Ollama GPU-Accelerated LLM Server | Support by cloudimg

This is a repackaged open source software product wherein additional charges apply for cloudimg support services.

Deploying Ollama on a GPU instance manually means installing NVIDIA drivers, configuring systemd services, setting up a reverse proxy, adding authentication, and provisioning storage for model weights. Most open-source Ollama deployments ship with no authentication, no proxy, and no separated storage - leaving you to handle production hardening yourself. This image eliminates that operational burden: launch the instance and your private, authenticated LLM endpoint is serving requests within minutes, with no manual driver installation, no proxy configuration, and no default credentials.

Ollama is the easiest way to run open large language models locally. It downloads, quantizes, and serves models such as Llama, Mistral, Gemma, Phi, Qwen, and DeepSeek with a single command, exposing a REST API that is also OpenAI chat-completions compatible. This image delivers Ollama fully installed and configured as a system service on an NVIDIA GPU instance, so a private, self-hosted LLM endpoint is running within minutes of launch. The current release available is Ollama 0.30.

This image is built and shipped for NVIDIA GPU instances (g4dn, g5, g6 families). The NVIDIA datacenter driver is preinstalled and verified on real hardware during the build, and Ollama auto-detects the GPU to offload model inference, delivering far higher throughput than CPU. Launch on a GPU instance type and your models run on the GPU out of the box.

Ollama runs as an unprivileged service account on the loopback address, with an nginx reverse proxy fronting it on port 80. A systemd service starts the server on boot and restarts it on failure. Model weights live on a dedicated, independently resizable storage volume kept separate from the operating system disk, and a small starter model is pre-pulled so the API responds immediately.

Ollama ships with no built-in authentication, so access is gated by HTTP Basic Authentication at the nginx reverse proxy. This image generates a fresh password, unique to your instance, on its first boot and writes it to a root-only file. The public version endpoint stays open for load balancers; model pull, generate, chat, and the OpenAI-compatible endpoints all require the password. No shared or default credentials ship in the image.

Pull a model with'ollama pull', chat from the CLI, or call the REST and OpenAI-compatible endpoints from LangChain, LlamaIndex, or any OpenAI SDK by pointing base_url at your instance. Use Ollama as a drop-in private LLM backend for your own applications.

• A private, self-hosted LLM endpoint in your own VPC for teams with data residency or compliance requirements - no data leaves your account
• GPU-accelerated inference for Llama, Mistral, Gemma, Qwen, and DeepSeek
• A drop-in OpenAI-compatible backend for RAG and agent applications
• Offline and air-gapped LLM serving

24/7 technical support by email and live chat. Our engineers help with Ollama deployment, model selection, GPU sizing, quantization, the OpenAI-compatible API, TLS termination, and scaling. Critical issues receive a one-hour average response.

All product and company names are trademarks or registered trademarks of their respective holders. Use of them does not imply any affiliation with or endorsement by them.