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Ollama
CommunityRun large language models locally — pull and serve open models like Llama, Qwen, and Gemma through a simple REST API.
| Runs | ollama/ollama:0.40.5 |
|---|---|
| Stack | go |
| Provisioned for it | Nothing, it's self-contained |
| Verified | Not yet |
Why deploy on Railyard
Railyard runs it standalone on a server you already pay for — no addons to provision, with zero-downtime deploys and scaling still included.
Deploying Ollama is one piece of a bigger stack you can keep building — add a database, a worker, a cache, or another app, all on the same servers you already pay for.
Good for
- Self-hosted LLM inference for Open WebUI, Langflow, or a custom app
- Running open models like Llama and Qwen without sending data to a third-party API
- A local OpenAI-compatible endpoint for development
Good to know
- No GPU is attached automatically — CPU-only inference works but is slow for larger models
- Nothing is bundled by default — pull a model after deploy, e.g. `ollama pull llama3.2`