Polygon vs OpenGPU Network Scalability
Real-time TPS
Polygon TPS is 36.49 tx/s, while OpenGPU Network has no data
Max TPS (100 blocks)
Polygon max TPS is 429.1 tx/s, while OpenGPU Network has no data
Max Theoretical TPS
Polygon max theoretical TPS is 714.3 tx/s, while OpenGPU Network has no data
Transaction Volume
Polygon transaction volume is 131,369 txns, while OpenGPU Network has no data
Block Time
Polygon block time is 2.13s, while OpenGPU Network has no data
Finality
Polygon finality is 5s, while OpenGPU Network has no data
Type
Polygon is a sidechain, while OpenGPU Network has no data
Launch Date
Polygon was launched on May 30, 2020, while the OpenGPU Network has no data
Polygon vs OpenGPU Network Decentralization New
Nakamoto Coefficient
Polygon Nakamoto Coefficient is 4, while OpenGPU Network has no data
Validators/Miners
Polygon has 105 validators, while OpenGPU Network has no data
Stake/Hashrate
Polygon stake is $809.8M, while OpenGPU Network has no data
Consensus Mechanism
Polygon is PoS, while OpenGPU Network has no data
Governance
Polygon governance is off-chain, while OpenGPU Network has no data
Other Comparisons
Polygon Comparisons
About Blockchains
About Polygon
Polygon, formerly Matic Network, is a blockchain platform designed to establish a multi-chain system compatible with Ethereum. It employs a proof-of-stake consensus mechanism similar to Ethereum for on-chain transactions, with its native token being POL. Functioning as a "layer two" or "sidechain" scaling solution alongside Ethereum, Polygon facilitates quicker transactions and lower fees. Its inception aimed to tackle Ethereum's major challenges, including high fees, subpar user experience, and limited transaction throughput, aspiring to create an "Ethereum's internet of blockchains" or a multi-chain ecosystem of Ethereum-compatible blockchains.
About OpenGPU Network
OpenGPU is a decentralized computing platform based on blockchain technology. It aims to address the computational demand pressure faced by current centralized cloud computing platforms by utilizing globally distributed GPU computing resources.