Block time is a sequential bottleneck. It measures the interval between linear blocks, a design that inherently limits throughput and creates latency. DAGs like Hedera Hashgraph and Nano abandon this model entirely, processing transactions asynchronously.
comparison-of-consensus-mechanisms
Blog
Why 'Block Time' is an Antique Metric in the Age of DAGs
Blockchain's foundational metric is obsolete. DAG-based consensus mechanisms decouple transaction inclusion from periodic block production, replacing block time with continuous streaming finality and latency as the true measure of performance.
introduction
THE OBSOLESCENCE
Introduction
Block time, the bedrock metric of blockchain performance, is now a misleading relic for modern DAG-based networks.
Finality, not latency, is the real metric. A 2-second block time with a 15-minute probabilistic finality is useless for finance. DAGs achieve sub-second finality by gossiping transactions directly, making block time an irrelevant comparison.
The industry standard has shifted. High-performance L1s like Solana (400ms slots) and L2s like Arbitrum Nitro (optimistic confirmation) already treat block time as a legacy dashboard widget, not a core architectural constraint.
thesis-statement
THE OBSOLESCENCE
The Core Argument: From Batches to Streams
Block time is a legacy metric for batch-based blockchains that fails to capture the continuous execution of modern DAG-based systems.
Block time measures latency, not throughput. It quantifies the interval between discrete, atomic state updates, a design artifact of Nakamoto Consensus and its derivatives. This metric is irrelevant for systems where transactions are processed continuously.
DAG-based ledgers like Solana and Aptos process transactions as a stream. Validators execute transactions as they arrive, with finality determined by optimistic confirmation or proof-of-stake voting. The concept of a 'block' is a post-hoc aggregation for data availability, not a processing barrier.
The correct metric is time-to-finality. This measures the latency from transaction submission to cryptographic irreversibility. For high-frequency DeFi or gaming, a 400ms finality on Solana is the operational reality, rendering a 12-second Ethereum block time an antique comparison.
Evidence: Solana's Sealevel parallel runtime and Aptos' Block-STM execute tens of thousands of transactions per second. Their performance is gated by hardware and network propagation, not an artificial, sequential block-production cadence.
key-trends
BEYOND BLOCK TIME
The Three Pillars of the Post-Block Era
Block time is a legacy constraint from sequential consensus. Modern DAG-based systems achieve finality through parallel processing and cryptographic attestations, not waiting for the next block.
01
Parallel Finality, Not Sequential Confirmation
Blockchains serialize transactions, creating a latency floor. DAGs like Avalanche and Solana (via Sealevel) process transactions concurrently. Finality is determined by the speed of attestation propagation, not a fixed time interval.
- Key Benefit: Sub-second finality vs. Ethereum's 12-second block time.
- Key Benefit: Eliminates orphaned blocks, increasing chain throughput efficiency.
<1s
Finality
~50k
Concurrent TX
02
The Latency/Censorship-Resistance Trade-Off is Dead
Fast block times historically meant fewer validators per slot, increasing centralization risk. DAG-based consensus (e.g., Narwhal-Bullshark, AptosBFT) decouples data dissemination from ordering, allowing high throughput without sacrificing decentralization.
- Key Benefit: Hundreds of validators can participate in a single consensus round.
- Key Benefit: Censorship resistance is baked into the data availability layer, not the block producer.
100+
Active Validators
>10k
TPS Potential
03
Fee Markets No Longer Need a Mempool
In blockchains, users bid for limited block space, leading to volatile fees. DAG architectures with leaderless consensus (e.g., Hedera Hashgraph) or localized fee markets (e.g., Solana's localized fee markets) eliminate the global auction, stabilizing costs.
- Key Benefit: Predictable, low fees (~$0.001) independent of network-wide congestion.
- Key Benefit: No front-running via mempool snooping, enhancing MEV resistance.
