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Developer Tools · head to head

Cortex vs DeepInfra

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
DeepInfra logo

DeepInfra

Cloud

Low-cost cloud API for running open-source AI models

From
$0.08/month
Free plan
No
Full reviewWebsite

The short version

  • Each has a real cost: 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.; DeepInfra focuses on inference hosting rather than fine-tuning or full training pipelines that competitors like Fireworks AI offer.
  • They diverge on capability: Cortex covers Service catalogue, DeepInfra covers Open model hosting.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Cortex and DeepInfra actually diverge.

Attributes where Cortex and DeepInfra differ
AttributeCortexDeepInfra
Starting priceOn request$0.08/month
Pricing modelquoteusage-based
CategoryDeveloper ToolsCloud

Identical on both: free tier (No), platforms (Web, API), 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 Cortex

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

Only in DeepInfra

  • Open model hosting
  • Pay-per-token pricing
  • Long context support
  • DeepCluster
  • Zero retention policy
  • Real-time metrics

What people use each for

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

Cortex

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

DeepInfra

  • Running open-source LLM inference without managing GPUsnot Cortex
  • Serving speech and image generation models via APInot Cortex
  • Cost-sensitive production inference at scalenot Cortex
  • Reserved GPU capacity via DeepCluster for steady workloadsnot Cortex

Where each one falls short

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

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.

DeepInfra

  • Focuses on inference hosting rather than fine-tuning or full training pipelines that competitors like Fireworks AI offer.
  • Model selection is limited to what DeepInfra chooses to host, unlike self-managed platforms.
  • No published free tier; usage is billed from the first token.

Pricing, plan by plan

Cortex

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

DeepInfra

$0.08/month
  • Pay-as-you-go$undefined/mo
    • Per-model token pricing from $0.08 to $2.85 per million input tokens
    • No long-term contract
  • DeepCluster$1.98/month
    • Dedicated NVIDIA B300 GPU clusters at $1.98/GPU-hour

Which should you pick?

Choose Cortex if

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

Choose DeepInfra if

  • You need open model hosting.
  • You work on web, api.
  • You also want pay-per-token pricing.
DeepInfra review

Questions people ask

Is Cortex or DeepInfra better?
Neither clearly leads. Cortex starts at On request and DeepInfra at $0.08/month, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Cortex or DeepInfra?
Cortex starts at On request and DeepInfra at $0.08/month.
Does Cortex or DeepInfra run on more platforms?
Cortex runs on Web, API. DeepInfra runs on web, api.
What is Cortex best used for?
Cortex is most often used for a platform team that needs to prove to leadership how far a kubernetes or framework migration has actually progressed across hundreds of services, an organisation where ownership of production services is genuinely unknown after reorganisations or acquisitions, enforcing production readiness standards on new services at creation time rather than at incident review, replacing a self-hosted backstage that is consuming a full-time engineer or two just to stay upgraded. Of those, a platform team that needs to prove to leadership how far a kubernetes or framework migration has actually progressed across hundreds of services and an organisation where ownership of production services is genuinely unknown after reorganisations or acquisitions are not what DeepInfra is typically brought in for.
What can Cortex do that DeepInfra cannot?
Cortex covers Service catalogue, Scorecards, Initiatives, Self-service templates. DeepInfra covers Open model hosting, Pay-per-token pricing, Long context support, DeepCluster.

Answered from the vendors’ own pages

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.

DeepInfra: Is there a free tier on DeepInfra?

No free tier is published; usage is billed pay-as-you-go from the first token, though a credit card or pre-payment is required before you can send requests.

Source
Cortex: Is pricing published?

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

DeepInfra: How is usage priced?

Language models are billed per million input/output tokens, other models by inference execution time, and audio models per minute of audio processed, with no minimum commitment.

Source
Cortex: Can it self-host?

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

DeepInfra: What are the Standard, Priority, and Flex tiers?

Standard is default best-effort pricing at 1x, Priority costs 1.5x for faster time-to-first-token during peak demand, and Flex costs 0.8x for non-production or asynchronous workloads.

Source
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.

DeepInfra: How does billing scale with spend?

Accounts advance through usage tiers as cumulative payments cross $20, $100, $500, $2,000, and $10,000 thresholds, with invoices generated monthly or at each threshold.

Source
DeepInfra: Is there a limit on concurrent requests?

Yes, accounts are limited to 200 concurrent requests by default, though spending limits can also be configured to prevent unexpected charges.

Source
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