Openship
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AI & models

vLLM

NVIDIA GPU required · Self-hosted only

OpenAI-compatible model serving on a self-hosted NVIDIA GPU. Preview pending real GPU installation tests.

OpenAI-compatible API

Connect existing inference clients.

NVIDIA inference

Request one GPU with private container shared memory.

Persistent model cache

Reuse downloads and compilation caches.

NVIDIA inference preview

This template uses vLLM's official CUDA image, one NVIDIA GPU and a generated API key for its OpenAI-compatible API. It is listed as a preview and cannot be installed yet: real NVIDIA hardware validation is still required. It is self-hosted only and does not support managed Cloud or CPU-only servers.

The server needs a compatible NVIDIA driver and NVIDIA Container Toolkit. The selected model must fit the GPU's VRAM; ordinary RAM guidance does not measure VRAM or reserve GPU capacity. Openship does not provision GPUs or install drivers.

Model and startup

The initial model is Qwen/Qwen3-0.6B. Choose a different Hugging Face model and, when required, provide a token and accept its license on Hugging Face. The first start downloads and loads the model. Check Logs for progress; a starting health check is not proof of a failed deployment.

The template persists model downloads and compilation caches. It gives the container a private 2 GiB /dev/shm, without sharing the host IPC namespace or enabling privileged mode. Context length, model choice and concurrency determine memory demand.

Use the generated API key as a bearer token for /v1 requests. Keep that key private. The pinned image's CUDA version must be compatible with the host driver; this preview is not a guarantee for every NVIDIA card or model.

Official Docker deployment · GPU requirements

Included in this template

The services configured by the catalog, deployed together as one project.

vllm

vllm/vllm-openai:v0.31.0