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Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.

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Runpod logo
Runpod
✓ verifiedPaid

Developer-focused GPU cloud offering on-demand pods, serverless inference and multi-node clusters at per-second pricing for AI workloads.

2.3M visits/mo
Vanta logo
Vanta
✓ verifiedPaid

Compliance automation platform that continuously monitors controls and evidence to help companies achieve SOC 2, ISO 27001, and HIPAA.

775K visits/mo
Vectra logo
Vectra
✓ verifiedPaid

AI-driven network detection and response platform that identifies and stops identity-based and lateral-movement cyberattacks in real time.

203K visits/mo1.0K saves
Pricing
Pods A40 48GB: $0.44/hr
Pods RTX 4090 24GB: $0.69/hr
Pods A100 SXM 80GB: $1.49/hr
Pods H100 SXM 80GB: $2.99/hr
Pods H200 141GB: $4.39/hr
Pods B300 288GB: $7.39/hr

No public pricing

No public pricing

Core features
  • On-demand GPU pods across 30+ GPU types and 31 regions
  • Serverless GPU endpoints with sub-200ms cold starts
  • Zero idle cost billing for inference workloads
  • Multi-node clusters for distributed training
  • Persistent network storage for full pipelines
  • Real-time logs, monitoring and autoscaling from 0 to hundreds of workers
  • Continuous automated compliance monitoring across frameworks
  • Automated evidence collection and audit preparation
  • Personnel access and permissions management
  • Vendor and third-party risk assessment workflows
  • Automated security questionnaire responses
  • Public-facing trust center for compliance status
  • 400+ tool integrations and an API for custom workflows
  • Real-time AI-driven threat detection beyond traditional EDR
  • Detection of identity-based attacks and lateral movement
  • 360 Response for enforced containment across identity, devices, and network
  • Exposure management and security posture improvement tools
  • Managed detection and response (MXDR/MDR) services
  • Integrations across existing security tool ecosystems
  • Attack Labs research sharing threat intelligence and techniques
Use cases
  • Renting GPUs for model training and fine-tuning
  • Deploying low-latency real-time inference APIs
  • Running AI agents that need to scale instantly
  • Processing compute-heavy batch or distributed workloads
  • Preparing for and maintaining SOC 2 or ISO 27001 certification
  • Automating responses to customer security questionnaires
  • Managing vendor security reviews at scale
  • Centralizing risk management across a growing company
  • Security operations teams needing detection beyond EDR/SIEM gaps
  • Enterprises defending against identity-based and hybrid cloud attacks
  • Organizations needing managed threat detection and response services
  • Finance, healthcare, and public sector teams meeting compliance-driven security needs
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