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By Zayden R., August 5, 2026
Fedora Linux users can now run large language models like Llama 3 locally using Ollama with Podman. This setup keeps systems clean and simplifies AI model management, making it easier for developers to experiment and test offline.
Fedora Linux users interested in running large language models (LLMs) locally have a new option with the release of Ollama, which can now be containerized using Podman. This development is particularly significant for developers who wish to maintain a clean host environment while experimenting with AI models like Llama 3 or Mistral.
Ollama, an open-source framework, simplifies the management of LLMs by packaging model weights, configurations, and data into a unified system. By running Ollama within a Podman container, users avoid dealing with local dependencies, Python environments, or GPU driver configurations on their base OS. This setup is especially useful for those on Fedora Workstation or Silverblue, where Podman is natively available.
To get started, users should verify Podman's installation, which can be done via a simple command: podman --version. If Podman is missing, it can be installed using DNF on Fedora Workstation: sudo dnf install podman -y. Fedora Silverblue users will find Podman readily available as part of the immutable base system.
One crucial step in setting up Ollama is creating a persistent Podman volume to store LLM weights, which can range from 4 GB to over 40 GB. This prevents the need to download models every time the container restarts. The command podman volume create ollama_storage facilitates this process.
Once the volume is set, users can run the Ollama container by pulling the official image and attaching the volume. The command podman run -d -v ollama_storage:/root/.ollama -p 11434:11434 --name ollama ollama/ollama will spin up the container, mapping the necessary communication port to the host machine.
For those seeking hardware acceleration, especially on systems equipped with Nvidia GPUs, installing the Nvidia Container Toolkit and using the GPU flag --device nvidia.com/gpu=all allows Ollama to leverage GPU resources for enhanced performance.
This setup empowers developers to run and test AI models locally without the hassle of complex configurations, offering a streamlined approach to AI model management on Fedora Linux.
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