Choose Your Plan

Start-Up to Enterprise

Launch in minutes. Scale to thousands of nodes.

Vantage Starter

Single cluster, standard support, 50,000 VCUs/month included.

$3,000per
month
Most popular

Vantage Professional

Multi-cluster, enhanced SLA, 200,000 VCUs/month included.

$12,000per
month

Vantage Enterprise

Unlimited clusters, premium support, 1M+ VCUs/month. Sales-led / private offers.

Contact us
Explore

Vantage Features

Deploy faster. Scale further. Spend smarter.

Starter
$3,000/mo
Professional
$12,000/mo
Enterprise
Custom/mo
Networking and Performance
Topology-aware Slurm networking
Infiniband and RDMA
NCCL performance validation and monitoring
Distributed training network visibility
Enterprise-grade networking
Service mesh and traffic management
Network policy enforcement and topology-aware traffic control
Global Availability and Scale
Support for leading AI and ML frameworks
JupyterHub notebooks available across tiers
Kubeflow, Ray, and Spark integrations
Enterprise-grade deployment patterns for AI and ML workloads
Secure, multi-environment AI workload isolation
Cost Transparency
Transparent infrastructure costs by provider
Flexible commitment options
Latest GPU types by provider
Performance tuning and optimized libraries
Security and Compliance
SOC 1 aligned security controls
Regular third-party penetration testing
Secure, identity-based container execution
Automated GPU security patching and CVE rollback
SOC 2 and ISO 27001 readiness
Kerberos-based authentication
Enterprise security review and compliance support
Storage and Data
Provider-native shared filesystem integration
Dynamic storage provisioning via Kubernetes PVCs
S3-compatible object storage integration
Reliable, non-flapping Kubernetes-native mounts
Secure access tied to user identity
Enterprise storage systems and high-performance tiers
Third-party storage integrations (VAST, WEKA, DDN)
Advanced storage placement and optimization
Gluster Support
AI and ML
Support for leading AI and ML frameworks
JupyterHub notebooks available across tiers
Slurm-powered AI workloads on Kubernetes
Integrated tracking and auditing of AI workloads
Kubeflow, Ray, and Spark integrations
Enterprise-grade deployment patterns for AI and ML workloads
Secure, multi-environment AI workload isolation
GPU and Compute Infrastructure
Automated GPU and network operator management
GPU sharing and MIG support
GPU topology-aware placement optimization
GPU utilization and health monitoring
Identity, Access, and Admin Controls
RBAC and SSO with external identity providers
Passwordless, identity-based access across nodes
Delegated administration controls
Advanced audit logging and access policies
Orchestration and Workloads
Fully managed Slurm clusters
Fully managed Kubernetes clusters
Secure managed services with encrypted data at rest
Lightweight health checks and self-healing nodes
Slurm job accounting and per-user resource tracking
Slurm integration with AI and platform services
Enterprise Kubernetes authentication patterns
Advanced cluster access policies
Reliability, Monitoring, and Observability
Continuous node and workload health checks
Automatic remediation and node replacement
Managed Grafana and Prometheus observability
Job, GPU, and infrastructure metrics
Alerting and diagnostics
Advanced hardware telemetry and profiling
Provisioning and Cluster Lifecycle
Point-and-click cluster provisioning
Fully automated setup with no Terraform required
Automatic Slurm head node and worker provisioning
Cloud-specific GPU and Infiniband driver automation
GPU Direct RDMA enabled out of the box
No onboarding fees
Tiered offboarding and data egress policies
Custom deployment and configuration options
Negotiated data egress and offboarding terms