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Developer Tools · head to head

Daytona vs Okteto

Daytona logo

Daytona

Developer Tools

Infrastructure for spinning up secure, sub-second sandboxes to run AI-generated code

From
Free
Rated
-
Full reviewWebsite
Okteto logo

Okteto

Developer Tools

Runs production-like development environments on your own Kubernetes cluster

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Daytona pricing is purely usage-based with no flat monthly plan, which can make costs harder to predict for steady workloads.; Okteto two of the three plans publish no price at all, with no currency and no billing period stated anywhere, so any budget above five seats requires a sales conversation before you can even compare it with an alternative.
  • They diverge on capability: Daytona covers Sub-second sandbox creation, Okteto covers Cluster development environments.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Daytona and Okteto actually diverge.

Attributes where Daytona and Okteto differ
AttributeDaytonaOkteto
Pricing modelusage-basedquote
Platformsweb, linux, windows, apiLinux, macOS, Windows, CLI, Kubernetes, Web

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Developer Tools).

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 Daytona

  • Sub-second sandbox creation
  • Per-second billing
  • GPU instances
  • Windows OS support
  • Enterprise BYOC

Only in Okteto

  • Cluster development environments
  • File synchronisation
  • Development containers
  • Environment catalogue
  • Preview environments
  • Bring your own cloud

What people use each for

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

Daytona

  • Running AI agent-generated code in a disposable, isolated sandboxnot Okteto
  • Executing untrusted user code for a coding platformnot Okteto
  • Running GPU workloads on demand without provisioning dedicated serversnot Okteto
  • Testing Windows-specific code paths in a sandboxnot Okteto

Okteto

  • A microservices estate where no developer can run the full dependency graph on a laptopnot Daytona
  • Giving each pull request a working environment reviewers can click rather than describenot Daytona
  • Letting coding agents build and test against real databases and queues instead of mocksnot Daytona
  • Removing a fleet of local Kubernetes installations that drift from production and produce false test resultsnot Daytona

Where each one falls short

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

Daytona

  • Pricing is purely usage-based with no flat monthly plan, which can make costs harder to predict for steady workloads.
  • GPU instances are priced separately and can be significantly more expensive than standard compute for AI-heavy use cases.
  • Enterprise features like SSO, audit logs, and BYOC are only available by contacting sales rather than self-serve.

Okteto

  • Two of the three plans publish no price at all, with no currency and no billing period stated anywhere, so any budget above five seats requires a sales conversation before you can even compare it with an alternative.
  • The Apache-2.0 CLI is restricted to the development section of the manifest, so build services, user management and observability all require the commercial platform and the open licence provides very little continuity insurance.
  • The last disclosed funding round is a 15 million US dollar Series A from February 2022 with nothing announced since, and the contributor base is dominated by company employees, which is concentrated risk for something embedded in every developer daily loop.
  • You must bring and pay for the Kubernetes cluster, so node cost, capacity planning and version upgrades stay with your platform team on top of the licence fee.
  • The 2026 repositioning towards AI agents means the classic developer inner loop is no longer what the marketing leads with, so a buyer purchasing that use case should confirm roadmap commitment rather than assume it.

Pricing, plan by plan

Daytona

Free
  • Pay-as-you-go$undefined/mo
    • $0.0504 per vCPU/hour
    • $0.0162 per GiB memory/hour
    • $0.000108 per GiB storage/hour after 5 free GiB
  • Startup Program$undefined/mo
    • Up to $50,000 in free credits for qualifying startups
  • Enterprise$undefined/mo
    • Custom usage limits
    • SSO
    • Audit logs

Okteto

Free
  • StarterFree
    • 5 seats included
    • Self-hosted deployment into your own cluster
    • Community support
  • Scale$undefined/year
    • Contact sales, no price, currency or billing period published
    • More seats and environments than Starter
    • Self-hosted deployment
  • Enterprise$undefined/year
    • Contact sales, no price published
    • Bring your own cloud deployment
    • Available through Google Cloud and AWS marketplaces

Which should you pick?

Choose Daytona if

  • You need sub-second sandbox creation.
  • You want to start without paying.
  • You work on web, linux, windows, api.
  • You also want per-second billing.
Daytona review

Choose Okteto if

  • You need cluster development environments.
  • You want to start without paying.
  • You work on Linux, macOS, Windows, CLI, Kubernetes, Web.
  • You also want file synchronisation.
Okteto review

Questions people ask

Is Daytona or Okteto better?
Neither clearly leads. Daytona starts at Free and Okteto at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Daytona or Okteto?
Daytona starts at Free and Okteto at Free.
Does Daytona or Okteto run on more platforms?
Daytona runs on web, linux, windows, api. Okteto runs on Linux, macOS, Windows, CLI, Kubernetes, Web.
Can I use Daytona for free?
Both have a free tier, so you can try either at no cost before committing.
What is Daytona best used for?
Daytona is most often used for running ai agent-generated code in a disposable, isolated sandbox, executing untrusted user code for a coding platform, running gpu workloads on demand without provisioning dedicated servers, testing windows-specific code paths in a sandbox. Of those, running ai agent-generated code in a disposable, isolated sandbox and executing untrusted user code for a coding platform are not what Okteto is typically brought in for.
What can Daytona do that Okteto cannot?
Daytona covers Sub-second sandbox creation, Per-second billing, GPU instances, Windows OS support. Okteto covers Cluster development environments, File synchronisation, Development containers, Environment catalogue.

Answered from the vendors’ own pages

Daytona: How is Daytona usage metered?

Usage is billed per second across vCPU, memory, and storage consumed, with separate per-hour rates for GPU and Windows instances.

Source
Okteto: Is Okteto open source?

The CLI is Apache-2.0, but the README states it supports only the development section of the manifest. Everything operationally interesting, including builds, user management and observability, is in the commercial platform.

Daytona: Is there a free plan, and what are its limits?

There is no flat free plan, but new signups receive $200 in free compute credit with no credit card required to start.

Source
Okteto: What does it cost?

Only the free Starter tier with five seats is published. Scale and Enterprise are both contact sales, with no price, currency or billing period disclosed on the pricing page.

Daytona: Are discounts available for startups?

Yes, the Startup Program offers up to $50,000 in free credits for qualifying companies.

Source
Okteto: Do I need my own Kubernetes cluster?

Yes. Okteto installs into a cluster you provide and pay for, so capacity, upgrades and node costs remain your responsibility in addition to the licence.

Okteto: How is this different from running Kubernetes locally?

Environments run against the same managed databases, queues and service mesh as production, so a class of failures that only appears in a real cluster is caught before merge rather than after deploy.

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