Safe & secure Virtu Network wallet
Take control of your Virtu Network assets with complete confidence in the Trezor ecosystem.
- Secured by your hardware wallet
- Use with compatible hot wallets
- Trusted by over 2 million customers
Send & receive your Virtu Network with the Trezor Suite app
Send & receive
Trezor hardware wallets that support Virtu Network
Sync your Trezor with wallet apps
Manage your Virtu Network with your Trezor hardware wallet synced with several wallet apps.
Trezor Suite
MetaMask
Rabby
Supported Virtu Network Network
- Ethereum
Why a hardware wallet?
Go offline with Trezor
- You own 100% of your coins
- Your wallet is 100% safe offline
- Your data is 100% anonymous
- Your coins aren’t tied to any company
Online exchanges
- If an exchange fails, you lose your coins
- Exchanges are targets for hackers
- Your personal data may be exposed
- You don’t truly own your coins
How to VIRTU on Trezor
Connect your Trezor
Open a third-party wallet app
Manage your assets
Make the most of your VIRTU
Trezor keeps your VIRTU secure
Protected by Secure ElementThe best defense against both online and offline threats
Your tokens, your controlAbsolute control of every transaction with on-device confirmation
Security starts with open-sourceTransparent wallet design makes your Trezor better and safer
Clear & simple wallet backupRecover access to your digital assets with a new backup standard
Confidence from day onePackaging & device security seals protect your Trezor’s integrity
VirtuNetwork is a platform that streamlines access to high-performance computing resources, especially GPUs (Graphics Processing Units) and TPUs (Tensor Processing Units). These advanced hardware components are essential for handling intensive computational tasks, such as deep learning, large-scale data processing, and scientific simulations, which are beyond the capacity of standard computer processors.
One of the key advantages of VirtuNetwork is that it provides users with full control over powerful GPUs and TPUs, giving them the flexibility to configure and manage these resources according to their specific needs. This control is invaluable for researchers, data scientists, and businesses seeking optimized performance for tasks that demand large amounts of parallel processing. For instance, GPUs are ideal for handling tasks in artificial intelligence, machine learning, and image processing, while TPUs are tailored for tasks requiring efficient machine learning model training, especially for neural networks.