On-demand NVIDIA GPU instances
Provision single-instance GPU capacity in under a minute, with selectable configurations from 1x to 8x GPUs.
Verda
Freemium
Verda is a full-stack AI cloud for running AI workloads on GPU infrastructure. It provides on-demand NVIDIA GPU instances and self-service multi-node clusters with managed Slurm or Kubernetes.
What is Verda?
Verda is a full-stack AI cloud focused on infrastructure for AI workloads. It combines on-demand NVIDIA GPU instances with self-service, multi-node clusters and managed Slurm or Kubernetes options. Users can choose individual GPU capacity for short-lived or focused jobs, or provision a multi-node environment when an application requires distributed compute.
What can Verda do?
Multiple NVIDIA GPU options
The listed instance hardware includes NVIDIA B300, B200, H200, H100, and A100 GPUs, allowing users to select from the models exposed by the platform.
Self-service multi-node clusters
Create clusters without a manual setup process or a sales call, supporting workloads that need more than one node.
Managed Slurm or Kubernetes
Choose between managed Slurm and Kubernetes for cluster operation, depending on the workload or orchestration workflow.
Pay-as-you-go GPU usage
GPU instances are offered with pay-as-you-go pricing; the available evidence does not state the applicable rates.
Use Cases
“Multi-GPU inference”
Run inference workloads that need several GPUs, such as the multi-GPU inference described in Verda’s 1XWM generative video collaboration.
“Generative video workloads”
Supply GPU infrastructure for video-generation systems where higher video quality is part of the application workflow.
“Distributed AI jobs”
Use an instant multi-node cluster when an AI workload must run across multiple machines rather than a single GPU instance.
“Managed research or engineering environments”
Provision a cluster with Slurm or Kubernetes when a team needs an established scheduler or container-orchestration environment without setting up the cluster manually.
Frequently Asked Questions
How quickly can a GPU instance be provisioned?
The GPU instances page states that on-demand instances can be provisioned in under a minute.
How quickly can a multi-node cluster be provisioned?
Instant clusters are described as provisioning in 20 minutes.
Which cluster management options are available?
Verda offers managed Slurm or Kubernetes for its instant clusters.
What GPU models are listed?
The source lists NVIDIA B300, B200, H200, H100, and A100 options, among others.
Does Verda publish GPU pricing?
The source identifies pay-as-you-go pricing for GPU instances, but the available material does not include specific rates or plan limits.
Quick Facts
- Category
- AI cloud infrastructure
- Primary resources
- NVIDIA GPU instances and multi-node GPU clusters
- Instance range
- 1x–8x GPU configurations
- Cluster software
- Managed Slurm or Kubernetes
- Provisioning
- GPU instances in under a minute; instant clusters in 20 minutes
- Pricing model
- Pay as you go for GPU instances
Verda Alternatives
Salad
salad.com
Salad is a distributed GPU cloud for AI, offering usage-based pricing with no contracts or pre-payment for inference, transcription, image generation, and batch processing.
Hyperstack
www.hyperstack.cloud
Hyperstack is a cloud GPU platform for running AI and machine learning workloads, including training, inference, data analytics, and model development. It also provides AI Studio, virtual machines, and managed Kubernetes for deploying and operating GPU-backed workloads.
Radiant
radiant.co
Radiant is an integrated AI infrastructure platform that finances, builds, and operates data centers, GPU systems, networking, storage, and managed services. It helps AI teams and infrastructure operators provision and run compute through a unified platform and FlightDeck control plane.
Together AI
together.ai
Together AI is an AI cloud platform for inference, fine-tuning, GPU clusters, sandboxes, and managed storage.
Paperspace
www.paperspace.com
Paperspace is a cloud platform for developing, training, and deploying machine learning applications with managed notebooks, GPU machines, and deployment workflows. It serves ML developers, data scientists, researchers, and teams that need on-demand accelerated computing.
DeepInfra
deepinfra.com
DeepInfra provides hosted machine-learning model inference and on-demand GPU instances for developers and teams. Its catalog covers text, image, audio, video, embedding, reranking, and other model workloads with pay-as-you-go pricing.