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Cloud · head to head

Anyscale vs Ona (formerly Gitpod)

Anyscale logo

Anyscale

Cloud

Platform for scaling AI and data workloads on Ray, built by Ray's creators

From
Free
Free plan
Yes
Full reviewWebsite
Ona (formerly Gitpod) logo

Ona (formerly Gitpod)

Developer Tools

Cloud development environments repositioned as a control plane for software engineering agents

From
Free
Free plan
Yes
Full reviewWebsite

The short version

  • Each has a real cost: Anyscale pricing for high-end H100/B200-class GPUs is not published and requires contacting sales.; Ona (formerly Gitpod) acquisition risk has already materialised: the company closed a sale to OpenAI on 10 August 2026 and now sits inside the Codex team, so nothing public guarantees pricing, continuity or neutrality between model vendors beyond honouring existing commitments.
  • They diverge on capability: Anyscale covers Distributed model training, Ona (formerly Gitpod) covers Ephemeral environments.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Anyscale and Ona (formerly Gitpod) actually diverge.

Attributes where Anyscale and Ona (formerly Gitpod) differ
AttributeAnyscaleOna (formerly Gitpod)
Pricing modelusage-basedPer month by compute unit
Platformsweb, apiWeb, Linux, macOS, Windows, AWS, Google Cloud Platform
CategoryCloudDeveloper Tools

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 Anyscale

  • Distributed model training
  • Multimodal data curation
  • Batch embedding generation
  • Multi-cloud orchestration
  • Governance and security
  • Observability
  • Bring-your-own-cloud deployment
  • Elastic GPU allocation

Only in Ona (formerly Gitpod)

  • Ephemeral environments
  • Agent sessions
  • Bring your own cloud
  • Devcontainer standard
  • Compute unit budgeting
  • Enterprise identity

What people use each for

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

Anyscale

  • Training large models on distributed GPU clustersnot Ona (formerly Gitpod)
  • Running batch inference and embedding jobsnot Ona (formerly Gitpod)
  • Preparing multimodal datasets at scalenot Ona (formerly Gitpod)
  • Post-training LLMs with reinforcement learning frameworksnot Ona (formerly Gitpod)

Ona (formerly Gitpod)

  • Giving a large engineering team identical, disposable environments so onboarding is a link rather than a two day setupnot Anyscale
  • Running several coding agents in parallel against real databases and services instead of on a laptopnot Anyscale
  • Keeping source code off contractor and offshore laptops by moving the whole environment into a controlled accountnot Anyscale
  • Reproducing a hard-to-configure toolchain for a short-lived project without polluting anyone machinenot Anyscale

Where each one falls short

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

Anyscale

  • Pricing for high-end H100/B200-class GPUs is not published and requires contacting sales.
  • Built around Ray, so teams not already using Ray face a steeper adoption curve than single-purpose inference APIs.
  • No published fixed-fee subscription tier; all listed pricing is usage-based on-demand compute.

Ona (formerly Gitpod)

  • Acquisition risk has already materialised: the company closed a sale to OpenAI on 10 August 2026 and now sits inside the Codex team, so nothing public guarantees pricing, continuity or neutrality between model vendors beyond honouring existing commitments.
  • Two disruptive changes of direction inside a year, from development environments to agent orchestration and then from independence to acquisition, mean the product a browser IDE buyer originally chose no longer exists in that form.
  • The Gitpod Classic sunset on 15 October 2025 required manual conversion of configuration, hand-moved secrets, self-rescued workspace data and a brand new account, which is the clearest available precedent for how the vendor handles deprecation.
  • Community self-hosting is finished: the AGPL-3.0 repository is deprecated by its own README, and self-hosted now means a vendor-operated install in your AWS or GCP account, with no Azure, no on-premises and no air-gapped path.
  • Pricing is difficult to model because it runs on a compute unit currency where subscription credits expire at the end of the month, the mapping from units to actual compute is not published on the pricing page, and Enterprise is quotation only.

