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Cloud · head to head

Beam Cloud vs Cortex

Beam Cloud logo

Beam Cloud

Cloud

Serverless GPU computing with sub-second cold starts and multi-cloud support

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 Beam Cloud has a free tier, so it costs nothing to try first.
  • Each has a real cost: Beam Cloud free tier limited to $30 monthly credits with 5 GPU containers; 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: Beam Cloud covers Sub-second 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 Beam Cloud and Cortex actually diverge.

Attributes where Beam Cloud and Cortex differ
AttributeBeam CloudCortex
Starting priceFreeOn request
Pricing modelFreemium with pay-per-millisecond usage chargesquote
Free tierYesNo
PlatformsCloud, PythonWeb, 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 Beam Cloud

  • Sub-second cold starts
  • Inference endpoints
  • Task queues
  • Sandboxes
  • Multi-cloud support
  • Python SDK
  • Global distribution
  • Massive parallelization

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.

Beam Cloud

  • Deploying ML models with minimal latency and setup timenot Cortex
  • Large-scale batch processing across thousands of concurrent tasksnot Cortex
  • Cost-effective inference serving with bursty workloadsnot Cortex
  • Multi-cloud AI deployments with global low-latency accessnot Cortex
  • Serverless AI development for rapid experimentationnot 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 Beam Cloud
  • An organisation where ownership of production services is genuinely unknown after reorganisations or acquisitionsnot Beam Cloud
  • Enforcing production readiness standards on new services at creation time rather than at incident reviewnot Beam Cloud
  • Replacing a self-hosted Backstage that is consuming a full-time engineer or two just to stay upgradednot Beam Cloud

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Beam Cloud

  • Free tier limited to $30 monthly credits with 5 GPU containers
  • Massive parallelization complexity may require DevOps expertise
  • Per-millisecond pricing model requires careful cost monitoring
  • Smaller team relative to established cloud providers

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

Beam Cloud

Free
  • DeveloperFree
    • $30 monthly free credits
    • 5 GPU containers, 30 CPU containers
    • Community support
  • Team$89/month
    • $30 monthly free credits included
    • 50 GPU containers, 1,000 CPU containers
    • 3 seats included, $25 per additional
  • Growth$undefined/custom
    • 1,000+ GPU containers
    • Unlimited CPU containers
    • Unlimited seats
  • Serverless GPUs$undefined/per-millisecond
    • RTX 4090: $0.00019/sec

Cortex

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

Which should you pick?

Choose Beam Cloud if

  • You need sub-second cold starts.
  • You want to start without paying.
  • You work on Cloud, Python.
  • You also want inference endpoints.
Beam Cloud review

Choose Cortex if

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

Questions people ask

Is Beam Cloud or Cortex better?
Neither clearly leads. Beam Cloud 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, Beam Cloud or Cortex?
Beam Cloud has a free tier; the other does not. Paid plans start at Free for Beam Cloud and On request for Cortex.
Does Beam Cloud or Cortex run on more platforms?
Beam Cloud runs on Cloud, Python. Cortex runs on Web, API.
Can I use Beam Cloud for free?
Yes. Beam Cloud has a free tier, so you can try it without paying. Cortex starts at On request.
What is Beam Cloud best used for?
Beam Cloud is most often used for deploying ml models with minimal latency and setup time, large-scale batch processing across thousands of concurrent tasks, cost-effective inference serving with bursty workloads, multi-cloud ai deployments with global low-latency access. Of those, deploying ml models with minimal latency and setup time and large-scale batch processing across thousands of concurrent tasks are not what Cortex is typically brought in for.
What can Beam Cloud do that Cortex cannot?
Beam Cloud covers Sub-second cold starts, Inference endpoints, Task queues, Sandboxes. Cortex covers Service catalogue, Scorecards, Initiatives, Self-service templates.

Answered from the vendors’ own pages

Beam Cloud: What is included in the Developer plan?

The Developer plan includes $30 monthly free credits, 5 GPU containers, 30 CPU containers, and community support. No upfront commitment is required.

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.

Beam Cloud: How fast are the cold starts?

Beam Cloud achieves sub-second cold starts through memory snapshots that restore GPU containers 35x faster than traditional cold boots.

Source
Cortex: Is pricing published?

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

Beam Cloud: Can I deploy across multiple cloud providers?

Yes, Beam Cloud supports multi-cloud deployment across AWS, GCP, Azure, Hetzner, and other providers with 30+ global regions available.

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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