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CPU only

docker run -d -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama

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Nvidia GPU

Install the NVIDIA Container Toolkit.

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Install with Apt

  1. Configure the repository 
    curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey \
    | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg
curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list \
    | sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' \
    | sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
sudo apt-get update
  2. Install the NVIDIA Container Toolkit packages 
    sudo apt-get install -y nvidia-container-toolkit

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Install with Yum or Dnf

  1. Configure the repository 
    curl -s -L https://nvidia.github.io/libnvidia-container/stable/rpm/nvidia-container-toolkit.repo \
    | sudo tee /etc/yum.repos.d/nvidia-container-toolkit.repo
  2. Install the NVIDIA Container Toolkit packages 
    sudo yum install -y nvidia-container-toolkit

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Configure Docker to use Nvidia driver

sudo nvidia-ctk runtime configure --runtime=docker
sudo systemctl restart docker

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Start the container

docker run -d --gpus=all -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama
[!NOTE]
If you’re running on an NVIDIA JetPack system, Ollama can’t automatically discover the correct JetPack version. Pass the environment variable JETSON_JETPACK=5 or JETSON_JETPACK=6 to the container to select version 5 or 6.

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AMD GPU

To run Ollama using Docker with AMD GPUs, use the rocm tag and the following command: 
docker run -d --device /dev/kfd --device /dev/dri -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama:rocm

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Run model locally

Now you can run a model: 
docker exec -it ollama ollama run llama3.2

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Try different models

More models can be found on the Ollama library.