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What is Verda?

Verda is a premium AI infrastructure platform built to accelerate modern machine learning workflows. It provides high-end GPU servers, clusters, and inference services without the friction of traditional cloud providers. Developers can instantly deploy NVIDIA Blackwell-based GPU clusters ranging from 16 to 128 GPUs. Each node is equipped with massive GPU memory, high-core CPUs, and ultra-fast networking. Verda supports both training and inference at scale through managed clusters and serverless endpoints. The platform is designed for rapid iteration, allowing teams to launch workloads in minutes. Pay-as-you-go pricing ensures cost efficiency without long-term commitments. Verda emphasizes performance, offering dedicated hardware for maximum speed and isolation. Security and compliance are built into the platform from day one. Expert engineers are available to support users directly. All infrastructure is powered by 100% renewable energy. Verda enables organizations to focus on AI innovation instead of infrastructure complexity.

What is NVIDIA virtual GPU?

NVIDIA's virtual GPU (vGPU) software provides exceptional GPU performance critical for tasks such as graphics-heavy virtual workstations and sophisticated data science projects, enabling IT departments to leverage virtualization while benefiting from the powerful capabilities of NVIDIA GPUs for modern workloads. Installed on a physical GPU in a cloud or enterprise data center server, this software creates virtual GPUs that can be allocated across multiple virtual machines, allowing users to connect from any device, regardless of location. The performance delivered mirrors that of a traditional bare metal setup, ensuring a smooth user experience akin to working directly on dedicated hardware. Moreover, it integrates with standard data center management tools, supporting features such as live migration and the flexible allocation of GPU resources through fractional or multi-GPU virtual machine instances. This adaptability is especially advantageous for meeting shifting business demands and enabling remote workforce collaboration, ultimately driving enhanced productivity and operational efficiency. Furthermore, the ability to scale resources on-demand allows organizations to respond swiftly to changing workloads, making NVIDIA's vGPU a valuable asset in today's fast-paced digital landscape.

Media

Media

Integrations Supported

AWS Marketplace
Armet AI
Azure Marketplace
IBM Spectrum LSF Suites
IONOS Cloud GPU Servers
IREN Cloud
Mistral Compute
NVIDIA Base Command Manager
NVIDIA Magnum IO
NVIDIA TensorRT
Notenic
SF Compute
Shadeform
WaveSpeedAI

Integrations Supported

AWS Marketplace
Armet AI
Azure Marketplace
IBM Spectrum LSF Suites
IONOS Cloud GPU Servers
IREN Cloud
Mistral Compute
NVIDIA Base Command Manager
NVIDIA Magnum IO
NVIDIA TensorRT
Notenic
SF Compute
Shadeform
WaveSpeedAI

API Availability

Has API

API Availability

Has API

Pricing Information

$3.01 per hour
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Verda

Company Location

Finland

Company Website

verda.com

Company Facts

Organization Name

NVIDIA

Date Founded

1993

Company Location

United States

Company Website

www.nvidia.com/en-us/data-center/virtual-solutions/

Categories and Features

Server Virtualization

Audit Management
Health Monitoring
Live Machine Migration
Multi-OS Virtual Machines
Patching / Backup
Performance Log
Performance Optimization
Rapid Provisioning
Security Management
Type 1 / Type 2 Hypervisor

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