NVIDIA DGX Cloud vs Spacelift

Detailed side-by-side comparison to help you choose the right tool

NVIDIA DGX Cloud

Cloud & Hosting

NVIDIA's cloud platform providing access to powerful GPU infrastructure for AI model training, inference, and high-performance computing workloads.

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Starting Price

Custom

Spacelift

Cloud & Hosting

Revolutionary Infrastructure-as-code orchestration platform that manages Terraform, OpenTofu, Pulumi, Ansible, and CloudFormation workflows with policy-as-code, drift detection, and concurrency-based pricing that won't surprise you.

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Starting Price

Enterprise

Feature Comparison

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FeatureNVIDIA DGX CloudSpacelift
CategoryCloud & HostingCloud & Hosting
Pricing Plans10 tiers8 tiers
Starting PriceEnterprise
Key Features
  • â€ĸ Dedicated NVIDIA H100 and A100 GPU instances
  • â€ĸ Multi-node training with NVLink and InfiniBand
  • â€ĸ NVIDIA AI Enterprise software suite included
  • â€ĸ Terraform, OpenTofu, Terragrunt, Pulumi, Ansible, Kubernetes, CloudFormation support
  • â€ĸ Open Policy Agent (OPA) policy-as-code
  • â€ĸ Drift detection with optional auto-remediation

NVIDIA DGX Cloud - Pros & Cons

Pros

  • ✓Provides turnkey access to 8x NVIDIA H100 80GB GPUs per node (640GB total GPU memory) without capital expenditure on hardware
  • ✓Includes white-glove support from NVIDIA AI experts who have trained foundation models at scale
  • ✓Bundles NVIDIA AI Enterprise software (NeMo, RAPIDS, Triton) valued at $4,500 per GPU per year at no additional charge
  • ✓Runs on identical NVIDIA reference architecture across Azure, OCI, Google Cloud, and AWS — avoiding cloud vendor lock-in
  • ✓Reserved capacity eliminates the 'GPU scarcity' problem that plagues on-demand instances at other hyperscalers
  • ✓Optimized high-speed InfiniBand interconnects enable efficient scaling to thousands of GPUs for trillion-parameter models

Cons

  • ✗Starting price of approximately $36,999 per instance per month makes it inaccessible to solo developers and small startups
  • ✗Requires multi-month commitments, not hourly or on-demand billing like Lambda Labs or Vast.ai
  • ✗Sales process is enterprise-driven and can take weeks to onboard, unlike self-service cloud GPU providers
  • ✗Limited geographic availability compared to mature hyperscaler regions
  • ✗Locked into NVIDIA's software ecosystem (CUDA, NeMo) — less friendly to AMD ROCm or custom silicon workflows

Spacelift - Pros & Cons

Pros

  • ✓Concurrency-based pricing is dramatically cheaper than Terraform Cloud's per-resource model — users report 3-5x cost reductions on real workloads
  • ✓Genuine multi-IaC support means you manage Terraform, Ansible, and Pulumi stacks in one platform instead of three separate tools
  • ✓OPA policy-as-code integration gives real teeth to infrastructure governance — not just advisory warnings, actual blocking policies
  • ✓Private workers run in your VPC with outbound-only connections, solving the 'state leaving our network' problem cleanly
  • ✓The free plan includes enough to evaluate with a real project — not just a 14-day trial that pressures you into buying
  • ✓Strong customer support with dedicated Slack channels and CSMs on Business/Enterprise plans — users consistently praise responsiveness

Cons

  • ✗Custom pricing with no published numbers makes it impossible to estimate costs without talking to sales first
  • ✗Overkill for small teams — if you have 2 developers and 50 resources, Atlantis or vanilla Terraform Cloud may be simpler
  • ✗The learning curve for OPA policies is real: Rego is a niche language that most teams need to learn from scratch
  • ✗Some users report rough edges with permission models, particularly around state locking and maintainer access
  • ✗No transparent pricing comparison possible — you have to get quotes from both Spacelift and competitors to compare
  • ✗Audit trail is Enterprise-only, which means compliance-focused mid-market teams get pushed to the most expensive tier

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🔒 Security & Compliance Comparison

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Security FeatureNVIDIA DGX CloudSpacelift
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