$0.001
Avg. Cost
-99%
Fee Volatility
THE DAG PARADIGM SHIFT
Block Time vs. Real-World Finality: A Performance Illusion
Compares traditional block-based finality metrics against modern DAG-based systems, exposing the latency gap between chain state and user settlement.
| Finality Metric / Feature | Traditional L1 (e.g., Ethereum PoS) | Parallelized L1 (e.g., Solana, Sui) | DAG-Based L1 (e.g., Kaspa, Nano) | Intent-Based Settlement (e.g., UniswapX, Across) |
|---|---|---|---|---|
Theoretical Block/Unit Time | 12 seconds | 400 milliseconds | < 1 second | N/A (Off-chain) |
Time to Probabilistic Finality (99.9%) | ~15 minutes (12-15 blocks) | ~2.5 seconds (6-7 slots) | ~1 second (instant confirmation) | N/A (Depends on solver) |
Time to Economic Finality (User Settlement) | ~15 minutes | ~2.5 seconds | ~1 second | < 1 second (via pre-signed fill) |
Throughput (Peak TPS) - Theoretical | ~100 TPS | ~65,000 TPS | ~10,000 TPS (Kaspa BPS) | Unlimited (off-chain auction) |
Throughput vs. Finality Trade-off | High (Slow, secure finality) | Medium (Fast, but probabilistic) | Low (Fast, near-instant finality) | None (Decouples execution from settlement) |
MEV Resistance at L1 | Low (Sequential blocks) | Very Low (Centralized sequencing) | High (BlockDAG consensus) | Very High (Batch auctions via CowSwap) |
Cross-Chain Settlement Latency | High (Depends on bridge finality) | High (Depends on bridge finality) | Medium (Faster source finality) | Very Low (Abstracted via layerzero, Across) |
deep-dive
THE DECOUPLING
How DAGs Decouple Inclusion and Ordering
DAG-based consensus separates transaction acceptance from final sequence, rendering traditional block time metrics obsolete.
Block time is a legacy metric that conflates two distinct processes: transaction inclusion and final ordering. In blockchains like Ethereum or Solana, these processes are serialized within a single block, creating a deterministic but slow cadence.
DAGs decouple these functions entirely. Protocols like Narwhal (used in Sui) and Avalanche separate the mempool from consensus. Nodes gossip and include transactions asynchronously, achieving inclusion latencies under 100ms, independent of finalization.
This enables parallel execution. With inclusion decoupled, validators in systems like Aptos process transactions in parallel based on the DAG's causal structure. This is the architectural foundation for their claimed 160k TPS, not a faster block clock.
The relevant metric is now finality time. For users and applications, the guarantee is when a transaction's position in the total order is immutable. DAG-based systems like Solana's Jito optimize for this, not for producing empty blocks on a fixed schedule.
counter-argument
THE OBSOLETE ABSTRACTION
The Steelman: Isn't Block Time Still Useful for Simplicity?
Block time is a legacy abstraction that misrepresents finality and throughput in modern DAG-based and parallelized systems.
Block time is a false proxy for user experience. The metric measures the interval between block proposals, not transaction finality. Users care about when their transaction is irreversible, not when a miner gossips a block. This distinction is critical for DeFi settlement and cross-chain operations via protocols like LayerZero and Wormhole.
DAGs decouple ordering from execution, rendering block time meaningless. Networks like Solana's Sealevel and Sui's Narwhal-Bullshark process transactions in parallel streams. A single 'block' can contain thousands of finalized transactions with variable internal latencies, making a monolithic block time metric an irrelevant average.
Throughput is the real metric. Block time obscures capacity. A 2-second block with 10,000 transactions (e.g., Arbitrum Nitro) offers higher real throughput than a 12-second block with 200 transactions. The industry standard is now Transactions Per Second (TPS) and Time to Finality (TTF), as tracked by L2Beat and other analytics platforms.
The simplicity argument is technical debt. Relying on block time encourages monolithic, sequential execution architectures. This limits scalability and creates bottlenecks that parallel execution engines like Aptos' Block-STM and Fuel's UTXO model are designed to eliminate. The abstraction has outlived its utility.
protocol-spotlight
THE DAG REVOLUTION
Architectural Spotlight: Who's Killing the Block?
Block time is a legacy constraint. Modern DAG-based architectures achieve finality in milliseconds by decoupling execution from consensus.
01
Solana's Parallel Execution Engine
Solana's Sealevel runtime treats the state as a DAG, allowing non-conflicting transactions to be processed simultaneously. This makes 'block time' irrelevant for throughput.
- Key Benefit: Enables 50k+ TPS by processing thousands of transactions in parallel.
- Key Benefit: Achieves ~400ms time to finality, making block propagation obsolete.
50k+
Peak TPS
~400ms
Finality
02
Aptos & Sui's Block-STM
These Move-based chains use a Software Transactional Memory model to optimistically execute all transactions in parallel, then validate and commit.
- Key Benefit: 160k+ TPS in controlled benchmarks by reordering failed transactions, not discarding them.
- Key Benefit: Sub-second finality without waiting for a canonical block order to be established.
