Cloud · head to head
Fireworks AI vs Ona (formerly Gitpod)

Fireworks AI
Cloud
Fast inference and fine-tuning platform for open and custom AI models
- From
- Free
- Free plan
- Yes

Ona (formerly Gitpod)
Developer Tools
Cloud development environments repositioned as a control plane for software engineering agents
- From
- Free
- Free plan
- Yes
The short version
- Each has a real cost: Fireworks AI reserved and enterprise-tier pricing is not published and requires sales contact.; 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: Fireworks AI covers Serverless inference, 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 Fireworks AI and Ona (formerly Gitpod) actually diverge.
| Attribute | Fireworks AI | Ona (formerly Gitpod) |
|---|---|---|
| Pricing model | usage-based | Per month by compute unit |
| Platforms | web, api | Web, Linux, macOS, Windows, AWS, Google Cloud Platform |
| Category | Cloud | Developer 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 Fireworks AI
- Serverless inference
- On-demand and reserved deployments
- Managed fine-tuning
- OpenAI/Anthropic API compatibility
- Nexus router
- Long context models
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.
Fireworks AI
- Deploying open-source LLMs behind an OpenAI-compatible APInot Ona (formerly Gitpod)
- Fine-tuning models with LoRA or full-parameter trainingnot Ona (formerly Gitpod)
- Routing AI coding assistant traffic to cheaper models via Nexusnot Ona (formerly Gitpod)
- Reserving dedicated GPU capacity for production trafficnot 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 Fireworks AI
- Running several coding agents in parallel against real databases and services instead of on a laptopnot Fireworks AI
- Keeping source code off contractor and offshore laptops by moving the whole environment into a controlled accountnot Fireworks AI
- Reproducing a hard-to-configure toolchain for a short-lived project without polluting anyone machinenot Fireworks AI
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Fireworks AI
- Reserved and enterprise-tier pricing is not published and requires sales contact.
- Model catalog is curated to ~30 models, smaller than DeepInfra's 100+ model library.
- On-demand GPU rates are scheduled to increase from September 1, adding cost unpredictability for locked-in workloads.
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
Fireworks AI
Free- Serverless$undefined/mo
- Pay-per-token from $0.07 to $1.74 per million input tokens
- $1 free credit to start
- On-Demand$7/month
- Dedicated GPU instances from $7/hour for H100/H200
- Reserved$undefined/mo
- Guaranteed capacity and priority hardware access
- Custom pricing
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 Fireworks AI if
- You need serverless inference.
- You want to start without paying.
- You work on web, api.
- You also want on-demand and reserved deployments.
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.
Questions people ask
- Is Fireworks AI or Ona (formerly Gitpod) better?
- Neither clearly leads. Fireworks AI 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, Fireworks AI or Ona (formerly Gitpod)?
- Fireworks AI starts at Free and Ona (formerly Gitpod) at Free.
- Does Fireworks AI or Ona (formerly Gitpod) run on more platforms?
- Fireworks AI runs on web, api. Ona (formerly Gitpod) runs on Web, Linux, macOS, Windows, AWS, Google Cloud Platform.
- Can I use Fireworks AI for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Fireworks AI best used for?
- Fireworks AI is most often used for deploying open-source llms behind an openai-compatible api, fine-tuning models with lora or full-parameter training, routing ai coding assistant traffic to cheaper models via nexus, reserving dedicated gpu capacity for production traffic. Of those, deploying open-source llms behind an openai-compatible api and fine-tuning models with lora or full-parameter training are not what Ona (formerly Gitpod) is typically brought in for.
- What can Fireworks AI do that Ona (formerly Gitpod) cannot?
- Fireworks AI covers Serverless inference, On-demand and reserved deployments, Managed fine-tuning, OpenAI/Anthropic API compatibility. Ona (formerly Gitpod) covers Ephemeral environments, Agent sessions, Bring your own cloud, Devcontainer standard.
Answered from the vendors’ own pages
Fireworks AI: How is Fireworks AI billing calculated?
Serverless inference uses postpaid, pay-per-token billing across Standard, Priority, and Fast tiers, with rates from $0.07 to $1.74 per million tokens depending on model.
SourceOna (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.
Fireworks AI: Is there a free tier or trial credit?
New accounts receive $1 in free credit to try serverless inference before adding a payment method.
SourceOna (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.
Fireworks AI: How much do on-demand GPU deployments cost?
Dedicated on-demand instances range from $7-8/hour for H100/H200 GPUs up to $18-20/hour for GB300, billed per GPU second with no start-up surcharge.
SourceOna (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.
Fireworks AI: How is fine-tuning priced?
Managed training is billed per 1 million training tokens for supervised or preference tuning, while reinforcement tuning is billed per GPU hour.
SourceOna (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.
Fireworks AI: Does region selection affect pricing?
Yes, region-restricted on-demand deployments carry a 1.5x premium over standard regional pricing.
SourceRelated pages
More on Fireworks AI
More on Ona (formerly Gitpod)
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- Ona (formerly Gitpod) vs Oracle Cloud
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- Ona (formerly Gitpod) vs Packer
- Ona (formerly Gitpod) vs OpenTelemetry
- Ona (formerly Gitpod) vs Coder
- Ona (formerly Gitpod) vs CodeSandbox
- Ona (formerly Gitpod) vs StackBlitz
- Ona (formerly Gitpod) vs Namespace
- Ona (formerly Gitpod) vs Daytona
- Ona (formerly Gitpod) vs Earthly
- Ona (formerly Gitpod) vs Nixpacks
- Ona (formerly Gitpod) vs Spacelift
- Ona (formerly Gitpod) vs Atlantis
- Ona (formerly Gitpod) vs Backstage
- Ona (formerly Gitpod) vs Cloud Native Buildpacks
- Ona (formerly Gitpod) vs ConfigCat
- Ona (formerly Gitpod) vs Xlinesoft
- Ona (formerly Gitpod) vs GNU Emacs
- Ona (formerly Gitpod) vs Keil MDK
- Ona (formerly Gitpod) vs Vite
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