Cloud · head to head
Cerebrium vs LangGraph

Cerebrium
Cloud
Serverless GPU infrastructure for real-time AI inference and applications
- From
- Free
- Free plan
- Yes
The short version
- Each has a real cost: Cerebrium free Hobby tier limited to 3 apps and 5 GPU concurrency; LangGraph steeper learning curve compared to high-level abstractions
- They diverge on capability: Cerebrium covers Ultra-fast cold starts, LangGraph covers Human-in-the-loop controls.
- Prices and features above were last checked on 29 August 2026.
Where they differ
Only the attributes on which Cerebrium and LangGraph 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 LangGraph
- Human-in-the-loop controls
- Customizable workflows
- Memory management
- Token-by-token streaming
- Low-level control
- Multi-agent support
What people use each for
The jobs each tool is most often brought in to do.
Cerebrium
- Deploying voice agents and conversational AI applicationsnot LangGraph
- Video and image model serving with low latencynot LangGraph
- LLM inference and completion endpointsnot LangGraph
- Real-time embeddings and vector database operationsnot LangGraph
- Distributed model training with hyperparameter sweepsnot LangGraph
LangGraph
- Building production AI agents with auditable workflowsnot Cerebrium
- Designing multi-agent systems for complex tasksnot Cerebrium
- Implementing human oversight in autonomous systemsnot Cerebrium
- Creating reliable agentic applications at scalenot 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
LangGraph
- Steeper learning curve compared to high-level abstractions
- Requires understanding of graph-based architecture
- Debugging complex workflows can be challenging
- Not optimized for simple, one-off use cases
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
LangGraph
Free- Open SourceFree
- MIT-licensed framework
- Self-hosted deployment
- Full API access
- LangGraph Platform$35/month
- Managed hosting
- Enterprise deployment
- Integrated tooling
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 LangGraph if
- You need human-in-the-loop controls.
- You want to start without paying.
- You work on Python, JavaScript, Web.
- You also want customizable workflows.
Questions people ask
- Is Cerebrium or LangGraph better?
- Neither clearly leads. Cerebrium starts at Free and LangGraph at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Cerebrium or LangGraph?
- Cerebrium starts at Free and LangGraph at Free.
- Does Cerebrium or LangGraph run on more platforms?
- Cerebrium runs on Cloud, Docker. LangGraph runs on Python, JavaScript, Web.
- 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 LangGraph is typically brought in for.
- What can Cerebrium do that LangGraph cannot?
- Cerebrium covers Ultra-fast cold starts, Elastic scaling, Bring your own code, Multi-region failover. LangGraph covers Human-in-the-loop controls, Customizable workflows, Memory management, Token-by-token streaming.
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.
SourceLangGraph: Is LangGraph free to use?
Yes. The core LangGraph framework is MIT-licensed and completely free. You only pay if you use the optional managed LangGraph Platform for hosting.
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.
SourceLangGraph: What programming languages does LangGraph support?
LangGraph provides first-class support for Python and JavaScript, enabling cross-platform agent development.
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.
SourceLangGraph: Can I deploy LangGraph in production?
Yes. LangGraph can be self-hosted on your own infrastructure or deployed through LangGraph Platform with enterprise support and SLA guarantees.
SourceRelated pages
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