000 TPS and sustains high throughput under load for protocols like Jupiter (DEX aggregator) and Tensor (NFT marketplace). This matters for scaling decentralized exchanges and NFT mints with minimal congestion.

Eliminates contention: Sui's Move-based object model allows transactions affecting independent objects (e.g., NFTs, tokens) to bypass consensus entirely, achieving instant finality. This 'simple transactions' path provides ~100-200ms latency for most user actions. This matters for gaming assets, social feeds, and payment systems where most operations are independent.

Consensus-on-demand: Only transactions sharing objects (e.g., AMM pool swaps) require Narwhal & Bullshark consensus, which is optimized for low latency even under complex coordination. This design prevents network-wide congestion from affecting unrelated activities. This matters for DeFi protocols (e.g., Cetus, FlowX) and shared-state applications that require guaranteed, predictable execution times.

Leader-based streaming: Solana's single global state and Tower BFT consensus provide 400ms optimistic confirmation. This is critical for order-book DEXs (e.g., Phoenix) and real-time gaming where perceived speed is paramount.

Congestion sensitivity: Under network spam (e.g., memecoin launches), the single-threaded execution model can cause queueing delays and failed transactions. This requires complex client-side retry logic, as seen during the $JUP airdrop congestion.

Object-centric design: Sui's Narwhal & Bullshark DAG consensus and Move-based ownership allow independent transactions to finalize in parallel. This provides predictable sub-second latency even during high demand, ideal for mass-scale gaming and social apps.

BFT consensus required: Transactions modifying shared objects (e.g., a common liquidity pool) must go through full BFT consensus, adding latency. This creates a bimodal latency profile where performance depends heavily on application design.

Sealevel Runtime: Processes up to 128,000 non-conflicting transactions in parallel per block. This is ideal for high-throughput DeFi (e.g., Jupiter DEX aggregator) and NFT mints where operations are independent, achieving sub-400ms finality.

Trade-off: All validators process the same state. Contention on popular accounts (e.g., JUP, Raydium pools) causes congestion, spiking latency and causing failed transactions during peak load. Requires careful state architecture.

Narwhal-Bullshark Consensus: Separates transaction dissemination from ordering. For single-owner object transactions (simple transfers, P2P games), Sui bypasses consensus entirely, enabling sub-100ms latency and predictable gas fees.

Trade-off: Transactions involving shared objects (e.g., DeFi pools, order books) require full consensus via Bullshark, adding latency. While still fast, it converges with other high-performance chains, making complex app performance more variable.