Cloud · head to head
Cerebrium vs Terraform

Cerebrium
Cloud
Serverless GPU infrastructure for real-time AI inference and applications
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Cerebrium free Hobby tier limited to 3 apps and 5 GPU concurrency; Terraform hCL syntax requires learning a domain-specific language with limited GUI alternatives
- They diverge on capability: Cerebrium covers Ultra-fast cold starts, Terraform covers Infrastructure as code.
Where they differ
Only the attributes on which Cerebrium and Terraform actually diverge.
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated).
What each one covers
Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.
Only in Cerebrium
- Ultra-fast cold starts
- Elastic scaling
- Bring your own code
- Multi-region failover
- WebSocket and streaming
- Asynchronous jobs
- CI/CD with gradual rollouts
- OpenTelemetry integration
Only in Terraform
- Infrastructure as code
- Resource graph
- Plan & apply
- State management
- Provider ecosystem
- Modules
- Workspaces
- Remote backends
What people use each for
The jobs each tool is most often brought in to do.
Cerebrium
- Deploying voice agents and conversational AI applicationsnot Terraform
- Video and image model serving with low latencynot Terraform
- LLM inference and completion endpointsnot Terraform
- Real-time embeddings and vector database operationsnot Terraform
- Distributed model training with hyperparameter sweepsnot Terraform
Terraform
- Multi-cloud provisioningnot Cerebrium
- Infrastructure automationnot Cerebrium
- Environment replicationnot Cerebrium
- Disaster recoverynot Cerebrium
- Compliance automationnot Cerebrium
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Cerebrium
- Free Hobby tier limited to 3 apps and 5 GPU concurrency
- Standard plan at $100/month required for production deployments
- Per-second compute pricing requires continuous cost monitoring
- Storage costs add up for large model files
Terraform
- HCL syntax requires learning a domain-specific language with limited GUI alternatives
- State file management is complex, especially at scale with multiple workspaces
- terraform import workflow is fiddly and must be done one resource at a time
- No native error handling or try-catch capabilities like traditional programming languages
- No automatic rollback capability - must manually delete and re-run if needed
Pricing, plan by plan
Cerebrium
Free- HobbyFree
- 3 user seats
- Up to 3 deployed apps
- 5 GPU concurrency
- Standard$100/month
- Unlimited seats and apps
- 30 GPU concurrency
- Custom domains
- Enterprise$undefined/custom
- Unlimited resources
- Volume discounts
- Dedicated support
- GPU Compute$undefined/per-second
- T4: $0.000164/s
- H100: $0.00167/s
Terraform
FreeNo published plan breakdown. See the Terraform review.
Which should you pick?
Choose Cerebrium if
- You need ultra-fast cold starts.
- You want to start without paying.
- You work on Cloud, Docker.
- You also want elastic scaling.
Choose Terraform if
- You need infrastructure as code.
- You want to start without paying.
- You work on Linux, macOS, Windows.
- You also want resource graph.
Questions people ask
- Is Cerebrium or Terraform better?
- Neither clearly leads. Cerebrium starts at Free and Terraform at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Cerebrium or Terraform?
- Cerebrium starts at Free and Terraform at Free.
- Does Cerebrium or Terraform run on more platforms?
- Cerebrium runs on Cloud, Docker. Terraform runs on Linux, macOS, Windows.
- Can I use Cerebrium for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Cerebrium best used for?
- Cerebrium is most often used for deploying voice agents and conversational ai applications, video and image model serving with low latency, llm inference and completion endpoints, real-time embeddings and vector database operations. Of those, deploying voice agents and conversational ai applications and video and image model serving with low latency are not what Terraform is typically brought in for.
- What can Cerebrium do that Terraform cannot?
- Cerebrium covers Ultra-fast cold starts, Elastic scaling, Bring your own code, Multi-region failover. Terraform covers Infrastructure as code, Resource graph, Plan & apply, State management.
Answered from the vendors’ own pages
Cerebrium: Is Cerebrium only for inference or can it train models?
Cerebrium supports both inference serving and model training with hyperparameter sweeps. It enables deployment of voice agents, LLMs, video models, and other AI applications.
SourceTerraform: Is there a free tier?
Yes. The free tier supports up to 500 managed resources and 1 concurrent run. The legacy free tier ends March 31, 2026; remaining organizations auto-convert to the enhanced free tier.
SourceCerebrium: How do the cold starts compare to other platforms?
Cerebrium achieves 2-4 second cold starts through memory and GPU snapshotting, significantly faster than traditional 30+ second cold boots. This is competitive with platforms like Beam Cloud.
SourceTerraform: What clouds does Terraform support?
Terraform supports AWS, Microsoft Azure, Google Cloud Platform, Oracle Cloud, Docker, and HashiCorp's own HCP Terraform managed service, with over 2000 providers available.
SourceCerebrium: What compliance certifications does Cerebrium have?
Cerebrium maintains SOC 2 Type II compliance, HIPAA certification, GDPR compliance, and ISO certification. It provides gVisor container isolation and configurable data residency for regulated workloads.
SourceTerraform: Do I need HCP Terraform Cloud or can I run locally?
Terraform runs locally by default, storing state on your machine. For team collaboration and production use, remote backends like S3, Azure Storage, or HCP Terraform are recommended for locking and security.
SourceTerraform: Is HCL hard to learn?
HCL is designed to be human-readable and sits between JSON and YAML. It supports comments, variables, functions, and conditional logic. While beginners can get started quickly, mastering advanced features takes practice.
SourceRelated pages
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- Terraform vs Anyscale
- Terraform vs Fireworks AI
- Terraform vs Podman
- Terraform vs Railway
- Terraform vs Render
- Terraform vs Vault
- Terraform vs Wiz
- Terraform vs Beam Cloud
- Terraform vs DeepInfra
- Terraform vs Go
- Terraform vs Azure Functions
- Terraform vs Caddy
- Terraform vs Asana
- Terraform vs ClickUp
- Terraform vs Linear
- Terraform vs Figma
- Terraform vs Kubernetes
- Terraform vs Notion
- Terraform vs Datadog
- Terraform vs Monday.com
- Terraform vs Docker
- Terraform vs Greenhouse
- Terraform vs Google Chrome
- Terraform vs Intercom
- Terraform vs Mozilla Firefox
- Terraform vs Okta
- Terraform vs PostHog
- Terraform vs Redis
- Terraform vs Supabase
- Terraform vs Amplitude