Pricing, plan by plan

Anyscale

Free
  • Pay-as-you-go$undefined/mo
    • CPU only from $0.0135/hr
    • NVIDIA T4 $0.5682/hr
    • NVIDIA L4 $0.9542/hr
  • Committed contract$undefined/mo
    • Volume discounts
    • Use of existing GPU reservations

Ona (formerly Gitpod)

Free
  • FreeFree
    • Up to 3 parallel environments
    • Machines up to 4 vCPU, 16 GB memory and 80 GB disk
    • Ona Cloud multi-tenant only
  • Core$20/month
    • From 20 US dollars a month, up to 100 team members
    • Includes 80 to 2,200 recurring compute units a month depending on tier
    • Additional units from 10 US dollars per 40 units
  • Enterprise$undefined/year
    • Single-tenant deployment in your own AWS or GCP account
    • SAML and OIDC single sign-on
    • Dedicated account management and forward deployed engineers

Which should you pick?

Choose Anyscale if

  • You need distributed model training.
  • You want to start without paying.
  • You work on web, api.
  • You also want multimodal data curation.
Anyscale review

Choose Ona (formerly Gitpod) if

  • You need ephemeral environments.
  • You want to start without paying.
  • You work on Web, Linux, macOS, Windows, AWS, Google Cloud Platform.
  • You also want agent sessions.
Ona (formerly Gitpod) review

Questions people ask

Is Anyscale or Ona (formerly Gitpod) better?
Neither clearly leads. Anyscale starts at Free and Ona (formerly Gitpod) at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Anyscale or Ona (formerly Gitpod)?
Anyscale starts at Free and Ona (formerly Gitpod) at Free.
Does Anyscale or Ona (formerly Gitpod) run on more platforms?
Anyscale runs on web, api. Ona (formerly Gitpod) runs on Web, Linux, macOS, Windows, AWS, Google Cloud Platform.
Can I use Anyscale for free?
Both have a free tier, so you can try either at no cost before committing.
What is Anyscale best used for?
Anyscale is most often used for training large models on distributed gpu clusters, running batch inference and embedding jobs, preparing multimodal datasets at scale, post-training llms with reinforcement learning frameworks. Of those, training large models on distributed gpu clusters and running batch inference and embedding jobs are not what Ona (formerly Gitpod) is typically brought in for.
What can Anyscale do that Ona (formerly Gitpod) cannot?
Anyscale covers Distributed model training, Multimodal data curation, Batch embedding generation, Multi-cloud orchestration. Ona (formerly Gitpod) covers Ephemeral environments, Agent sessions, Bring your own cloud, Devcontainer standard.

Answered from the vendors’ own pages

Anyscale: How much does Anyscale cost?

Anyscale bills on a pay-as-you-go basis: CPU compute starts at $0.0135/hr, NVIDIA T4 at $0.5682/hr, and NVIDIA A100 at $4.9591/hr, with committed contracts offering volume discounts for larger workloads.

Source
Ona (formerly Gitpod): Is Gitpod still called Gitpod?

No. It rebranded to Ona in September 2025, and gitpod.io now redirects to ona.com. The company was acquired by OpenAI in a deal that closed on 10 August 2026.

Anyscale: Is there a free trial or credit?

New users receive $100 in Anyscale credits to explore the platform, which can be applied toward starter templates and on-demand compute usage.

Source
Ona (formerly Gitpod): Can I still self-host it for free?

No. The AGPL-3.0 self-hosted project is deprecated by its own README. What is offered now is a vendor-operated single-tenant install in your AWS or GCP account on the Enterprise plan.

Anyscale: How is usage billed?

Hosted usage is billed hourly per compute instance type and invoiced monthly by credit card; bring-your-own-cloud usage is invoiced through Anyscale or the customer's cloud marketplace account.

Source
Ona (formerly Gitpod): What happened to Gitpod Classic?

Pay-as-you-go Classic was switched off on 15 October 2025. Migration required converting gitpod.yml to devcontainer.json, moving secrets by hand, downloading workspace data before the cutoff and creating a new account.

Anyscale: What support is included?

Hosted plans include business-hours support with up to 5 case submissions, while bring-your-own-cloud deployments get 24x7 enterprise SLAs and unlimited case submissions.

Source
Ona (formerly Gitpod): What does it cost?

Core starts at 20 US dollars a month and includes a monthly allowance of Ona Compute Units, with more from 10 dollars per 40 units. Subscription credits expire monthly. Enterprise is quoted.

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