160k+
Theoretical TPS
<1s
Finality
03
Narwhal & Bullshark (Mysten Labs)
This mempool/consensus decoupling creates a DAG of transaction data (Narwhal) for availability, then orders it (Bullshark). It's the engine behind Sui.
- Key Benefit: Separates bandwidth from consensus, allowing linear scaling with more validators.
- Key Benefit: Enables 120k TPS in benchmarks by eliminating block-based bottlenecks in data dissemination.
120k
Benchmark TPS
Linear
Scalability
04
The Problem: Sequential Block Production
Traditional blockchains like Ethereum and Bitcoin are single-threaded computers. Every node must process transactions in the order defined by a single leader, creating a hard bottleneck.
- Consequence: Block time dictates minimum latency, creating a trade-off with security (shorter blocks = more orphans).
- Consequence: Throughput is capped by single-node validation speed, not network capacity.
12s
Eth Block Time
~15
TPS (Eth L1)
05
The Solution: DAG-Based State Machines
Instead of a linear chain, these systems model state transitions as a directed acyclic graph. Consensus agrees on a partial order, not a strict sequence, for non-conflicting txns.
- Key Benefit: Finality-first design. Users get fast, firm commitments, not probabilistic confirmations.
- Key Benefit: Hardware utilization scales with cores and bandwidth, not clock speed.
Parallel
Execution
Milliseconds
Latency
06
The New Metric: Time-to-Finality (TTF)
The critical metric is no longer how often a block is produced, but how quickly a transaction is irreversibly settled. DAGs excel here by making data availability instantaneous.
- Key Benefit: Enables real-time DeFi and CEX-grade UX on-chain.
- Key Benefit: Renders MEV front-running via block timing structurally impossible.
TTF
New Benchmark
~0
Orphan Rate
takeaways
WHY BLOCK TIME IS OBSOLETE
TL;DR for CTOs and Architects
Block time is a legacy metric from linear chains. Modern DAG-based systems like Solana, Avalanche, and Sui decouple transaction ordering from finality, making latency and time-to-finality the only metrics that matter.
01
The Problem: Block Time Measures the Wrong Thing
Block time only measures the interval between empty data structures. It says nothing about when your transaction is actually settled. On a congested chain like Ethereum, a 12-second block time can mean minutes of inclusion latency and 12+ minutes for probabilistic finality. This creates false expectations for users and developers.
12s -> 12m
Latency vs. Finality
~0 TPS
During Congestion
02
The Solution: Measure Time-to-Finality (TTF)
TTF is the interval from transaction submission to cryptographic irreversibility. DAG architectures like Avalanche's Snowman++ achieve this in ~1-2 seconds. Solana's Tower BFT achieves 400ms optimistic confirmation and ~2.5s finality. This is the only metric that guarantees state security for your application.
<2s
Avalanche TTF
~2.5s
Solana Finality
03
The Architecture: Pipelining & Leaderless Consensus
DAGs and parallel execution engines (Sui's Narwhal-Bullshark, Aptos' Block-STM) separate transaction dissemination, ordering, and execution. This allows for sub-second latency and linear scalability with cores. Block time is irrelevant here; the system's throughput is gated by network bandwidth and CPU cores, not an artificial sequencing cadence.
160k+ TPS
Sui Testnet Peak
~300ms
Latency Floor
04
The Implication: Rethink Your Service-Level Agreements (SLAs)
If you're building a perp DEX, payment rail, or game, your SLA is based on finality, not block production. Architect for systems with deterministic, sub-3s TTF. This eliminates front-running uncertainty and enables real-time user experiences. Block time is a vanity metric; TTF is a business requirement.
Sub-3s
SLA Target
~100%
Uptime Expectation
05
The Ecosystem Shift: Fast Finality is Table Stakes
L2s are racing to reduce TTF via innovations like EigenDA's fast confirmation, Arbitrum BOLD, and zk-rollup validity proofs. Even Ethereum's roadmap targets single-slot finality. The competitive landscape is now defined by finality speed, rendering the old block time comparisons between L1s meaningless.
Single-Slot
Ethereum Goal
~1s
zk-Rollup Proof Finality
06
The Action: Audit Your Stack's True Latency
- Instrument your app to log submission-to-finality delay, not block inclusion.\n2. Pressure your infra providers (RPCs, oracles, indexers) to provide TTF metrics.\n3. Evaluate chains & L2s on their p95 TTF under load, not marketed block times. The tech that wins is the one that makes latency invisible.
P95 TTF
Key Metric
Instrument
Required Action
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