- Compare
- Sirius vs OpenGPU Network
Sirius vs OpenGPU Network Scalability
Real-time TPS
Sirius TPS is 0.0058 tx/s, while OpenGPU Network has no data
Max TPS (100 blocks)
Sirius max TPS is 5.4 tx/s, while OpenGPU Network has no data
Max Theoretical TPS
Sirius max theoretical TPS is 6,279 tx/s, while OpenGPU Network has no data
Transaction Volume
Sirius transaction volume is 21 txns, while OpenGPU Network has no data
Block Time
Sirius block time is 15s, while OpenGPU Network has no data
Finality
Sirius finality is 0s, while OpenGPU Network has no data
Type
Sirius is a layer 1 blockchain, while OpenGPU Network has no data
Launch Date
Sirius was launched on Sep 24, 2019, while the OpenGPU Network has no data
Sirius vs OpenGPU Network Decentralization New
Nakamoto Coefficient
Sirius and OpenGPU Network have no data
Validators/Miners
Sirius and OpenGPU Network have no data
Stake/Hashrate
Sirius and OpenGPU Network have no data
Consensus Mechanism
Sirius is PoS, while OpenGPU Network has no data
Governance
Sirius governance is multisig, while OpenGPU Network has no data
Other Comparisons
Sirius Comparisons
OpenGPU Network Comparisons
About Blockchains
About Sirius
Sirius aims to offer a suite of primary services including blockchain, storage, streaming, and Supercontract. Its architecture allows for the seamless addition of future services without compromising performance. These services are managed and governed by robust consensus protocols, ensuring network integrity while incentivizing decentralized participation. With its parallelized services and protocols organized into distinct layers, Sirius is flexible, easy to adopt, fast, and secure. Packaged within an all-in-one extensible framework, the Sirius ecosystem is well-suited for a range of applications including dApps, DeFi, NFTs, Web3, and beyond.
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.