RamaLama
Run local LLMs in locked-down containers with an Ollama-style CLI.
About
RamaLama is an open-source command line tool from Red Hat that makes running AI models locally deliberately boring. It pulls models from OCI registries, Ollama, and Hugging Face, then runs them inside rootless Podman or Docker containers rather than on the host OS, so a model process cannot see host files or reach the network during inference.\n\nIt supports both llama.cpp and vLLM as inference backends, ships a built-in web chat UI with the serve command, and can generate Podman Quadlet files to run a model as a systemd service on edge devices. Red Hat positions it as the security-conscious counterpart to Ollama for teams that cannot risk a model process touching the underlying host.
What it can do
- Pull models from OCI, Ollama, and Hugging Face registries
- Run inference inside isolated rootless containers with no network access
- Serve models as OpenAI-compatible endpoints plus a built-in web chat UI
- Generate Podman Quadlet systemd units for edge and production deployment
- Support both llama.cpp and vLLM inference backends
Setup
Install the ramalama binary from the GitHub releases or your distro package manager, then run ramalama run <model>.
Prerequisites
Podman or Docker installed; a GPU helps but CPU fallback works.
Use cases
Works with
Trust score — 8/10
Scored 8/10 (verified tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 100; Trending score 82/100 from researcher assessment.
Sources
Every fact above was checked against these sources. Where a claim comes from the provider and couldn't be independently verified, the text says so.