Ollama is not "free only" anymore, has paid versions.
But the installer is not digitally signed, and is HUGE, 2 GB.
So Windows 11 rejects it for security reasons.
But the installer is not digitally signed, and is HUGE, 2 GB.
So Windows 11 rejects it for security reasons.
Ollama can be run in Docker using its official Docker image.
Running Ollama in a container provides a clean, isolated environment and simplifies deployment across different systems. [1, 2, 3, 4]
CPU-only:
CPU-only:
docker run -d -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama
Nvidia GPU support (Requires NVIDIA Container Toolkit):
Nvidia GPU support (Requires NVIDIA Container Toolkit):
docker run -d --gpus=all -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama
AMD GPU support:
AMD GPU support:
docker run -d --device /dev/kfd --device /dev/dri -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama:rocm
1.4 GB
The Ollama Docker container appears significantly larger than the native Windows installation primarily due to a space-for-time tradeoff and the nature of how Docker reports image sizes.
1. Uncompressed Run-Time Payload
In recent versions (0.3.11+), Ollama developers changed how the Docker image is built to prioritize startup speed.
- Windows/Linux Native: The installer carries compressed LLM runner executables and libraries that are extracted to a temporary directory at runtime. This saves disk space but adds a 5–20 second delay during every startup.
- Docker Container: To make container startup nearly instantaneous (less than a second), these runners and libraries are stored uncompressed and ready-to-execute within the container's root filesystem. [1]
2. Reported vs. Compressed Size
When you view image sizes in Docker, it displays the uncompressed size of the entire filesystem. [1]
- The actual "wire size" (what you download from Docker Hub) is often much smaller because the layers are compressed during transit.
- The native Windows installer size reflects the compressed package, whereas the Docker "Size" column reflects the fully expanded environment. [1]
Summary of Differences
gemma4
Gemma 4 models are designed to deliver frontier-level performance at each size. They are well-suited for reasoning, agentic workflows, coding, and multimodal understanding.
Gemma 4 models are designed to deliver frontier-level performance at each size. They are well-suited for reasoning, agentic workflows, coding, and multimodal understanding.
docker run -d \
-v ollama:/root/.ollama \
-p 11434:11434 \
--name ollama \
ollama/ollama
-v ollama:/root/.ollama \
-p 11434:11434 \
--name ollama \
ollama/ollama
docker run -d \
--gpus=all \
-v ollama:/root/.ollama \
-p 11434:11434 \
--name ollama \
ollama/ollama
# and with the flag as...
--gpus=all Passes all available GPUs to the container (this one requires the NVIDIA Container Toolkit)
--gpus=all \
-v ollama:/root/.ollama \
-p 11434:11434 \
--name ollama \
ollama/ollama
# and with the flag as...
--gpus=all Passes all available GPUs to the container (this one requires the NVIDIA Container Toolkit)
docker exec -it ollama ollama run llama3
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