Managed Ollama Hosting
AI & MLRun large language models locally
Ollama makes it easy to run LLMs on your own infrastructure with GPU acceleration and an OpenAI-compatible API — deployed and fully managed by ManageStacks on AWS, Azure, or GCP with GPU drivers and model storage included.
About Ollama
Ollama makes it easy to run large language models on your own infrastructure. It bundles model weights, configuration, and runtime into a single package, providing a simple API for running models like Llama, Mistral, Gemma, and many more.
With Ollama, you get full control over your AI inference without sending data to third-party APIs. It supports GPU acceleration, model customization through Modelfiles, and an OpenAI-compatible API for drop-in replacement of cloud AI services.
Key Features
- One-command model download and execution
- OpenAI-compatible REST API
- GPU acceleration with CUDA and Metal support
- Modelfile for custom model configuration
- Support for Llama, Mistral, Gemma, and more
- Multi-model serving from a single instance
How ManageStacks Helps
ManageStacks deploys Ollama on GPU-enabled infrastructure with optimized memory configuration and model storage. We handle GPU driver management, model caching, and performance monitoring so you can run private AI inference at scale.
Frequently Asked Questions
Does ManageStacks provide GPU support for Ollama?+
Yes. ManageStacks provisions Ollama on GPU-enabled infrastructure with CUDA drivers pre-installed and optimized memory configuration.
Can I use Ollama as a drop-in OpenAI replacement on ManageStacks?+
Yes. Ollama exposes an OpenAI-compatible API, so you can point any OpenAI SDK application to your ManageStacks-hosted Ollama endpoint by changing the base URL.
How do I add new models to Ollama on ManageStacks?+
You can pull models from the Ollama library via the API or CLI. ManageStacks provides persistent model storage so downloaded models survive restarts and updates.
