Monad has shattered expectations in the EVM ecosystem by consistently hitting 10,000 transactions per second (TPS) on its mainnet, a feat validated through rigorous benchmarks using real Ethereum transactions. This isn’t hype; it’s engineered reality powered by Monad parallel execution, which redefines throughput without compromising Ethereum compatibility. As of late 2025, developers are migrating dApps seamlessly, capitalizing on 400ms block times and 800ms finality that legacy chains can only dream of.
Traditional EVM chains like Ethereum process transactions sequentially, creating inherent bottlenecks where each tx waits for the previous one to update state. Monad flips this script with its parallel execution engine, identifying independent transactions-those without overlapping accounts or contract states-and executing them concurrently across CPU cores. Benchmark tests confirm up to 10,000 TPS, with testnets previously peaking at 5,000 TPS and handling 334 million RPC requests in just 12 hours.
Parallel Execution Engine: The Core Throughput Multiplier
At the heart of EVM parallelization 2025 lies Monad’s ability to analyze transaction dependencies upfront. Validators scan mempool txs, tagging conflicts based on read/write sets. Non-conflicting txs run in parallel, leveraging superscalar pipelining for maximum hardware utilization. This deterministic approach ensures reproducibility, a critical nod to EVM’s single-threaded legacy while scaling linearly with node resources.
Monad’s engineering centers on parallel execution and deterministic state updates to hit its 10k TPS target.
Numbers don’t lie: Monad outpaces Ethereum’s 15-30 TPS by orders of magnitude. Real-world DeFi workloads, with their frequent token transfers and oracle calls, execute without serialization delays, slashing latency and unlocking new dApp paradigms like real-time trading bots and high-frequency yield farms.
Deferred Execution: Decoupling Consensus from Computation
MonadBFT consensus, inspired by HotStuff, agrees on transaction order first in a single round, achieving sub-second finality. Execution defers post-consensus, allowing parallel processing unbound by validator synchronization. This deferred execution model cuts block production to 400ms, with full finality in 800ms-single-slot guarantees that fortify against reorgs.
Contrast this with sequential chains: consensus and execution entwine, inflating times. Monad’s split optimizes both; validators focus on ordering, executors on crunching txs. The result? Sustained 10k TPS under load, proven in stress tests mimicking Ethereum mainnet traffic.
Solana Technical Analysis Chart
Analysis by Grant Holloway | Symbol: BINANCE:SOLUSDT | Interval: 1h | Drawings: 6
Technical Analysis Summary
On this SOLUSDT Heikin Ashi chart, draw a bold red downtrend line connecting the swing high at 190 on Dec 7 to the recent low at 128 on Dec 25, extending it forward for projection. Add horizontal resistance lines at 150 (moderate) and 175 (strong), support at 128 (strong) and 120 (weak). Overlay Fib retracement from Dec 7 high to Dec 25 low, highlighting 38.2% at ~152 and 61.8% at ~140. Mark a distribution rectangle from Dec 15 (175) to Dec 25 (128). Place arrow_mark_down at MACD bearish crossover around Dec 20. Use callout for volume spike on downside Dec 22 breakdown. Vertical line at Dec 22 for key breakdown event. Short position marker at 140 entry, profit target 120, stop loss 152.
Risk Assessment: high
Analysis: Crypto volatility amplified by L1 competition (Monad 10k TPS threat), downtrend intact with no bullish reversal signals—high reward skews odds
Grant Holloway’s Recommendation: Go aggressive short at 140, 5x leverage play for day-traders; trail stops ruthlessly. Data says ride the dump to 120.
Key Support & Resistance Levels
📈 Support Levels:
-
$128 – Recent swing low with volume cluster, strong confluence
strong -
$120 – Psych round number extension, prior consolidation base
weak
📉 Resistance Levels:
-
$142 – Fib 23.6% retrace and recent high
moderate -
$150 – Broken support turned resistance, high volume rejection
strong
Trading Zones (high risk tolerance)
🎯 Entry Zones:
-
$140 – Aggressive short on resistance rejection, high R:R 1:4 potential
high risk
🚪 Exit Zones:
-
$120 – Measured move target from range expansion
💰 profit target -
$152 – Tight stop above channel and Fib 38.2%
🛡️ stop loss
Technical Indicators Analysis
📊 Volume Analysis:
Pattern: Climactic increase on downside breaks
Bearish divergence resolved with distribution volume spike Dec 22, confirming seller control
📈 MACD Analysis:
Signal: Bearish crossover with expanding histogram
MACD line sliced below signal Dec 20, momentum accelerating south—stats show 85% continuation prob
Applied TradingView Drawing Utilities
This chart analysis utilizes the following professional drawing tools:
Disclaimer: This technical analysis by Grant Holloway is for educational purposes only and should not be considered as financial advice.
Trading involves risk, and you should always do your own research before making investment decisions.
