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Cloud · head to head

Cerebrium vs Cortex

Cerebrium logo

Cerebrium

Cloud

Serverless GPU infrastructure for real-time AI inference and applications

From
Free
Free plan
Yes
Full reviewWebsite
Cortex logo

Cortex

Developer Tools

Internal developer portal that scores service ownership and maturity rather than just cataloguing services

From
On request
Free plan
No
Full reviewWebsite

The short version

  • Only Cerebrium has a free tier, so it costs nothing to try first.
  • Each has a real cost: Cerebrium free Hobby tier limited to 3 apps and 5 GPU concurrency; Cortex pricing is quote only, so a platform team cannot build a business case or compare against the true cost of self-hosted Backstage without entering a sales cycle first.
  • They diverge on capability: Cerebrium covers Ultra-fast cold starts, Cortex covers Service catalogue.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Cerebrium and Cortex actually diverge.

Attributes where Cerebrium and Cortex differ
AttributeCerebriumCortex
Starting priceFreeOn request
Pricing modelFreemium with monthly plans and per-second compute chargesquote
Free tierYesNo
PlatformsCloud, DockerWeb, API
CategoryCloudDeveloper Tools

Identical on both: 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 Cortex

  • Service catalogue
  • Scorecards
  • Initiatives
  • Self-service templates
  • Query language
  • Eng intelligence
  • Integrations layer
  • On-call and ownership mapping

What people use each for

The jobs each tool is most often brought in to do.

Cerebrium

  • Deploying voice agents and conversational AI applicationsnot Cortex
  • Video and image model serving with low latencynot Cortex
  • LLM inference and completion endpointsnot Cortex
  • Real-time embeddings and vector database operationsnot Cortex
  • Distributed model training with hyperparameter sweepsnot Cortex

Cortex

  • A platform team that needs to prove to leadership how far a Kubernetes or framework migration has actually progressed across hundreds of servicesnot Cerebrium
  • An organisation where ownership of production services is genuinely unknown after reorganisations or acquisitionsnot Cerebrium
  • Enforcing production readiness standards on new services at creation time rather than at incident reviewnot Cerebrium
  • Replacing a self-hosted Backstage that is consuming a full-time engineer or two just to stay upgradednot 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

Cortex

  • Pricing is quote only, so a platform team cannot build a business case or compare against the true cost of self-hosted Backstage without entering a sales cycle first.
  • The catalogue is only as accurate as the metadata you supply, so an organisation with inconsistent repository conventions spends its first quarter cleaning data before any scorecard means anything.
  • Scorecards create political friction: publishing a per-team grade turns an engineering standard into a performance metric, and teams will game the rules rather than fix the underlying issue.
  • It is closed source and hosted, so organisations with strict data residency or air-gap requirements have limited options compared with running Backstage themselves.
  • Value scales with organisation size, so a company with fifty engineers and thirty services will find the catalogue tells them nothing they did not already know while still paying an enterprise contract.

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

Cortex

On request
  • Cortex$undefined/year
    • Service catalogue and ownership mapping
    • Scorecards and initiatives
    • Self-service templates

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.
Cerebrium review

Choose Cortex if

  • You need service catalogue.
  • You work on Web, API.
  • You also want scorecards.
Cortex review

Questions people ask

Is Cerebrium or Cortex better?
Neither clearly leads. Cerebrium starts at Free and Cortex at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Cerebrium or Cortex?
Cerebrium has a free tier; the other does not. Paid plans start at Free for Cerebrium and On request for Cortex.
Does Cerebrium or Cortex run on more platforms?
Cerebrium runs on Cloud, Docker. Cortex runs on Web, API.
Can I use Cerebrium for free?
Yes. Cerebrium has a free tier, so you can try it without paying. Cortex starts at On request.
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 Cortex is typically brought in for.
What can Cerebrium do that Cortex cannot?
Cerebrium covers Ultra-fast cold starts, Elastic scaling, Bring your own code, Multi-region failover. Cortex covers Service catalogue, Scorecards, Initiatives, Self-service templates.

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.

Source
Cortex: How is Cortex different from Backstage?

Backstage is an open source framework you build and staff. Cortex is a hosted product with scorecards and initiatives out of the box and no platform team required to keep it running.

Cerebrium: 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.

Source
Cortex: Is pricing published?

No. Cortex requires a sales conversation and prepares a custom proposal.

Cerebrium: 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.

Source
Cortex: Can it self-host?

It is offered as a hosted product; on-premise arrangements are handled through sales rather than published.

Cortex: What is the main adoption risk?

Bad or missing service metadata. The catalogue and every scorecard on top of it inherit whatever quality your repositories already have.

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