Key facts
| Ollama | Local model runner with a pull-and-run workflow |
| Ollama Cloud | Hosted models used with the same Ollama tooling after sign-in |
| API style | Ollama-native API with an OpenAI-compatible local endpoint |
| Primary use | Development, prototyping and personal workflows |
| Plugsky model | Managed production API for applications and teams |
| Catalogue | 30+ models under one OpenAI-compatible API |
| Plans | Flat monthly self-serve plans; free plan with two models |
| Deployment | Cloud, VPC, on-prem or air-gapped |
TL;DR
- Ollama Cloud extends the local workflow to hosted models and suits experimentation.
- Plugsky is built for production: one API, team keys, plans and private deployment.
- Both can coexist: prototype with Ollama, ship on a managed endpoint.
- Moving between them is mostly a base URL and model-name change.
- Start free with plugsky-micro and plugsky-lite before committing to a plan.
How it works, step by step
- Prototype the workload with Ollama locally or Ollama Cloud using your real prompts.
- Record the model names, parameters and prompt templates you settled on.
- Create a Plugsky key and call the endpoint from a staging branch.
- Map the prototype model to the closest Plugsky model and re-run your evaluation set.
- Add authentication, limits and logging for multi-user production traffic.
- Move to a paid plan or private deployment when usage outgrows the pilot.
Try it yourself
Open the Ollama Cloud API cost calculator →
Two different jobs
Ollama exists to make local models easy: pull a model, run it, and talk to it through a simple API that also speaks the OpenAI dialect. Ollama Cloud extends that convenience to larger models hosted for you, so the same commands and client code work without a workstation-class GPU.
That design is optimised for one developer exploring a workload. It is not optimised for team accounts, quotas, audit trails or service-level commitments, which are the things production teams eventually need.
Where Ollama Cloud fits
Ollama Cloud is a strong fit for evaluation: comparing model families, testing prompt strategies and building throwaway prototypes. Because the local API is OpenAI-compatible, code written against it can often move to another endpoint with minimal changes, which keeps the experimentation cheap.
It is also useful when a developer wants occasional access to a bigger model than their machine can host. The trade is dependency on the Ollama ecosystem for authentication and model availability rather than a general-purpose platform contract.
The production path
Production adds requirements that local-first tooling does not target: multiple API keys, usage separation per team, uptime expectations, data-handling terms and regional controls. Plugsky provides those through a managed OpenAI-compatible API covering 30+ models, with a free plan, a 14-day full-access trial and VPC, on-prem and air-gapped deployment for stricter environments — see the live pricing page for current plans.
The honest limit: if your workflow depends on Ollama-native APIs, Modelfiles or the exact local model builds you tuned, staying with Ollama is reasonable. Plugsky does not reproduce that local-first model management; it replaces the production serving layer.
Honest comparison
| Dimension | Plugsky | Ollama Cloud | Local Ollama |
|---|---|---|---|
| Purpose | Production API for teams | Hosted models for the Ollama workflow | Local development and privacy |
| API surface | OpenAI-compatible | Ollama-native with OpenAI-compatible access | Ollama-native with OpenAI-compatible endpoint |
| Model catalogue | 30+ models across families | Ollama-hosted model line-up | Whatever you pull locally |
| Team features | Keys, plans, usage | Account-based access | Single user |
| Residency | Region choice, VPC, on-prem, air-gapped | Provider-hosted | On your machine |
| Cost shape | Free plan, then flat monthly plans | Provider usage terms | Free, your hardware |
Frequently asked questions
Is Ollama Cloud a production API?
It is designed around developer convenience rather than service contracts. Teams that need team keys, quotas, audit and uptime commitments usually move to a platform built for that.
Can I switch from Ollama to Plugsky easily?
Often yes. Both can expose OpenAI-compatible endpoints, so you change the base URL and model name, then re-test prompts and parameters.
Does Plugsky run models locally?
No. Plugsky is a managed cloud API. For workloads that must stay inside your perimeter it offers VPC, on-prem and air-gapped deployment options.
Which models are available on Plugsky?
The catalogue spans 30+ models across families, from small efficient models to frontier tiers. Check the live catalogue for the current line-up.
Is there a free way to start?
Yes. The free plan includes plugsky-micro and plugsky-lite with no card, and new accounts get a 14-day full-access trial.
How should I split work between local and cloud?
Prototype locally for speed and privacy, then run production traffic on a managed endpoint where authentication, scaling and residency are handled for you.
Does Ollama Cloud keep my data local?
No. Cloud models run on provider infrastructure. Only local Ollama keeps inference on your own machine, which is a key reason teams pair local development with managed production.