Past performance does not guarantee future results. The analysis reflects the author’s personal methodology and risk tolerance (high).
MonadDB: Asynchronous Storage for Linear Scaling
Parallel execution demands parallel storage. Enter MonadDB, a custom engine bypassing I/O serialization via asynchronous operations. Traditional Merkle Patricia tries lock state access; MonadDB uses a multi-threaded trie with versioned snapshots, enabling concurrent reads/writes without contention.
Performance metrics: 375 million gas per second, dwarfing Ethereum’s peaks. Nodes scale with SSDs and RAM, no custom hardware needed. For developers, this means EVM tools unchanged, yet apps fly at 10k TPS EVM chain speeds. DeFi protocols report 10x faster settlements; NFT mints handle floods without gas wars.
This trifecta-parallel execution, deferred model, MonadDB-propels Monad as the high-performance EVM L1 benchmark. But how does it stack against rivals in live deployments?
Live mainnet data as of November 2025 paints a clear picture: Monad sustains 10,000 TPS under real DeFi loads, where Solana falters at peaks above 2,000 TPS and Ethereum hovers below 30. Independent audits confirm Monad’s edge, with 400ms blocks processing Ethereum-equivalent transactions at scale. This isn’t theoretical; it’s deployed reality transforming high-frequency applications.
Performance Comparison: Monad vs. Competitors
| Blockchain | TPS | Block Time | Finality | EVM Compatibility |
|---|---|---|---|---|
| Monad | 10,000 | 400 ms | 800 ms | ✅ Yes |
| Ethereum | 15-30 | ~12 s | Probabilistic (~12-15 min) | ✅ Yes |
| Solana | 2,000 (peak) | ~400 ms | ~1-2 s | ❌ No |
| Sui | 10,000 (claimed) | ~390 ms | ~390 ms | ❌ No |
MonadBFT Consensus: Sub-Second Finality at Scale
MonadBFT elevates the stack, delivering single-slot finality in 800ms via pipelined HotStuff variants. Validators propose, vote, and commit in one round, decoupling from execution overhead. Quantitative edge: 99.99% uptime in testnets, zero reorgs under 10k TPS floods. Compared to Ethereum’s probabilistic finality or Solana’s multi-slot waits, MonadBFT asserts deterministic security without throughput trade-offs.
Stress tests reveal Monad handling 375 million gas/second, equivalent to Ethereum mainnet’s yearly volume in hours. Parallel execution identifies 70-80% independent txs in DeFi mempools, executing them across 128 threads. Deterministic ordering via read/write sets prevents race conditions, ensuring EVM bytecode fidelity.
Real-World Benchmarks: 10k TPS Validated on Mainnet
Benchmarks using Ethereum’s top 100 contracts clock Monad at 10,000 TPS sustained, 400ms blocks, outstripping rivals. Testnet v0.5 hit 5,000 TPS with 334 million RPCs in 12 hours; mainnet doubles that. Latency metrics: average 200ms tx inclusion, versus Ethereum’s 12-second averages. For Monad mainnet performance, this translates to viable high-frequency trading, where microseconds matter.
Versus traditional EVM chains, Monad’s parallelization yields 300x throughput gains. Solana’s 50,000 TPS claims crumble under EVM workloads; its non-EVM Rust limits portability. Monad ports Uniswap V3 verbatim, achieving 50x faster swaps.
MonadDB’s async I/O shines here: 100x faster state commits than geth-level databases. Multi-version tries snapshot states per tx, enabling parallel commits without locks. Nodes on commodity hardware-Intel Xeons, NVMe SSDs-scale to 20k TPS with RAM upgrades, linear not exponential.
Developer Advantages: Seamless EVM Migration, Explosive dApp Potential
Full EVM compatibility means zero code changes. Foundry, Hardhat, Remix work out-of-box. RPCs mirror Ethereum JSON-RPC, archive nodes via MonadDB index historical states instantly. Developers report 10x faster iteration cycles; simulations predict real-time AMMs rivaling CeFi.
DeFi TVL surges: protocols like parallelized perpetuals hit $500M in weeks. NFT platforms mint 10,000 items/block sans frontrunning. High performance EVM L1 status attracts enterprises; confidential compute layers integrate via zkEVM rollups at native speeds.
Gaming dApps leverage 800ms finality for turn-based economies without lag. SocialFi apps process likes, tips at Twitter-scale. Quantitative models forecast Monad capturing 15% EVM market share by 2026, driven by 10k TPS EVM chain economics.
RPC providers benchmark Monad nodes at 1ms latency, half Solana’s. Paid tiers from Alchemy, Infura optimize for parallel queries, filtering mempools by dependency graphs. This infrastructure cements developer lock-in.
Monad’s ascent redefines EVM limits. Parallel execution, MonadBFT, MonadDB form an unbreakable trio, delivering 10,000 TPS where others stall. Deploy today; the data demands it.
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